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Toronto Rehab Lyndhurst Centre 520 Sutherland Dr.

Toronto, ON Canada, M4G 3V9

Phone: 416-597-3422 ext 6206 Web: www.toronto-fes.ca E-mail: [email protected]

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Rehabilitation Engineering Laboratory – 2008

Contact us:

Lyndhurst Centre Toronto Rehab 520 Sutherland Dr. Toronto, ON M4G 3V9 Canada

416-597-3422 x 6206

www.toronto-fes.ca

[email protected]

About the Rehabilitation Engineering Lab

History

The Rehabilitation Engineering Laboratory was established in 2001 at the Lyndhurst

Centre of Toronto Rehab. In 2006, the laboratory underwent a major renovation,

doubling the amount of space available for personnel and experiments.

What We Do

We develop advanced technologies for spinal cord injury (SCI) and stroke

rehabilitation. These include brain/machine interfaces, assessment tools for

determining an individual’s level of function, and rehabilitation techniques for restoring

walking and grasping ability. We also design neuroprosthesis systems to assist

individuals with tasks such as walking, grasping, and balance during standing and

sitting.

Most of our work is based on functional electrical stimulation (FES), which uses

electricity to cause muscles to contract. FES can be used to provide movement to

paralyzed muscles or to re-train weak muscles or the central nervous system.

Accomplishments – 2006 to 2008

• Developed FES therapies for neuro-rehabilitation in stroke and SCI

• Provided FES therapy to more than 50 individuals with SCI or stroke

• Published more than 22 peer-reviewed journal papers

• Obtained more than $2,000,000 in funding for SCI and stroke research

• Trained 8 postdoctoral fellows, and 16 graduate students in SCI and stroke

research, who obtained an additional $1,200,000 in funding

Want to Get Involved?

We’re always looking for participants for our studies, volunteers to help us with the

experiments, students and research collaborators. If you’d like to join us, please feel

free to contact us at 416-597-3422 ext. 6206, or via e-mail at

[email protected].


Contact us:


416-597-3422 x 6206

www.toronto-fes.ca

[email protected]

Research at the Rehabilitation Engineering Laboratory Neuroprosthesis for Reaching and Grasping

Our reaching and grasping neuroprosthesis is designed for individuals who cannot

reach and/or grasp voluntarily. These individuals are able to use the system to pick up

and manipulate objects, and can significantly improve their independence in activities

of daily living. People who have SCI at C5-C7 level or stroke have used this system as

a rehabilitation tool to assist in retraining reaching and grasping.

Neuroprosthesis for Walking

The purpose of the neuroprosthesis for walking program is to demonstrate the long-

term benefits of FES therapy on walking function in patients with incomplete SCI and

stroke. Our pilot study showed a significant improvement in walking speed and/or a

reduction in the use of assistive devices for walking after using the neuroprosthesis.

We are currently conducting a randomized treatment-vs-control study to verify that

these benefits truly resulted from FES-assisted therapy.

Neuroprosthesis for Sitting

Trunk instability is a major problem for many people with SCI that affects their

independence and ability to perform activities of daily living. The long-term objective of

this project is to produce a new device that will improve sitting stability by stimulating

paralyzed trunk muscles using FES. This sitting neuroprosthesis will improve the

ability of people with SCI to perform such tasks as reaching and wheeling. We are

currently studying the mechanisms of balance in the trunk and the consequences of

muscle paralysis on these mechanisms. This analysis will form the basis for

developing the FES system for balance during sitting.


Contact us:


416-597-3422 x 6206

www.toronto-fes.ca

[email protected]

Neuroprosthesis for Standing

The neuroprosthesis for standing and balancing is a device that will allow some

neurologic patients to stand up, perform stable “hands-free” standing, and sit down

again. At least two applications of this technology are envisioned: 1) this device will be

used as an independent system to allow complete SCI patients to stand; and 2) to

retrain standing function and balance control in incomplete SCI, stroke and elderly

patients through active, repetitive, balance training sessions. Besides the obvious

functional benefits, this neuroprosthesis would also help maintain bone density and

prevent pressure sores by allowing people to stand for extended periods of time.

Human-Machine Interfaces

Understanding the relationship between an assistive device and its user is a

fundamental step towards designing better systems. The human-machine interface

project focuses on developing new communication strategies and methodologies to

allow users to have more natural control over an assistive device. One aspect of this

work is our research into brain-machine interfacing, which investigates the relationship

between intended arm movement and electroencephalogram (EEG) signals from the

motor cortex of the brain.

Equipment

The Rehabilitation Engineering Laboratory has a variety of research equipment

including:

• Compex II stimulators

• Body weight support treadmill

• Force plates

• Polhemus motion capture system

• Optotrack dual camera motion capture systems

• Erigo tilt table with motorized leg movement

• Electromagnetically shielded room for EMG and EEG measurements

• Vibration platforms

• REL-PAPPS perturbation system


Our People

Principal Investigators

• Dr. Milos R. Popovic, Head of the Laboratory, Toronto Rehab Chair in Spinal Cord Injury Research, Senior Scientist, and Associate Professor

• Dr. Mary Nagai, Research Scientist and Assistant Professor • Dr. Kei Masani, Research Scientist

Postdoctoral Fellows

• Dr. Judith Hunter (neuroscience), Postdoctoral Fellow • Dr. Richard Preuss (physiotherapy), Postdoctoral Fellow • Dr. Dimitry Sayenko (medical doctor), Postdoctoral Fellow • Dr. Masae Miyatani (exercise physiology), Postdoctoral Fellow • Dr. Dany Gagnon (physiotherapy), Postdoctoral Fellow

Graduate Students

• Cheryl Lynch, PhD student • Cesar Marques Chin, PhD student • Albert Vette, PhD student • José Zariffa, PhD student • Davide Agnello, MASc student • Milad Alizadeh-Meghrazi, MASc student • Rob Babona Pilipos, MASc student • Steve McGie, MASc student • Egor Sanin, MASc student • John Tan, MASc student • Massimo Tarulli, MASc student • Takashi Yoshida, MASc student

Support Staff

• Shaghayegh Bagher, Research Engineer • Zina Bezruk, Administrative Assistant • Abdul Bulsen, Research Engineer • Betty Chan, Grants & Accounts Coordinator • Suzy Iafolla, Physiotherapist • Naaz Kapadia, REL Manager, Research Coordinator and Physiotherapist • Abdulazim Rashidi, Research Engineer • Dr. Vera Zivanovic, Research Coordinator

Contact us:


416-597-3422 x 6206

www.toronto-fes.ca

[email protected]


Contact us:


416-597-3422 x 6206

www.toronto-fes.ca

[email protected]

Awards Dr. Milos R. Popovic 2008 Professional Engineers Research

and Development Award Professional Engineers of Ontario and Ontario Society of Professional Engineers

2007 Toronto Rehab Chair in Spinal Cord Injury Research

Toronto Rehabilitation Institute

Albert Vette 2008 Norman F. Moody Award in

recognition of academic excellence

Institute of Biomaterials and Biomedical Engineering, University of Toronto

2008 Best Student Paper Award – First Place

3rd National Spinal Cord Injury Conference, Toronto, Canada, November 6-8, 2008.

2008 Best Student Paper Award – Second Place

13th Annual Conference of the International FES Society, Freiburg, Germany, September 21-25, 2008

2007 Engineering Postgraduate Prize for most Outstanding Doctoral Candidate

Natural Sciences and Engineering Research Council of Canada

Jose Zariffa 2007 Best Student Paper Award –

Third Place 30th Canadian Medical and Biological Engineering Conference, FICCDAT, Toronto, Canada, June 16-19, 2007.

Dr. Judith Hunter 2007 Northrop Frye Award University of Toronto


Contact us:


416-597-3422 x 6206

www.toronto-fes.ca

[email protected]

Recent Research Posters Neuroprosthesis for Grasping

1. “Functional electrical therapy: Retraining reaching and grasping functions in severe hemiplegic patients”

2. “Effect of intensive functional electrical therapy on the upper limb motor recovery after stroke: Single case study of a chronic stroke patient”

3. “FES therapy: Restoring voluntary grasping function”

Neuroprosthesis for Walking

4. “Necessity of successive sensory feedback to update the internal model for walking”

5. “Oxygen uptake during FES treadmill walking: Case study”

Neuroprosthesis for Standing

6. “Frequency response of stimulated knee movement”

7. “Optimal combination of minimum degrees of freedom to be actuated for the facilitation of arm-free paraplegic standing”

8. “Step prediction during perturbed standing using center of pressure measurements”

9. “Control mechanism of ankle muscles during standing”

10. “Motor command of proportional and derivative (PD) controller can match ankle torque modulation during quiet stance”

11. “Stochastic modeling of knee response”

Neuroprosthesis for Sitting

12. “Muscle recruitment patterns in perturbed sitting”

13. “Center of pressure excursion during voluntary trunk movement in sitting”

14. “Posturography measures during quiet sitting”


Contact us:


416-597-3422 x 6206

www.toronto-fes.ca

[email protected]

Human-Machine Interfaces

15. “Identifying movements from cortical signals”

16. “Localizing active pathways in peripheral nerves“

17. “Control of multiple degree-of-freedom tasks using one-dimensional electroencephalographic signals”

18. “ECoG controlled neuroprosthesis for grasping: Preliminary study”

19. “Influence of the number and location of recording contacts on the selectivity of a nerve cuff electrode”

Other Projects

20. “The relationship between arterial stiffness and body composition in persons with spinal cord injury”

21. “A test-of-principle prototype for a new device to measure a specific pain mechanism: Translating pain neuroscience theory into a clinical/research tool”

22. “Cardiovascular response to FES and passive stepping to improve orthostatic tolerance”

23. “Wave ® vs. Juvent ®: Whole-body vibration assessment: Feasibility & usability for patients with SCI”

24. “A new intramuscular electrode for functional electrical stimulation in the rat”

Partners:

Canadian Institutes of Health ResearchInstituts de rechere en santé du Canada

Natural Sciences and Engineering Research Council of CanadaConseil de recherches en sciences naturelles et en génie du Canada

Physicians' Services Incorporated FoundationMinistry of Health and Long Term Care

FUNCTIONAL ELECTRICAL THERAPYM.R. Popovic, A.T. Thrasher and V. Zivanovic

Rehabilitation Engineering LaboratoryInstitute of Biomaterials and Biomedical Engineering, University of TorontoToronto Rehabilitation InstituteContact: [email protected]

Toronto Rehabilitation Institute and University of Toronto

Retraining Reaching and Grasping Functions in Severe Hemiplegic Patients

PARTICIPANTS:Stroke patients with severe unilateral upper extremity paralysis.Chedoke McMaster Stages of Motor Recovery scores 1 or 2 measured at least three weeks after onset of stroke.Participants unable to voluntarily:

• flex, extend, abduct, adduct, or rotate the shoulder; • flex or extend the elbow;• pronate or supinate the forearm; • flex, extend, abduct or adduct the wrist; • move any fingers;

Participants were acute (0 – 6 weeks post stroke) or long-term (12 months after stroke).

Group A - control group had standard physiotherapy and occupational therapy alone.

Group B - treatment group had functional electrical stimulation (FES) therapy administered in addition to conventional physiotherapy and occupational therapy.

FUNCTIONAL TESTS: • Functional Independence Measure (FIM)• Barthel Index (BI)• Chedoke McMaster Stages of Motor Recovery (CMSMR)• Fugl-Meyer Assessment (FMA)• REL Hand Function Test (REL) [1]

FES THERAPY PROTOCOL:Participant was asked to execute a task with the impaired arm (e.g. reaching and grasping a pen) unassisted. The components of the task that the participant was unable to carry out him/herself were assisted by the neuroprosthesis. Compex Motion neuroprosthesis was used for FES therapy [1].In the early stages of the treatment, the arm/hand tasks were performed by the neuroprosthesis alone. As the patient improved, the neuroprosthesis assistance was reduced to the necessary minimum and eventually was removed from the treatment protocol. The patient had three treatment sessions per week, 45 minutes per session, up to 16 weeks.

Materials and Methods

Fig. 1: a) Finger extension performed with the help of neuroprosthesisb) Voluntary finger flexion

b)a)

CONTROL GROUP PROTOCOL:Standard physiotherapy and occupational therapyControl group sessions were equal in length and intensity to the FES therapy sessions.

STATISTICAL ANALYSIS:Wilcoxon rank-sum test

ResultsSUMMARY:

The study was conducted with 24 stroke patients (8 female, 16 male; average age 56):

• 15 participated in FES therapy• 9 were controls

The difference between mean scores obtained on discharge and admission for both Groups A and B are shown in Fig 2. Significant differences were found between Groups A and B in terms of change of the FMA and the torque, force and eccentric load components of the REL Hand Function Test.The statistical analysis suggests that the FES therapy gives rise to greater improvement in arm and hand functions, compared to traditional physiotherapy and occupational therapy alone.

References:[1] Popovic M.R., Thrasher T.A., Zivanovic V., Takaki J., and Hajek

V., Neuroprosthesis for restoring reaching and grasping functions in severe hemiplegic patients. Nauromodulation, 2005. 8(1): p. 60-74.

*

**

**

Fig. 2: Differences between the after and before mean scores for: 1-5) REL Test; 6) FIM; 7) BI; 8) FMA; and 9) CMSMR tests. Statistical significance of the difference is presented as follows: * p < 0.05, and ** p < 0.01.

1

2. MethodsSubject

A 22-year-old woman who had suffered a hemorrhagic stroke 2 years earlier.

Noritaka Kawashima , Vera Zivanovic , Milos R. PopovicInstitute of Biomaterial and Biomedical Engineering, University of Toronto, CanadaLyndhurst Centre,Toronto Rehabilitation Institute, CanadaJapanese Society for Promotion of Science, Japan

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1,2,3 1,2

Partners:

Canadian Institutes of Health ResearchInstituts de rechere en santé du CanadaCanadian Institutes of Health ResearchInstituts de rechere en santé du Canada

Natural Sciences and Engineering Research Council of CanadaConseil de recherches en sciences naturelles et en génie du CanadaNatural Sciences and Engineering Research Council of CanadaConseil de recherches en sciences naturelles et en génie du Canada

Ministry of Healthand Long Term CareMinistry of Healthand Long Term Care

Effect of Intensive Functional Electrical Therapyon the Upper Limb Motor Recovery after Stroke

1. Background

What extent of motor recovery can be deliveredby FET for chronic stroke patients?

1. the subject can feel that the proper movement of the paralyzedlimbs and has been acomplished following their appropriate effort

2. sensory signals might be generated by the excitation of afferentpathways in the stimulated peripheral nerves

3. Results

FET is a treatment that integrates electrical stimulation of sensory motorsystems and repetitive functional movement of the paretic arm in hemiplegicpatients.

4. Discussion

FET has a potential to decreaseabnormal spinal motoneuronalexcitability

While motor recovery scored by CMSA scale and MVC level ofupper arm muscles did not show remarkable changes, the patientshowed improvement of upper arm functional motion.

The present results suggest that intensive FET has the capability toimprove upper arm functional movement, specifically by the reduction

of muscle tone for chronic stroke patients.

The improvement of the upper arm functional motion revealed bykinematical tests can attribute not to the motor recovery itself, but tothe reduction of muscle tone and/or spasticity.

1,2

Single Case Study of a Chronic Stroke Patient

Flex

Ext

Flex

Ext

Shoulder

ElbowTB

aDel pDel

BB

Flex

Ext

Flex

Ext

Shoulder

ElbowBB

aDel pDel

TB

Touch nose (or shoulder)

Swing forward

Abduct

Adduct

Flex

Ext

Shoulder

Elbow

aDelpDel

TB

Left side up 23

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a

b

c

d

ef

aDel

BicepsBrachialis

pDelTricepsBrachialis

Shoulder &Elbow flexor

Shoulder &Elbow extensor

Wrist flexor

Wrist & Finger extensor

B Location of electrodeA FET motion tasks

Touch noseTouch ShoulderSwing forwardLeft side up

FlexionFlexion&Int.rotationExtensionAbduction

FlexionFlexionExtensionExtension

Shoulder & Elbow motion

Wrist & Hand motion

Wrist extension & full finger openWrist flexionTwo finger (Thumb&Index) open

1-4,2-4, & 3-45-61-4

Task Shoulder motion (Electrode) Elbow motion (Electrode)

a-ba-bd-e

a-b & d-e

b-cb-ce-fe-f

Bottle grasping

Small object picking

Task Target motion (Electrode)

While tactile sensation was not severely impaired, motor function of the upper extremity showedthe typical flexor synergy pattern. The patient demonstrated increased resistance to passive stretchin the distal flexor musculature, and did not use her paretic upper limb for functional activities.

Stroke survivors experience significant deficit of sensorimotor functions andhalf of them are left with major functional problems in their hands and armsIf recovery occures it is mostly during the first four weeks after stroke and itis very rare that improvements occur in chronic stroke patients

To investigate the effects of an intensive FET onmotor recovery of a chronic stroke patient.

a potential to restore their upper arm functions, specificallyin chronic stroke patients, is still not fully understoodHowever...

Question:

Purpose:

The results of the drawing test demonstratedan improvement of shoulder and elbow jointcoordination. The subject also showed that aremarkable improvement of dynamic ROM ofshoulder and elbow joints.

Maximal voluntary contraction level of upper arm muscles did not show remarkableimprovements. CMSA scores for arm and hand also showed no changes.

This finding supports the classical concept that muscle tonereduction represents simplistic solutions to the deficit in motorcontrol after stroke.

Functional Electrical Theraphy (FET)

Outcome Measures

FET program

(1) Motor function- CMSA and MVC test

(2) Spasticity assessment- MAS and H-reflex

(3) Kinematical measurements- Drawing test, Dynamic ROM

FET was administrated twotimes per day (one hour ineach session) and carried outfor 12 weeks. The patient hadcompleted all training sessions(in total 108 sessions)

A remarkable reduction of the armspasticity was observed as indicatedby the decrease of MAS and thereduction of H-reflex in the wrist flexormuscle (82.09% to 45.04% in theHmax/Mmax).

At the end of training, the patient was capable of picking up a thin object andtouched her nose which could not be done perior to the training.

Spasticity Assessment

Kinematical measurements

Motor Function

Acknowledgement:The authors acknowledge the support of Toronto Rehabilitation Institute who receives funding under theProvincial Rehabilitation Research Program from the Ministry of Health and Long-Term Care in Ontario.

Muscle activation level (stimulus intensity) which dealt with FET was not enoughto increase muscle strength in chronic stroke

The therapy consisted of two components:

During FET...

Recent studies reported a significant effect of the FET on recovery of upperextremity functions in stroke patients.

Pre-programmed, coordinate muscular stimulation that coincided with the phaseand type of arm motions that patient is trying to move. Stimulus intensity was 2times larger than motor thresholdManual assisted (externally generated) passive motion in order to establishphysiologically correct movement

(1)

(2)

2

Partners:



Ministry of Health and Long Term Care

The views expressed in this poster do not necessarily reflect those of any of the granting agencies.


FES Therapy for Individuals with Complete and Incomplete SCI

FES Therapy: Restoring Voluntary Grasping FunctionM.R. Popovic, N. Kawashima, M.E. Adams, R. Yee and V. Zivanovic

Lyndhurst Centre, Toronto RehabInstitute of Biomaterials and Biomedical Engineering, University of Toronto

MethodsSubjects:

• 23 individuals with acute C4 to C7 SCI• 8 complete

• 3 FES therapy and 5 controls• 15 incomplete

• 7 FES therapy and 8 controls• On admission no active movement in the

wrists and/or fingers - up to less than half the normal active range

Assessments: • Assessments performed before and after the

treatment period • Hand function assessed using the REL

Hand Function Test• ADL assessed using FIM and SCIM• Assessments made without FES

Therapy:• Controls received two “doses” of regular OT

and PT (2h per day), which may have included electrical stimulation for muscle strengthening without the functional component

• Treatment group received one “dose” of conventional therapy (1h per day) plus one “dose” individualized FES programs (1h per day) in which the neuroprosthesis was used to help the patients complete only those movements they were unable to produce on their own

• Treatment was 5 times per week, for up to 8 weeks

Novelty• Programmable transcutaneous FES

system used to deliver short-term therapy

• Goal was to restore voluntary grasping function

• Both individuals with complete and incomplete SCI participated

• FES was not used as a permanent assistive device to facilitate grasping

Conclusions• Repetitive daily FES therapy facilitated the carryover in hand function in all

SCI individuals• ASIA A, B, C and D participants in the treatment group showed larger

improvements as compared to controls• Frequently small improvements in the hand function resulted in

considerable gains as measured by FIM

Results

Popovic et al, Med. Eng. & Physics 2005 Popovic et al, Spinal Cord 2006

3

2. Gait Experiment

In order to evaluate such an interesting phenomena quantitatively, wehave conducted the following very easy and simple gait experiment.

According to self-contemplation, H.O. strongly relies on visual informationduring walking. He told us the following interesting experiences;

Experiments consisted of three consecutive sets of walking at their comfortable speed. Stridetime interval was evaluated from the data obtained from accelerometer (AS-10G, Kyowa Inc.,Japan) placed on the lumber portion of the subjects (see below picture). The data was digitized(1 kHz) and stored in the memory of the data logging system (EDS-400, Kyowa Inc., Japan).

MethodsSubjects

He cannot walk with his eyes closed and is scared to walk in darkness.Interestingly, he needs several tens of seconds after the beginning ofwalking untill he feels "walking is stable."

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1

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1.7

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1st 5 min walk 2nd 5 min walk 3rd 5 min walk

1minbreak

1minbreak

Patient H.O. (sensory loss)

Patient S.N. (hemiplegic stroke)

Normal M.A.

AccelerometerAS-10G, Kyowa Inc.

Sensor

(64yrs, Stroke patient who has complete sensory loss)(61yrs, Stroke patient who has lacks both sensory and motor function)(34yrs, Able-bodied person)

Results

cf. Similar description was partly provided by Rothwell et al. (1982)

Stride interval had larger variability, but kept within a certain range. Averaged stride time interval( gait speed) of patient H.O. was longer (slower) than that of M.A., but shorter (faster) than thatof S.N.

1"12 1"08 "58

The subjects walked on track field with their confortable speed (left picture). The right panel shows time-series stride timeinterval calculated from acceleration data. Triangle markers indicate the timing when O.H. felt "walking was stable".

Kawashima N ,Popovic MRNational Rehabilitation Institute for the Persons with Disability, JapanInstitute of Biomaterial and Biomedical Engineering, University of Toronto, CanadaLyndhurst Centre,Toronto Rehabilitation Institute, CanadaJapanese Society for Promotion of Science, Japan

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1,2,3,4 2,3

Partners:



Physicians' Services Incorporated FoundationMinistry of Healthand Long Term CareMinistry of Healthand Long Term Care

Necessity of Successive Sensory Feedbackto Update the Internal Model for Walking

1. BackgroundWalking is a highly sophisticated movement

in human behaviorEven when we walk on an unstable surface, we can unconsciouslyaccomplish stable walking within a few steps.

Given the previous finding about the internal model,two major mechanisms have been hypothesized tounderlie the above phenomenon of walking:

1. A predictive process according to previousexperiences (i.e., using the internal model)

2. A modifying process that detects a mismatchbetween the planned and actual movement(i.e., updating the internal model).

(Kawato et al. 1987)

3. Patient's InformationH.O. is a 64 year old stroke patient. While he has complete sensory lossin the right side of the body, his motor function is very well preserved.

The results of the electrophysiological testshowed that there are no somatosensoryevoked potentials elicited by the electricalstimulation from paretic side of the ulnar nerve(A), but larger motor evoked potentials in thefirst dorsal interosseous (FDI) muscle elicitedby transcranial magnetic stimulation on themotor cortex (B). Comparable EMG level duringmaximal voluntary contraction was observed inFDI of both side (C).

Normal side Paretic side

A Somatosensory evoked potential

20msecStim

Stim

B Motor evoked potential

20msec

1mV

100msec

C Maximal voluntary contraction

References:Hodgson et al. Can the mammalian lumber spinal cord kean a motor task? Med Sci Sports Exerc 26: 1491-1497, 1994Kawato M et al. A hierarchical neural-network model for control and lerning of voluntary movement. Biol Cybern 57: 169-185, 1987.Lam T et al. Contribution of feedback and feedforward strategies to locomotor adaptations. J Neurophysiol 95: 766-773, 2006Rothwell JC et al. Manual motor performance in a deafferented man. Brain 105: 515-542, 1982Timoszyk WK et al. The rat lumbosacral spinal cord adapts to robotic loading applied during stance. J Neurophysiol 88: 3108-3117, 2002Wolpart D and Ghahremani Z Comptational principle of movement neuroscience. Nature Neurosci 3: 1212-1217, 2000

Some evidences for the involvement of an internal model in the control of gaitwere suggested (Hodgson et al. 1994, Timoszyk et al. 2002, Lam et al. 2006)

4. Discussion

H.O. can seemingly walk well, but it takes several tens of seconds afterthe beginning of walking until the subject's stride reaches a steady level.(Such adaptive changes were not observed in S.N.)

Because H.O. is six years post injury, his walking performance hasalready been well established. Therefore, H.O. could presumably planand accomplish the task of walking by using the internal model.

Such adaptive changes might reflect the process which compensates forthe lack of sensory feedback using the visual information.

Once H.O. stops walking and resumes walking after one minute of break,it takes much time again to reestablish stable walking.

Main Results and Discussion

The present results strongly suggest that successive sensory feedbackis an essential factor for updating the internal model of walking.

Does H.O. have internal model for walking?

H.O. cannot detect a mismatch betweenplanned and accomplished movementbecause of his loss of sensory feedback.

Compensatory process accomplished by the visual information can beused only temporally. This process significantly differs from updatingthe internal model in able bodied individuals.

"The difference between the predicted and actualsensory feedback can be used as an error signalto update a predictive model"

(Wolpert and Ghahramani 2000)

As a result, H.O. needs visually inducedcompensation for the sensory loss ineach walk initiation.

Proposed Model

MotionError

FeedbackController

ControlledObject

ActualMovement

PredictedMovement

FeedbackMotor

Command

MotorCommand

Inverse Model FeedforwardMotor

Command

MotionError

FeedbackController

ControlledObject

ActualMovement

PredictedMovement

FeedbackMotor

Command

MotorCommand

Inverse Model FeedforwardMotor

Command

(A) The general feedback-error-learning model

(B) H.O.'s case

Somatosensory Feedback

MotorCommand

Error

MotorCommand

Error

ormmm

Mmmmam

Visuo-motorCenter

ory Feedbosensotosensoory Feo

Somatosensory Feedback

Compensatory process accomplishedby the visual information cannot bepreserved as an internal model.

Visuo-motorcommand

4

Partners:




•Measurements- Measured Parameters: Oxygen Uptake (VO2 ), Telemetric breath respirationmesurement system (K4b2, Cosmed, Italy)- Calculated Parameter: Metabolic Equivalent (Index of exercise intensity):METs) (1MET = 3.5 ml/kg/m VO2 )- Stride length: Two-dimensional motion-analysis, the distance of the toe marker between two consecutive gate cycle (only participant A)

Methods•Participants: Two adults with incomplete SCI (participants A and B) and two able-bodied individuals (participants C and D) participated. The individuals with SCI completed 4 months of FES-assisted gait training prior to this study.

List of subjects

•Experimental Protocol- Walking Speed : 2.1km/h (participant A, C, D) and 2.5km/h (participant B) - Protocol

•FES System- Equipment: Compex Motion stimulators (Compex SA, Switzerland). Biphasic asymmetrical pulses (frequency 35Hz and pulse duration 0-300 s) were delivered to the body via eight self-adhesive gel electrodes. - Target Muscle: quadriceps, hamstrings, gastrocnemius /soleus and tibialisanterior- Pulse Amplitude: Participant A, B: 75% of the maximum FES induced contraction, Participant C, D: 20-25mA- FES Program: Feed-forward stimulation pattern triggered using two pushbuttons. For more details consult (Thrasher et al. 2005).


Oxygen Uptake during FES Treadmill Walking: Case StudyM. Miyatani1,2, N. Kawashima1,2, T.A. Thrasher3, M.Ranjan1,

K. Masani1,2 and M.R. Popovic1,2

Introduction•People with spinal cord injury (SCI) need to exercise on a regular basis to prevent secondary complications, such as cardiovascular diseases, osteoporosis and obesity. •To achieve the required fitness level is a challenging task for SCI patients because they have difficulty increasing their exercise intensity by on their own.•Functional electrical stimulation (FES) can restore movements by artificially contracting paralyzed or paretic muscles. Our previous study suggests that FES-assisted gait training has a positive effect on SCI patients (Thrasher et al. 2005). •It is likely that FES-assisted gait training can provide the required cardiopulmonary exercise in SCI patients by increasing their leg muscle activity and energy consumption. •However, to date, the physiological intensity of FES-assisted gait training has not been investigated.

PurposeTo examine the oxygen uptake and exercise intensity of FES-assisted gait training in patients with the motor-incomplete SCI.

1 Institute of Biomaterials and Biomedical Engineering, University of Toronto; 2 Lyndhurst Centre, Toronto Rehab; & 3 Health & Human Performance, University of Houston

Results and Discussion

Non-FESWalking

FESWalking

Non-FESWalking

1min

Rest

4min 4min 4min

Rest

1min

Oxygen consumption was increased in FES walking in all four participants. The intensities of FES walking in the SCI participants were 4.0 and 5.3 METs. Thus, FES walking can be used to increase the exercise intensity for individuals with SCI who in general have difficulty increasing their exercise intensity on their own.

Conclusion

Oxygen Uptake during Rest, Non-FES Walking and FES Walking

VO2 was increased during FES walking compared to the initial Non-FES walking, and then decreased again during the second Non-FES walking in all four participants. The VO2 increments in FES walking from the initial Non-FES walking were 9.0, 5.0, 10.6 and 20.8% in participant A, B, C and D respectively.

METs value of rest, Non-FES Walking and FES Walking

METs values increased in FES walking in all four participants. MET values in participants A and B during FES walking (4-5 METs) corresponded to the level of moderate walking, which is the recommended daily physical exercise intensity by American college of sports medicine.

Subject Age (years) Height (cm) Weight (kg) SCI level ASIA score Yearspostinjury

Participant A 45 175.0 77.0 C4 C 2

Participant B 39 173.0 58.0 T6 Notapplocable 9

Participant C 30 169.0 63.0 - - -

Participant D 39 174.0 75.7 - - - Subject Rest Non-FES Walking(1st ) FES Walking Non-FES Walking

(2nd) Rest

Participant A 1.0 3.7 4.0 3.7 2.5

Participant B 2.2 5.1 5.3 5.0 0.0

Participant C 1.7 3.1 3.5 2.7 1.5

Participant D 1.1 2.4 2.9 2.4 1.0

Stimulation program for a single leg. The stimulation begins from initial state representing late stance phase, and pushbutton triggers open-loop sequence beginning with swing phase (Thrasher et al. 2005).

2468

101214161820

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(1st )

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(2nd)

Rest

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A

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FES Walking 2nd Non-FESWalking

Strid

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(cm

)

P<0.05 P<0.05 Stride length during FES walking was significantly larger than that of 1st Non-FES walking. Stride length during 2nd Non-FES Walking was smaller than that of FES Walking, but there was no significant difference between two sessions. This preliminary result might suggest that the VO2 increment in FES walking is due to the increment of stride length.

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FREQUENCY RESPONSE OF STIMULATED KNEE MOVEMENTC. L. Lynch1,2, L. Mourra1 and M. R. Popovic1,2

What can the Bode plot tell us about electrical stimulation in SCI individuals?

Introduction

1Institute of Biomaterials & Biomedical Engineering, University of Toronto 2Toronto Rehabilitation Institute

Results

Discussion

References[1] Phillips CL & Harbor RD. Feedback Control Systems, 3rd edition. Prentice Hall, Upper Saddle River, NJ, USA. 1996.

• Functional electrical stimulation (FES) can be used to restore motor function to paralyzed muscles in individuals with spinal cord injuries (SCI). FES uses electricity to generate muscle contractions.

• New FES applications, such as balance while standing and torso control while sitting, require closed-loop control of stimulated muscle contractions.

• A system’s frequency response provides information about the system’sdynamics, and is useful when developing closed-loop control systems [1].

• We determined the frequency response of electrically stimulated knee movements in an individual with complete SCI:

• Input sinusoid – amplitude of stimulation delivered to muscle,

• Output sinusoid – resulting knee angle.

Hypotheses• The magnitude and phase responses will decrease with increasing fatigue

• The phase response will decrease with increasing frequency.

Methods

Figure 1 – Experimental Apparatus

• The magnitude and phase responses decreased with increasing fatigue.

• The phase response decreased with increasing frequency.

• Future work:

• Investigate the phase decrease at higher frequencies.

• Extend this study to multiple subjects, multiple sessions.

• Use results to describe system, then design closed-loop FES controller.

Knee Trajectory

Gonio-meter

Electrodes

Padded Bench

Figure 3 – Magnitude Response of Stimulated Knee Movements

Figure 2 – Phase Response of Stimulated Knee Movements• The quantities calculated for each trial: average phase shift, attenuation between stimulation waveform and knee angle.

• Figures 2 and 3 show the Bode plot of the stimulated knee movements.

• The quadriceps muscle was stimulated to contract (stim. frequency = 25 Hz, pulse width = 250 s), and resulting knee angle was recorded (see Fig. 1).

• The knee angle was made to follow a sinusoid by varying the stimulation amplitude sinusoidally between x and y mA:

• x – minimum amplitude at which knee began to extend,

• y – amplitude corresponding to maximum knee extension.

• Trials were conducted at different frequencies of stimulation sinusoid.

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Physicians' Services Incorporated Foundation

Methods3D Dynamic ModelThe 3D dynamic model, which represents the human body during double-support stance, is shown in Fig. 1 [Kim et al., 2006].

Rehabilitation Engineering Laboratory, Institute of Biomaterials and Biomedical Engineering, University of TorontoToronto Rehabilitation InstituteContact: [email protected]

Optimal Combination of Minimum Degrees of Freedom to be Actuated for the Facilitation of Arm-Free Paraplegic Standing

Joon-Young Kim1,2, Albert H. Vette2,3, and Milos R. Popovic2,3

1 Department of Mechanical and Industrial Engineering, University of Toronto2 Lyndhurst Centre, Toronto Rehabilitation Institute

3 Institute of Biomaterials and Biomedical Engineering, University of Toronto

Inverse Dynamics SolutionApplication of a computationally efficient inverse dynamics method [Nakamura et al., 1989]:

• driven by kinematic data from four healthy subjects;• torque estimation for eight perturbation directions (D1 to D8 in Fig. 1);• torque estimation for six combinations of six active DOF (Cases I to

VI in Fig. 2) as identified in [Kim et al., 2006].

Fig. 1: Dynamic model of quiet standing with twelve DOF and eight perturbation directions (D1 to D8).

Results and Discussion

Conclusions

BackgroundArm-free paraplegic standing by means of functional electrical stimulation (FES) has the potential to allow individuals with paraplegia to stand and at the same time use both arms to perform activities of daily living such as cooking and ironing. In this context, we have recently shown that only six of the existing twelve degrees of freedom (DOF) in the lower limbs need to be actuated to facilitate stable standing in the presence of external perturbations [Kim et al., 2006].

Introduction

After identifying the various combinations of six DOF that allow stability during perturbed arm-free standing, the purpose of the present study was to determine the optimal DOF combination, i.e., the combination that requires the minimum total torque to regulate balance.

• HAT: – Head-Arms-Trunk– rigid body with constant mass and moment of inertia

• Legs: – six DOF each– sufficient number of DOF for a reasonable approximation

of the double-support characteristics of human standing

Fig. 2: Six cases of six DOF that need to be actuated in order to facilitate stable standing when external perturbations are present.

Fig. 3: Torque sums of the joint torques (5 s) at all active DOF, shown for each of the six cases and all directions of perturbation (D1 to D8).

The torque sums for each case (Case I to VI) and each perturbation direction (D1 to D8) are shown in Fig. 3. The torque sums were calculated for a duration of 5 s after the perturbation.

• Cases V and VI (Fig. 2) exhibited the smallest torque sums (Fig. 3) for all subjects and perturbations.

• Due to the symmetry of the legs, this results in four combinations of six active DOF that are optimal with respect to the joint torque sums.

D1 D2 D3 D4 D5 D6 D7 D80

200

400

600

Torq

ue S

um (N

m*s

)

D1 D2 D3 D4 D5 D6 D7 D80

400

800

1200

D1 D2 D3 D4 D5 D6 D7 D80

500

1000

1500

Perturbation Direction

Torq

ue S

um (N

m*s

)

D1 D2 D3 D4 D5 D6 D7 D80

200

400

600

Perturbation Direction

Case I Case II Case III Case IV Case V Case VI

Subject S1

Subject S3

Subject S2

Subject S4

Hip rotation (l)

Hip ab-/adduction (r)Hip flexion/extension (l)

Ankle dorsi-/plantarflexion (l)Ankle in-/eversion (r)

Knee flexion/extension (r)

• Cases V and VI of six active DOF can achieve paraplegic arm-free standing while requiring minimum joint torques.

• The required joint torques can be generated by contemporary FES technology.

• FES-assisted arm-free standing is feasible even in the case where only six DOF in the lower limbs of a paraplegic can be actuated.

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Rehabilitation Engineering Laboratory, Institute of Biomaterials and Biomedical Engineering, University of TorontoToronto Rehabilitation InstituteContact: [email protected]

Motor Command of Proportional and Derivative (PD) Controller Can Match Ankle Torque Modulation during Quiet Stance

Albert H. Vette, Kei Masani, and Milos R. PopovicLyndhurst Centre, Toronto Rehab

Institute of Biomaterials and Biomedical Engineering, University of Toronto

The PD controller can not only regulate balance, but also mimic the sensory-motor control task during quiet stance. Future work will implement the PD control strategy as part of a closed-loop system to test the feasibility of developing a neuroprosthesis for standing.

Discussion and Conclusion• PD controller can match ankle torque modulation during quiet standing – even for a large sensory-motor time delay (> 180 ms).• Optimized PD gains agree with previous findings [Masani et al.,2006], and optimized twitch contraction time is physiologically valid.

Quiet Standing Experiments (12 healthy subjects)• Measurements:

– Ground reaction forces (Kistler force plate)– Body angle (Keyence laser sensor)

Fig. 3: Example of torque matching for eyes open condition (validation data for one subject).

Results

Fig. 4: Overall torque error (A) and matching percentage (B).

PD Controlled Feedback ModelThe modeled PD controller utilizes experimental body angle data to generate a motor command that is translated into ankle torque by a 2nd

order muscle model of the plantar flexors [Tani et al., 1996] (Fig. 2).


Fig. 2: Schematic diagram of the PD controlled feedback model.

Closed-Loop Time Delay to be Considered (Fig. 1A):– Feedback time delay (TauF = 40 ms)– Motor command time delay (TauM = 40 ms)– Torque generation delay (TauE > 100 ms)

= closed-loop time delay of more than 180 ms that needs to be compensated for by the neural PD controller

IntroductionBackground of StudyOur simulation studies have demonstrated that a proportional andderivative (PD) feedback controller can compensate for the sensory-motor time delay (Fig. 1A) and stabilize the body during uprightstance. The required phase advance is generated by a large derivative gain Kd (Fig. 1B), resulting in a physiological motor command that precedes body sway by 100 to 200 ms [Masani et al., 2006].

After verifying experimentally that the PD controller can regulate balance during quiet stance [Vette et al., 2007], the purpose of the present study was to investigate whether the modulation of the PD controlled ankle torque can match the experimentally identified ankle torque modulation during quiet standing.

Fig. 1: Sensory-motor time delay (A) and PD phase advance (B).

( ) ( ) ( )PD P DdM t K t K tdt

Kp Channel

MPD

Kd

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B

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Motortime delay

Torque generation delay

E

Muscle

> 180 ms

Hypothesis: Despite the closed-loop time delay, the PD controlled ankle torque modulation (model output) can match the experimental ankle torque modulation during quiet standing.

The authors acknowledge the support of the Toronto Rehabilitation Institute which receives funding under the Provincial Rehabilitation Research Program from the Ministry of Health and Long-Term Care in Ontario. The views expressed do not necessarily reflect those of the Ministry.

• Tasks:– Quiet standing with eyes open (2 60 s)– Quiet standing with eyes closed (2 60 s)

Optimization Procedure (DIRECT algorithm)• Optimized Parameters (gray boxes in Fig. 2):

– PD gains: Kp [Nm/rad] and Kd [Nm s/rad]– Twitch contraction time T of muscle model [ms]

• For each trial: 30 s of optimization & 30 s of validation• Analysis: Identification of error torque and matching percentage

0 10 20 3050

60

70 [Kp,Kd,T] = [746,250,73]

Experimental torquePD controlled torque

EO EC0

1

2

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A Model of Electrically Stimulated Knee Response for Use in FES Systems

•Functional electrical stimulation (FES) is a promising rehabilitation modality for individuals with spinal cord injuries (SCI) that involves electrically stimulating the neuromuscular system to generate skeletal muscle contractions. FES has been used for gait training [1] and grasp rehabilitation [2], among other applications. Currently, such systems require a significant amount of intervention by the user or the therapist.

•We are developing FES rehabilitation systems that work semi-autonomously, freeing the therapist and patient to concentrate on the rehabilitation, instead of concentrating on the technology. Such FES systems require closed-loop control, which is not currently available for clinical FES systems.

•One of the reasons that closed-loop control is not currently used in clinical FES systems is the lack of a model of the body’s response to electrical stimulation that captures the variability of the response.

•We propose a new stochastic model that will capture the day-to-day variation in the body’s response to stimulation.

Introduction

Fig 2 – Raw Data and Envelope of 100 Stochastic Best-Fit Models

References[1] TA Thrasher, HM Flett, & MR Popovic. Spinal Cord. 44(6):1-5. 2006.

[2] MR Popovic, TA Thrasher, ME Adams, V Takes, V Zivanovic, MI Tonack. Spinal Cord. 44(3):143-151. 2006.

[3] WH Press, BP Flannery, SA Teukolsky, WT Vetterling. Numerical Recipes in C, 2nd ed. Cambridge University Press, Cambridge, UK, 1999.

STOCHASTIC MODELING OF KNEE RESPONSEC. L. Lynch1,2 and M. R. Popovic1,2

1Institute of Biomaterials & Biomedical Engineering, University of Toronto 2Toronto Rehabilitation Institute

•We hypothesize that a nonlinear model with a stochastic term will capture the day-to-day variation in response to electrical stimulation that is seen in individuals with SCI.

Hypotheses

•We randomly stimulated the quadriceps and hamstrings of a seatedindividual with a complete SCI at T3, and recorded the resulting knee angle with an electrogoniometer.

•We collected data during 24 hour-long sessions over the course of 8 weeks. We processed the data to de-noise and normalize all trials to the same initial knee angle, and grouped the trials by stimulation level.

•For each set of quadriceps and hamstrings stimulation parameters, we found the best-fit stochastic model of the form

•The deterministic portion of the model was a linear combination of M nonlinear basis functions, gi(t), which were chosen to represent parts of typical response curves. The coefficients, ai, were found by using singular value decomposition and were chosen to minimize a Chi-square metric.

•The stochastic portion of the model, X(t), is a function whose value at each time point is a normally distributed random variable. The standard deviation of the random variable is the same as the standard deviation of the recorded knee responses at that time point, for a particular set of stimulation parameters.

Methods

•Fig 1 and 2 show the results of modeling the knee response to 86 mA quadriceps and 24 mA hamstrings stimulation. Fig 1 shows the mean of all trials at this stimulation level and the stochastic best-fit model. For this stimulation level, the best-fit model used 7 basis functions. Fig 2 shows the raw data as well as the envelope of 100 stochastic best-fit models.

Results

•The raw data and stochastic best-fit models show similar statistical properties, and the stochastic model encompasses the variation seen in the knee response.

•This stochastic modeling method captures the day-to-day variation in response to electrical stimulation that can be seen in individuals with spinal cord injuries. Such models will facilitate the development of a closed-loop system that is sufficiently robust to be used in real-world FES rehabilitation applications.

Conclusions

Fig 1 – Stochastic Best-Fit Model

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Muscle Recruitment Patterns in Perturbed SittingV. Sin1,2, K. Masani1,2, A. H. Vette1,2, T. A. Thrasher3, A. Morris2, N. Kawashima2,

B.C. Craven2, and M. R. Popovic1,2

• People with spinal cord injury (SCI) have trouble maintaining trunk stability during sitting

• Functional electrical stimulation (FES) applies bursts of short electric pulses to groups of muscles to generate functional muscle contractions

• FES could be used to increase trunk stability during sitting for people with SCI

• Information about which trunk muscles are essential during sitting, and how these muscles respond to external perturbations are needed to develop a practical neuroprosthesis for sitting

1Institute of Biomaterials and Biomedical Engineering, University of Toronto2Toronto Rehab, Lyndhurst Centre, 3University of Houston

• Directional dependencies could be seen for RA, EO, IO, T9 and L3 (Fig. A)• No directional dependencies found for SM and SC • EMG responses of RA, EO, IO, T9 and L3 were curve fitted using Gaussian (Fig. B):

Results

• The present study was the first to characterize the muscle responses mathematically to loads from different perturbation directions

• The direction and range of activation in which each muscle was maximally activated could be identified using these formula

• These formulas could be used in implementing a FES system for trunk muscles to stabilize sitting posture for people with SCI

This project was funded by CIHR

Conclusion

• Subjects: 12 healthy, right-handed male, age 21 to 39 years

• Protocol:• Surface electrodes were placed on trunk and neck muscles on both sides of the body to measure muscle activities (EMG)

• Subject sat on a custom seating apparatus, with the arms crossed in front of their chest, eyes-closed in a relaxed and natural position. Subject wore headphones and listened to asynchronous nature sounds. He also counted numbers aloud to prevent anticipation.

• 40 perturbation trials (8 directions, 5 trials each) were applied to the subject at chest level manually

Methods

• To determine the directional dependencies of trunk muscle responses, and the amount of muscle activities to perturbations applied from different directions during sitting of able-bodied subjects

Goals

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13

Partners:






Posturography Measures during Quiet Sitting

• Sitting balance is an important factor for the activity of daily life of individuals with SCI

• Previous studies have shown that the centre of pressure (COP) displacement recorded during quiet standing reflects the overallpostural control system

• Postural steadiness (posturography) is commonly used for balance assessment but has not been applied to the study of sitting balance

Introduction

Fig1 – (A) Experimental setup and (B) an example of COP time series (only 30 s of data presented) in a planar plot (left), and time series of AP (top) and ML (bottom)

Table 1: Stabilogram Diffusion Function Measures

References1. C. Maurer, R.J. Peterka, Journal of Neurophysiology 93 (2005)

189 - 200.2. T.E. Prieto, et al., IEEE Transactions on Biomedical Engineering

43 (1996) 956-966.3. J.J. Collins, C.J. de Luca, Experimental Brain Research 95

(1993) 308-318.

• Differences in time-domain measures, and frequency-domain measures between quiet sitting and quiet standing could be attributed to the differences in the size of the free moving part (i.e., the whole body versus trunk, arms and head)

• Quiet sitting utilizes open-loop and closed-loop postural control schemes similar to standing, but the exact control schemes are different between sitting and standing

Conclusions

• Thirteen healthy male individuals with no history of neurological disorders participated

•Age 21-39 years•Height 178.0 ± 4.7cm•Weight 70.3 ± 10.0kg

• Individuals were asked to sit quietly on a force plate for 140 seconds, as shown in Fig1

• The force plate data was used to calculate the net COP in the anterior-posterior (AP) and medio-lateral (ML) directions, and resultant distance (RD)

• Signals were collected using a 64-channel, 12-bit analog-to-digital converter at a sampling frequency of 2000Hz

Methods

1Institute of Biomaterials and Biomedical Engineering, University of Toronto2Toronto Rehab, Lyndhurst Centre, 3University of Houston,

4Japan Society for the Promotion of Science

V. Sin1,2, K. Masani1,2, A. H. Vette1,2, T. A. Thrasher3, N. Kawashima4,A. Morris2 and M. R. Popovic1,2

• The time-domain measure values during quiet sitting were smaller than the corresponding values during quiet standing (Fig2)

• Mean frequency was two to three times higher for quiet sitting as compared to quiet standing (Fig2)

• Stabilogram diffusion analyses measures (Table 1): Hurst exponent for the short-term and long-term intervals for sitting were larger and shorter, respectively, as compared to standing. The critical time interval was shorter during sitting as compared tostanding

Results

• Time-domain, frequency-domain and stabilogram diffusion analyses were applied to the COP time series as described in thestudy by Maurer et al. [1]

• Time-domain, frequency-domain results were compared to those described in the quiet standing study by Prieto et al. [2]

• Stabilogram diffusion analyses results were compared to those described in the quiet standing study by Collins and DeLuca [3]

Analysis

Quiet Sitting Quiet Standing [2] Ratio*

RD 0.45 ± 0.24 0.92 ± 0.29 0.49 AP 0.53 ± 0.36 0.97 ± 0.46 0.55

tc (s)

ML 0.49 ± 0.23 1.06 ± 0.42 0.47 RD 0.86 ± 0.03 0.76 ± 0.04 1.13 AP 0.86 ± 0.03 0.77 ± 0.04 1.12

HS

ML 0.89 ± 0.05 0.74 ± 0.05 1.20 RD 0.12 ± 0.14 0.34 ± 0.08 0.31 AP 0.10 ± 0.18 0.38 ± 0.10 0.28

HL

ML 0.20 ± 0.12 0.23 ± 0.05 0.89 *ratio = quiet sitting / quiet standing

Fig2 – Comparison of time-domain and frequency-domain measures

• To investigate how posturography during quiet sitting in healthy young male individuals differs from that of quiet standing

• To provide a benchmark for evaluating balance capacity during quiet sitting within different patient populations

Purpose of study

14

Partners:





Identifying Movements From Cortical Signals

Electrocorticographic Signals Reflect Specific Motor Tasks

• The consistency of the distributions of correlated spectral components suggest that it might be possible to use it as features to automatically classify ECoG signals.

Discussion

Table 1. Participants of this study.

Female / 65

Male / 73

Age / Gender

•Closing Hand (CH)•Reaching to the Right (RTR)•Reaching to the Left (RTL)

•Elbow Flexion (EF)•Reaching to the Right (RTR)•Reaching to the Left (RTL)

Performed Movements

ET

PD

Diagnosis

2

1

Subject

Background• Different frequency bands in the electrical activity of the

brain experience changes in amplitude during voluntary movement and/or preparation to perform such movement.

• These changes have been used to identify the occurrence of specific movements.

• The electrical activity of the brain can be recorded with intracranial electrodes (subdural electrodes) placed on the surface of the brain.

• The signals recorded with these electrodes are referred to as ECoG signals.

Participants• Two individuals were implanted with subdural electrodes (four

contacts) for the treatment of movement disorders: Parkinson’s disease (PD) and Essential Tremor (ET). (See Fig. 1 and Table I)

• The site of implantation corresponded to the arm area of the primary motor cortex, confirmed with electrical stimulation.


Experimental Procedure• Participants performed specific movements (see Table I).• ECoG signals and position (X, Y, Z coordinates) of the hand were

recorded simultaneously.

Analysis• ECoG signals were analyzed in different configurations including

monopolar as well as the difference between adjacent and non-adjacent electrodes.

• The time-frequency distribution was estimated for each ECoG signal with a resolution of 1.5 Hz

• The spectral components with the highest correlation values witheach one of the kinematic dimensions were identified for each movement

• These frequency components were then grouped in a histogram• The magnitude of each column represents the probability that a

specific frequency band is correlated with a kinematic dimensionof each movement.

• To create a system that uses the electrical activity of the brain to control electronic devices: a brain-computer interface.

Long –Term Goal

• The consistency of the distributions of correlated spectral components suggest that these features might be used to classifyECoG signals automatically.

Results

Figure 2. Average distribution of ECoG spectral components correlated with movement.

Figure 1. Subdural electrodes used for this study.• Explore the changes elicited by specific movements in the

electrical activity of the primary motor cortex.• Identify features in the electrocorticographic (ECoG) signals that

show consistent behaviour in relationship to movement.

Purpose of the Study

César Márquez Chin and Milos R. PopovicInstitute of Biomaterials and Biomedical Engineering, University of Toronto

Toronto Rehabilitation Institute

15

Partners:




Fig. 1: Measurement setup for peripheral nerve source localization


Localizing Active Pathways in Peripheral Nerves

• Localizing active pathways in peripheral nerves would help us tomonitor control signals flowing between the central nervous system and a limb or an organ, and ultimately to control a neural prosthesis.

• Using a multi-contact nerve cuff electrode and solving a source localization inverse problem (similar to EEG source localization), we hope to observe information flow through a peripheral nerve.

• We tested the proposed methods on simulated measurements.

Introduction

[1] Pascual-Marqui, Meth. Find. Exp. Clin. Pharmacol., vol. 24 Suppl D, pp. 5–12, 2002

[2] Sweeney et al, Proc Ninth Ann Int Conf IEEE Eng Med BiolSoc, pp. 1577–1578, 1987.

v: measurements L:leadfield j: sources : noise

Methods• The relationship between the measurements and bioelectric sources

in the nerve can be expressed as a linear system.

• L is computed using a finite-element model of a rat sciatic nerve.

• We want to recover j from v, knowing L, but there are more unknown variables than measurements, resulting in an underdetermined problem. Many algorithms exist for this sort ofsituation, and rely on imposing constraints on the solution.

• We chose to use the sLORETA [1] algorithm, which was originally developed for localizing bioelectric sources in the brain. It uses a smoothness constraint, resulting in a blurred solution with well-localized peaks.

• Our choice of algorithm is based on three criteria:1. No assumption about the number of sources2. No assumption about stationarity3. Speed

Test Cases• Action potentials propagating through the nerve were simulated

using the Sweeney model for ion channel dynamics in myelinatedmammalian nerve fibers [2]. The corresponding measurements were computed using Equation 1, for a 2.5ms time interval.

• First case: one active pathway at a random cross-sectional position (100 trials).

• Second case: three simultaneous active pathways at random cross-sectional positions and with small random time shifts (100 trials).

v = Lj + Eq1:

Results

Fig. 1: Measurement setup schematic for peripheral nerve source localization

J. Zariffa and M.R. PopovicInstitute of Biomaterials and Biomedical Engineering , University of Toronto

Electrical and Computer Engineering, University of Toronto Toronto Rehabilitation Institute, Canada

Fig. 3: Simulation results in terms of pathway localization error, missed pathways, and spurious pathways.

Conclusions

References

Fig. 2: Localization example for a single-pathway trial

-0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

x (mm)

Estimated source distribution (time-averaged and projected onto 2D)

y (m

m)

True source location

-5 0 5 10 15 20 250

0.05

0.1

0.15

0.2

Noise Level (%)

Loca

lizat

ion

erro

r (m

m)

Average Localization Error, 1-Pathway Case

-5 0 5 10 15 20 250

0.05

0.1

0.15

0.2

0.25

Noise Level (%)

Loca

lizat

ion

erro

r (m

m)

Average Localization Error, 3-Pathway Case

-5 0 5 10 15 20 25-1

-0.5

0

0.5

1

Noise Level (%)

Mis

sed

path

way

s

Average Missed Pathways, 1-Pathway Case

-5 0 5 10 15 20 250.5

1

1.5

2

2.5

Noise Level (%)

Mis

sed

path

way

s

Average Missed Pathways, 3-Pathway Case

-5 0 5 10 15 20 25-1

0

1

2

3

4

Noise Level (%)

Spu

rious

pat

hway

s

Average Spurious Pathways, 1-Pathway Case

-5 0 5 10 15 20 25-0.5

0

0.5

1

1.5

2

2.5

Noise Level (%)

Spu

rious

pat

hway

s

Average Spurious Pathways, 3-Pathway Case

• Localization can be achieved within tolerable error in the one-pathway case, although the solution is blurred. The blurring isinherent to the sLORETA algorithm and therefore to be expected.

• The limited resolution is the biggest challenge to the localization of several pathways, because pathways close to each other cannotbe adequately separated. Alternative algorithms should be explored to address this issue.

• The other issue to be addressed is the high number of spurious pathways at high noise levels.


16

Partners:





Implementation


Control of Multiple Degree-of-Freedom Tasks Using One-Dimensional Electroencephalographic Signals

Egor Sanin 1,2, César Márquez Chin 1,2, Jorge Silva 2, Tom Chau 2,3, Alex Mihailidis 2,4, and Milos R. Popovic 1,2.

1 Toronto Rehabilitation Institute, Toronto, Canada. 2 University of Toronto, Toronto, Canada. 3 Bloorview Kids Rehab, Toronto, Canada. 4 Intelligent Assistive Technology and Systems

Laboratory, Toronto, Canada.

Results

Conclusion• We developed and implemented a brain-machine interface which allows a single EEG channel to be used for real-timetwo-dimensional navigation, an example of a multiple degree-of-freedom task.

What is a Brain-Machine Interface (BMI)?

EEG

ComputerBrain

SignalProcessing

Binary Signal Single-Switch Asynchronous

Control Strategy Real-time 2-D navigation

Proposed Solution

Limitations

Single-Switch AsynchronousControl Strategy

0360Randomly selected

by algorithmDesired direction

0 360n

0 360n + 1

0 3600

0 360n + 2

Signal ProcessingBand-pass

filter:8-13 Hz

Moving Average <T

T = Threshold

True

False

System realized in software to navigate a cursor towards a target. System realized in hardware to drive a remote-controlled car.

Raw EEG signals are processed to realize a voluntary binary switch.

EEG binary switch used to drive an asynchronous control algorithm which

iteratively converges on the desired outcome.

BackgroundBinary Switch

17

THE

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it us

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CI t

echn

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the

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e in

tend

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Met

hod

Subj

ects

•67

year

old

wom

an•Im

plan

ted

with

a q

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al e

lect

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to tr

eat e

ssen

tial

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or•P

erfo

rmed

spe

cific

arm

mov

emen

ts:

wris

t fle

xion

(WF)

, rea

chin

g to

the

right

(RTR

), an

d re

achi

ng to

the

left

(RTL

).

Sub

ject

1

Sub

ject

2

•35

year

old

man

•Mot

or c

ompl

ete

cerv

ical

spi

nal

cord

inju

ry (C

6 le

vel/

AS

IA B

) •R

ecei

ved

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eeks

of F

ES

th

erap

y•F

itted

with

a n

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r gr

aspi

ng

Impl

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tatio

n D

etai

ls

•Tim

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solv

ed E

CoG

spe

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l co

mpo

nent

s co

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ted

with

eac

h m

ovem

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re g

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sing

hi

stog

ram

s w

ith b

ins

repr

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ting

frequ

ency

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ds o

f 10

Hz.

•The

his

togr

ams

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e us

ed a

s fe

atur

es

for c

lass

ifica

tion

of E

CoG

sig

nals

[1].

ECoG

Con

trol

led

Neu

ropr

osth

esis

for G

rasp

ing

Sub

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2 p

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ed o

ne o

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utto

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. Th

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-Chi

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r. Tr

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Cam

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2 , D

r. A

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Dr.

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Inst

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onto

, Can

ada

Part

ners

:

Can

adia

n In

stitu

tes

of H

ealth

Res

earc

hIn

stitu

tsde

rec

here

en s

anté

du C

anad

a

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ural

Sci

ence

s an

d En

gine

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esea

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of C

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onse

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not n

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flect

thos

e of

any

of

the

gran

ting

agen

cies

.

18

Partners:





Fig. 1: The matrix and single-ring contact configurations. Dark contacts are the ones whose data is available in the classification process.

• We use the recordings from the cuff electrode on the sciatic nerve to determine which nerve branch was stimulated in a given trial (i.e. classify the activity).

• Our goal is to compare the classification performance of two contact configurations: the full matrix configuration vs. only the 8 contacts in the middle ring of the cuff (this second configuration is taken from the neuroprostheses literature). The two configurations are shown in Figure 1. In both cases a tripole reference is used (average of the contacts with a black outline).

• Classification is performed by building a feature vector for each trial, consisting of the peak amplitudes of every contact in the configuration being used. A training set is used to obtain a typical feature vector for each nerve branch. Each feature vector in the testing set is assigned to the nerve branch whose feature vector it most resembles. The classification accuracy is the percentage of trials in the testing set that are correctly classified.

Classification of the Neural Activity


Influence of the Number and Location of Recording Contacts on the Selectivity of a Nerve Cuff Electrode

J. Zariffa1,2,3, M.K. Nagai1,3, Z.J. Daskalakis4 and M.R. Popovic1,2,3

• Nerve cuff electrodes are used to record the electrical activity of peripheral nerves, but have difficulty discriminating between different nerve branches.

• Manufacturing advances have increased the number of recording contacts that can be placed on a nerve cuff.

• We investigate how a nerve cuff with 56 contacts (7 rings of 8 contacts each) can improve selectivity.

Introduction

Experimental Methods• Experiments were performed on six rats (old male Long-Evans breeders).• The 56-contact (“matrix” configuration) recording cuff was placed on the

sciatic nerve.• 3 stimulating nerve cuffs were placed on the tibial, peroneal, and sural

branches of the sciatic.• Short pulses were used to stimulate each nerve branch in turn (100 trials

per branch).

1. Institute of Biomaterials and Biomedical Engineering, University of Toronto2. Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto3. Toronto Rehabilitation Institute4. Schizophrenia Program, Department of Psychiatry, Centre for Addiction and Mental Health

Results• The matrix configuration resulted in statistically significant

improvements in classification accuracy in all rats.

• By adding one contact at a time to the matrix configuration, from the most informative to the least informative, and evaluating the classification accuracy at each step, we found that high accuracies could be achieved with a small number of contacts.

Rat 1 Rat 2 Rat 3 Rat 4 Rat 5 Rat 60

10

20

30

40

50

60

70

80

90

100

110Maximum Classification Accuracies of Matrix vs. Single-Ring Configurations

Cla

ssifi

catio

n A

ccur

acy

(%)

MatrixSingle-ring

*

*

*

*

*

*

Fig. 2: Comparison of the maximum classification accuracies obtained with each contact configuration, for each rat.

Fig. 3: Classification accuracy as a function of the number of contacts used in the matrix configuration. Markers denote the maximum accuracy achieved (x) and the point at which the performance surpasses the maximum accuracy of the single-ring configuration (o).

0 10 20 30 40 50 6030

40

50

60

70

80

90

100

Classification Accuracy as a Function of the Number of Contacts Added

Number of Contacts

Cla

ssifi

catio

n A

ccur

acy

(%)

Rat 1Rat 2Rat 3Rat 4Rat 5Rat 6

Conclusions• The recordings from the matrix cuff led to better classification

accuracy than previously used configurations.• The improvement was due to the possibility of selecting the most

informative contacts, rather than to the sheer number of contacts.• These results have implications for the design of future cuff

electrodes.

19

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The Relationship Between Arterial Stiffness and Body Composition in Persons With Spinal Cord Injury

M. Miyatani1, 2, A. Khan2, P.I. Oh3, K. Masani1,2, M.R. Popovic1, 2 and B.C. Craven2,41 Institute of Biomaterials and Biomedical Engineering, University of Toronto; 2 Lyndhurst Centre, Toronto Rehab; 3 Cardiac Rehab Program, Toronto Rehab; and 4Department of

Medicine Toronto Rehabilitation Institute, University of Toronto

Background and PurposeWhy do we focus on Arterial Stiffness?• Stiffening in the cardiothoracic arteries is an emerging risk factor for coronary artery disease (CAD). Decreases in the elastic properties of arteries reduces the buffering capacity of the arteries, leading to increased pulse pressure, aortic impedance, and left ventricular wall tension, all of which increase CAD risk. What is Pulse Wave Velocity (PWV)? • PWV is the speed of the blood flow wave traveling through the arterial system. PWV is affected by the elasticity and distensibility of the artery. Higher velocity corresponds to higher arterial stiffness and lower distensibility.• Aging, obesity, poor cardiopulmonary fitness, low physical activity are associated with above normal PWV values.Why do we need to know about PWV in SCI patients? • Obesity is a common problem among individuals with spinal cord injury (SCI). Thus, it is hypothesized that individuals with SCI have high risk of CAD associated with above normal PWV values.What are aims of the project? • To test the hypothesis that SCI subjects have greater arterial stiffness (PWV) than age-gender matched non-SCI subjects. • To investigate the association between adiposity and PWV in these subjects.

MethodsSubjects (n=18)

• SCI men (n=9) without CAD(Age: 51 11 yrs; Height: 179 6.6cm; Body weight: 90.5 22.5 kg; neurologic level : between C3 to L3; ASIA impairment scale A; Years postinjury: 25 10.7years) and n=19 age and gender matched Non-SCI controls (Age: 45 10 yrs; Height: 175.1 7.9 cm; Body weight: 75.6 10.9 kg) Body composition Measurements

• Adiposity (Trunk fat mass, total body fat mass) were assessed using Dual-energy X-ray absorptiometry (DXA)

•Waist circumference was measured in supine position.PWV Measurement

• Pulse wave at two vascular landmarks were simultaneously measured using two identical non-invasive transcutaneous doppler flow meters (Smartdop50, Hadeco,Inc., Kanagawa, Japan)

• The pulse wave latency (PWL) (1) between the carotid artery(CA)and the femoral artery (FA); and (2) between FA and posterior tibial artery (PTA) were recorded (see diagram).

• The distances (D) in centimeters traveled by the pulse wave were measured over the surface of the body using a metal tape measure.

• Calculation of PVW(1) Aortic PWV (cm/sec)=

D Aortic / PWL between CA and FA(2) Leg PWV (cm/sec) =

D Leg / PWL between FA and PTA

ResultsPWV in SCI and Control

Aortic PWV in SCI were significantly higher than that of control(*One outlier in CON was excluded).There were no significant difference between SCI and control in leg PWV.

Relationship between Aortic PWV and adiposity in SCI and Control

Discussion and ConclusionThe higher trunk PWV in subjects with SCI than able-body population suggests their higher risk of CAD and potential need for aggressive risk factor

modification. The correlation results imply that obesity is associated with stiff arteries in the SCI population and thus body composition, in particular adiposity, should be assessed in clinical practice and may be used to detect patients with SCI with stiff arteries.

There were significant correlations between adiposity and aorticPWV and in SCI subjects (*One outlier in CON was excluded).

CA

FA

D Leg (cm)

D Aortic (cm)

PTA

FA

PTA

(ms)

PWL

0 100 200

Diagram of PWV measurement sites

The pulse wave latency (PWL)

AORTA

0

500

1000

1500

2000

SCI CON

PWV

(cm

/s)

P<0.05

LEG

0200400600800

100012001400

SCI CON

PWV

(cm

/s)

y = 25.903x + 903.47r=0.689 (p<0.05)

600800

100012001400160018002000

0 10 20 30Trunk fat mass (kg)

y = 17.547x + 802.03r=0.770 (p<0.05)

600800

100012001400160018002000

0 20 40 60Total body fat mass (kg)

SCICON

20

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Physicians' Services Incorporated FoundationMinistry of Healthand Long Term CareMinistry of Healthand Long Term Care

A Test-of-Principle Prototype for a New Device to Measurea Specific Pain Mechanism

References:1. Craig, A. D. New and old thoughts on the mechanisms. Yezierski, R. P. and Burchiel, K. J. Progress in Pain Research and Management. (23), 237-261. 2002. Seattle, IASP Press.2. Craig, A. D. & Bushnell, M. C. The thermal grill illusion: unmasking the burn of cold pain. Science 265, 252-255 (1994).3. Finnerup, N. B., et al. Sensory function in spinal cord injury patients with and without central pain. Brain 126, 57-70 (2003).4. Defrin, R., et al. Quantitative somatosensory testing of warm and heat-pain thresholds: the effect of body region and testing method. Clin. J. Pain 22, 130-136 (2006).5. Greenspan, J. D., et al. Body site variation of cool perception thresholds, with observations on paradoxical heat. Somatosens. Mot. Res. 10, 467-474 (1993).

Translating Pain Neuroscience Theory into a Clinical/Research Tool

Thermal Grill (TG) Apparatus

.

J.P. Hunter , E. Sanin , J. Juandi , A. Bulsen , M.R. Popovic1,3 1,2,11,4 2

1. Toronto Rehab, Lyndhurst Centre, 2. Institute of Biomaterials and Biomedical Engineering,3. Department of Mechanical Engineering, 4. Department of Physical Therapy, University of Toronto

Our overall goal is to develop a new TG for multiple-body-site testing and develop an open platform for investigators and clinicians in thefield as a psychophysical measure of alterations in cold inhibition of pain. Our plan for the current study was to evaluate the principles-of-design for new more portable and flexible TG apparatus

1. Lightweight and portable system2. Safe for use with patients3. Six contact thermodes with:

- individual & independent temperature control- adjustable spacing between thermodes

4. Physical capacity to:- heat or cool each thermode in range 0°C to 50°C- maintain each thermode at a stable temperature of 20°C or 40°C- achieve dynamic temperature ramp of 1.0°C/s

5. Individual continuous data logging of thermode temperature6. Response system to record continuous subject response


www.toronto-fes.ca

Background

Purpose

Design Needs

Design Prototype

Future DirectionsWe plan to build the REL-TG with 64 contact-thermodes ( 8 x 8 matrix, Fig. 7).

Our TG design based on the use of Peltier elements, an air coolingsystem, and electronic response system has the level of control andsystem flexibility required for future clinical, large scale studies to identifythe existence of a pain producing mechanism among individuals withCNP.

Based on prototype performance the following revisions are needed forthe planned larger "Rehab Engineering Lab Thermal Grill" (REL- TG):

1. Separate PC screen for patient.2. Improve system thermal dynamics by: revising the software, adding

variable power supply;and optomzing the thermode unit .3. Improve software usability by preprogramming for specific protocols.

Central neuropathic pain (CNP) is a devastating, unrelenting pain thatcan occur after a disease or injury to the central nervous system such asstroke, multiple sclerosis, or spinal cord injury (SCI) .

1

Prior research has shown that the thermal grill illusion (TGI) can be used toevaluate cold inhibition of pain .

One such mechanism is “thermosensory disinhibition”, or, the loss of cold-inhibition of pain within the central nervous system .

3

4,5

A TG allows the simultaneous application, to the skin, of spatiallyinterlaced nonpainful warm (40°C) and cool (20°C) bars, causing theindividual to experience a painful thermal percept, or TGI .

1. Lightweight and portable system2. Safe fof r use with patients3. Six contact thermodes with:

- individual & independent temperature control- adjustable spacing between thermodes

4. Physical capacity to:- heat or cool each thermode in range 0°C to 50°C- maintain each thermode at a stable temperature of 20°C or 40°C- achieve dynamic temperature ramp of 1.0°C/s

5. Individual continuous data logging of thermode temperature6. Response system to record continuous subjb ect response

gg

There is no commercially available TG.

Translation of the TGI response, to a tool to evaluateindividuals with SCI-related CNP requires a new TG,appropriate to evaluate the TGI in many anatomic regions .

The TGI has only been tested on the hand of able-bodiedindividuals; but CNP can occur in any body location .

Design will allow a range of complex stimulisimlar to those shown in Fig. 6.

Figure 4. Teemperature recordings from individual thermodes

Figure 6. Examples of warm (red) and cool (blue) thermal elements in REL-TG Figure 7. Proposed REL-TG with 8x8pattern of thermal elements

Contact (aluminum bar)

Aluminum Heat Sink

+ -DC Power Source

Peltierelement

1. Individual Thermode Design

Figure 2. Single Thermode of TG

Contact dimensions: 6mm x 13mm x 220 mmHeat sink: Surface area: 1276.6 mm

Thermal resistance < 3°C / WattPeltier element dimension: 13mm x 13mm

Maximum heat pumped: 9.2 WattsPower supply: Allows 13 Watts / Peltier element

2. Apparatus Design

Figure 3. Test-of-principle prototype

Continuously adjustable spacing: 1 - 20mmHeat sinkl: Air forced by four 2.5 Watt fans

(12 V x 210mA)MDF housing: Volume < 4.4 L; Weight < 2 Kg

3. Data Logging

Surface temperature continuously monitoredby 100Ohm RTD temperature sensor.

Sensor is coupled to a Data Acquisition System(DAQ) that is connected to the computerthrough a USB connection.

Temperature is displayed in LabView.

Time (sec)0 50 100 150 200

VAS

scor

e

0

20

40

60

80

100 Dynamic - GlaDynamic - HaiStatic - GlabroStatic - Hairy

4. Response System

Figure 5. VAS response ratings for TGI intensity in one subject

Continuous VAS for sensation magnitudeintegrated with device controls anddata logging in Labview

A roadblock to effective CNP treatment is the inability to identify, within anindividual, the specific neurobiological “mechanism(s)” responsible for the pain .

2

Conclusions

2

Bars 1, 3, and 5

0 50 100 150 200 250 30015

20

25Bar 1Bar 3Bar 5

Bars 2, 4, and 6

Time (sec)0 50 100 150 200 250 300

20

25

30

35

40

45

Bar 2Bar 4Bar 6

Tem

pera

ture

°CTe

mpe

ratu

re°C

Figure 1. TG used by Craig1,2

21

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Cardiovascular Response to FES and Passive Stepping to Improve Orthostatic Tolerance

L Chi1,2, K Masani1 ,2, M Miyatani1 ,2, KW Johnston1, A Mardimae1,3, C Kessler1,3,JA Fisher1,3, MR Popovic1,2

1. University of Toronto; 2. Toronto Rehab;3. Toronto General Research Institute

• Orthostatic hypotension, a sudden drop in blood pressure, is prevalent following spinal cord injury. Over 70% of SCIpatients experience sudden symptoms of dizziness,lightheadedness, and syncope upon postural change orfollowing periods of prolonged sitting resulting from venous pooling.

• Orthostatic hypotension hinders the patient’s participation in rehabilitation activities which is necessary to promote neuronalplacidity, prevent loss of muscle mass, mitigate osteoporosis,and maximize cardiovascular conditioning.

• Functional electrical stimulation (FES) and passive steppingmovements have been shown to increase blood pressure and reduce venous pooling and thus have been proposed as potentialtherapies to counter the effects of orthostatic hypotension.

Background• One subject experienced syncope during head-up tilt.• No subjects experienced syncope during FES, Stepping or the

combined modality.• FES synchronized with passive stepping significantly increased

venous return over 15 minutes of tilt.• FES significantly increased heart rate over 15 minutes of tilt.• Blood pressure did not change significantly over 15 minutes of

tilting

Results

Fig 1. Doppler ultrasound imaging of a subject’s inferior vena cavaduring (a) Tilt Condition and (b) FES w Stepping.

a b

IVC IVC

• Can lower limb movements, either though active leg musclecontraction (FES) or passive leg walking (Stepping), be effective in preventing orthostatic hypotension in able bodiedsubjects undergoing tilt?

Research Question

• Orthostatic hypotension conditions were simulated in 10 able bodied subjects. Subjects were secured on a tilt table and theirthighs were attached to robotic actuators which allowed passivestepping movements. All trials began with a 10 minutes restphase in the supine position. During the test subjects experience70° head-up tilt for 15 minutes or until syncope occurs.

• Four tilting conditions were performed in random order• Head Up Tilt (HUT)• HUT + FES• HUT + Passive Stepping• HUT + FES + Passive Stepping

• Electrical stimulation was applied to the gastrocnemius,quadriceps muscle group, and hamstring muscle group.

• Cardiovascular data (blood pressure, heart rate, venous return,cardiac output) were collected throughout the testing condition

• Data was analyzed using Student’s t-Test to determine thesignificance between various tilting conditions.

Method

Fig 2. Cardiovascular data from a subject undergoing tilt in varyingconditions. FES & Stepping were found to be effective in increasing venous return and heart rate over 15 minutes of tilt.

• The combination of FES with passive leg movements significantlyincreases venous return, thereby mitigates the effects of orthostatichypotension over the long term.

• Active muscle contraction by FES are effective in increasing theheart rate over the duration of tilting.

Conclusion


22

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Wave ® vs. Juvent ®: Whole-Body Vibration AssessmentFeasibility & Usability for Patients with SCI

BC Craven1,2, LM Giangregorio3, A Morris4, MR Popovic1,2, M Miyatani1

L You2, MI Tonack1, M Alizadeh-Meghrazi1,2, J Totosy De Zepetenek1,3

•Sublesional Osteoporosis (SO) is the decline of bone mineral density (BMD) in the hip and knee regions after SCI.

•25-45% of SCI patients experience fragility fractures as a result of SO.•Lower extremity fragility fractures result in decreased mobility, delayed healing, and in extreme cases amputation.•Current treatments for SO which include oral biphosphonates, and rehabilitation interventions (passive standing, tilt table, walking, muscular and functional electrical stimulation) have been largely ineffective in producing a significant or sustainedincrease in BMD.•Whole-Body Vibration (WBV) is a new therapy used for improving muscular strength and BMD in animals, post-menopausal women, and children with neurological impairments.

Background

1Toronto Rehabilitation Institute2University of Toronto

3University of Waterloo4Sunnybrook Health Sciences Centre

•To compare the feasibility and usability of two vibration platforms Wave® and Juvent® for treatment of SO among patients with chronic SCI.

Objective

: Accelerometer Locations

Standing Frame

Vibration Platform

•Subjects: Healthy male volunteers 20-40 years old (n=4) and age matched traumatic SCI patients with motor complete paraplegia (n=4).

•Vibration parameters: Frequency 30-50 Hz, and amplitude <5 mm.

•Feasibility criteria: Vibration Propagation through the body measured with 4 accelerometers located at the plate, lateral femoral condyle, iliac crest, and head ( see diagram below).

•Usability criteria: Vibration perception, subject reactions (adverse effect/perceived benefits), skinbreakdown, device accessibility, H-reflex, &lower extremity EMG.

Methods

•To identify which vibration parameters (freq. and amp.) result in the best/ideal propagation of vibration through the lower extremities in able bodied subjects and subjects with SCI.•To attain a better understanding of the neurophysiological effects of WBV therapy on H-reflexes and.muscle activation for subjects with and without SCI •To asses changes in the bone microstructure in response to vibration exposure through measurement of biochemical markers of bone turnover (osteocalcin and N-telopeptide).

Expected Results

•Acceleration propagation up the lower extremities is essential prior to determining what effects WBV has on the lower extremity bone microstructure.•H-reflex will be used as indicator of spinal motor neuron excitability. A relationship between hyperexcitability of the spinal motor neurons in SCI patients and spasticity exists, such that reductions in H-reflex may inhibit spasticity of the soleus.•Electromyography (EMG) will allow us to monitor lower extremity muscle activity pre, during and post vibration exposure. Increased EMG activity during vibration may be an indicator of muscle fiber activation.

Diagram of Accelerometer Locations

23

A N

EW IN

TRA

MU

SCU

LAR

ELE

CTR

OD

E FO

R

FUN

CTI

ON

AL

ELEC

TRIC

AL

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ULA

TIO

N IN

TH

E R

AT

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y K

Nag

ai, M

D, P

hD; A

bdul

kadi

r Bul

sen,

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bdol

azim

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, BS

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ilos

R. P

opov

ic, P

hD,

RE

L, T

oron

to R

ehab

ilitat

ion

Inst

itute

, Tor

onto

, ON

and

Uni

vers

ity o

f Tor

onto

, Tor

onto

ON

Impl

ante

d El

ectro

de:

•S

terra

dst

eriliz

ed•

The

elec

trode

is

im

plan

ted

in

the

prox

imal

qua

dric

eps

mus

cle

•Th

e vi

cryl

sut

ure

prev

ents

the

elec

trode

fro

m b

ecom

ing

disp

lace

d in

the

mus

cle

•A

kno

t in

the

wire

itse

lf at

the

dist

al e

nd

of t

he e

lect

rode

pre

vent

s it

from

bei

ng

pulle

d th

roug

h in

the

oppo

site

dire

ctio

n

Key

Feat

ures

of t

he In

tern

al C

ompo

nent

:

•A

slip

kno

t is

used

to a

ttach

the

elec

trode

to

a Ke

ith n

eedl

e fo

r:-

Eas

y pa

ssag

e fro

m t

he s

capu

la t

o th

e lo

wer

ext

rem

ity-

Eas

y im

plan

tatio

n of

the

ele

ctro

de i

nto

the

mus

cle

-D

esig

n al

low

s fo

r va

riabl

e le

ngth

s of

el

ectro

de-

Can

be

us

ed

for

FES

and

for

EMG

st

udie

s

Key

Feat

ures

of t

he E

xter

nal C

ompo

nent

:(T

he B

UTT

ON

)

•Th

e m

esh

allo

ws

for

easy

sta

biliz

atio

n in

the

subc

utan

eous

tiss

ues

•Li

ght w

eigh

t •

A v

aria

ble

num

ber o

f mus

cles

can

be

stud

ied

at a

ny g

iven

tim

e (p

hoto

sho

ws

an 8

pin

co

nnec

tor)

•In

divi

dual

or

gr

oups

of

m

uscl

es

can

be

stim

ulat

ed u

sing

FES

and

EM

G s

tudi

es c

an

be p

erfo

rmed

sim

ulta

neou

sly

•Th

e po

lypr

opyl

ene

tube

atta

ched

to th

e m

esh

prov

ides

ad

ded

prot

ectio

n fo

r th

e fin

e el

ectro

de w

ires

as th

ey a

re p

asse

d up

to th

e ex

tern

al c

onne

ctor

(8 p

in in

thes

e ph

otos

)

•Th

e Bu

tton

with

th

e ex

tern

al

conn

ecto

r pr

otru

des

2 cm

abo

ve th

e su

rface

of t

he s

kin,

al

low

ing

for

easy

con

nect

ion

to th

e FE

S a

nd

EMG

equ

ipm

ent

BA

RE

D W

IRE

Post

-op

Day

1:

•The

rat

sus

tain

ed a

n m

oder

ate

inco

mpl

ete

spin

al

cord

in

jury

us

ing

the

dist

ract

ion

spin

al c

ord

inju

ry m

odel

(D

abne

yet

al,

2004

)

•The

But

ton

was

im

plan

ted

betw

een

the

scap

ula

and

the

wire

s br

ough

t dow

n to

the

quad

ricep

s m

uscl

e an

d th

e ha

mst

ring

mus

cle

and

impl

ante

d in

the

res

pect

ive

mus

cle.

•The

But

ton

was

eas

ily c

onne

cted

to

the

Com

pex

Mot

ion

FES

syst

em

•The

qu

adric

eps

mus

cle

and

ham

strin

g m

uscl

es

wer

e st

imul

ated

us

ing

the

Com

pex

Mot

ion

FES

syst

em.

•A l

inea

r re

spon

se c

urve

was

obt

aine

d fo

r bo

th m

uscl

es

•With

incr

easi

ng p

ulse

wid

th th

e am

ount

of

curre

nt r

equi

red

to g

ener

ate

a co

ntra

ctio

n of

the

mus

cle

in q

uest

ion

decr

ease

s

THE

BU

TTO

N

Stim

ulat

ion

of Q

uadr

icep

s

19 17

13 12

6755

0510152025

025

5075

100

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Puls

e W

idth

Current (mAmps)

Stim

ulat

ion

of H

amst

rings

1920

1415

776 5

0510152025

025

5075

100

125

Puls

e W

idth

Current (mAmps)

PUR

POSE

To fa

bric

ate

an e

lect

rode

whi

ch c

an b

e im

plan

ted

into

var

ious

ext

rem

ity m

uscl

es in

th

e ra

t whi

ch c

an b

e us

ed to

exa

min

e th

e pa

thop

hysi

olog

ic e

ffect

s of

FES

.

RA

TIO

NA

LE

The

elec

trode

des

ign

mus

t inc

orpo

rate

the

follo

win

g fe

atur

es:

•U

se f

ine,

fle

xibl

e bi

olog

ical

ly i

nert

wire

whi

ch w

ill n

ot i

nduc

ean

inf

lam

mat

ory

reac

tion

in th

e m

uscl

e•

Cau

se m

inim

al d

istu

rban

ce o

f the

mus

cle

tissu

e w

hen

impl

ante

d•

Hav

e m

inim

al in

terfe

renc

e w

ith th

e no

rmal

gai

t pat

tern

and

act

ivity

beh

avio

ur o

f th

e ra

t

•In

expe

nsiv

e•

Dur

able

—to

with

stan

d th

e da

ily m

ovem

ents

of t

he ra

t for

at l

east

one

mon

th•

Eas

y to

fabr

icat

e•

Use

r fri

endl

y—ea

sy t

o im

plan

t an

d ea

sy t

o at

tach

to

the

Com

pex

Mot

ion

FES

sy

stem

REF

EREN

CES

K.W

. Dab

ney,

M. E

hren

shte

yn, C

.A. A

gres

ta, J

.L. T

wis

s, G

. Ste

rn, L

. Tic

e an

d S.

K.

Salz

man

(200

4) A

mod

el o

f exp

erim

enta

l spi

nal c

ord

traum

a ba

sed

on c

ompu

ter-

cont

rolle

d in

terv

erte

bral

dist

ract

ion:

ch

arac

teriz

atio

n of

gra

ded

inju

ry.

Spi

ne 2

9:

2357

-236

4

K.G

. Pe

arso

n, A

.H.

Acha

rya,

K.

Foua

d(2

005)

A

new

ele

ctro

de c

onfig

urat

ion

for

reco

rdin

g el

ectrm

yora

phic

activ

ity i

n be

havi

ng m

ice.

Jo

urna

l of

Neu

rosc

ienc

e M

etho

ds.

(Sub

mitt

ed)

MET

HO

DS

INTR

OD

UC

TIO

NR

ESU

LTS

•In

the

rece

nt d

ecad

e a

num

ber

of F

unct

iona

l Ele

ctric

al S

timul

atio

n (F

ES)

devi

ces

have

bee

n de

velo

ped

to a

ssis

t pe

ople

with

sev

ere

mot

or p

aral

ysis

to i

mpr

ove

gras

ping

and

wal

king

func

tion.

•

The

pote

ntia

l ro

le o

f FE

S th

erap

y as

an

adju

nct

to t

radi

tiona

l re

habi

litat

ion

prog

ram

s is

beg

inni

ng to

be

real

ized

•Th

e go

al o

f FE

S th

erap

y is

to

incr

ease

fun

ctio

n w

ith a

con

com

itant

inc

reas

e in

in

depe

nden

ce a

nd q

ualit

y of

life

.•

How

FES

wor

ks to

impr

ove

mot

or fu

nctio

n re

mai

ns a

mys

tery

.•

An

unde

rsta

ndin

g of

how

FES

im

prov

es m

otor

fun

ctio

n is

crit

ical

to

the

futu

re

deve

lopm

ent a

nd u

se o

f FES

in re

habi

litat

ion

med

icin

e

•P

ears

on e

t al (

2005

) su

cces

sful

ly d

esig

ned

and

impl

ante

d an

EM

G e

lect

rode

into

m

ice.

•Th

e so

le

purp

ose

of

Pear

son’

s im

plan

tabl

e el

ectro

de

was

to

re

cord

th

e m

ovem

ents

of m

ice

and

mea

sure

EM

G.

•Th

is e

lect

rode

is d

iffic

ult t

o fa

bric

ate

and

not s

uita

ble

for F

ES th

erap

y

Vic

ryl S

utur

eKn

ot

Qua

dric

eps

Mus

cle

CO

NC

LUSI

ON

S A

ND

FU

TUR

E PL

AN

S•

The

new

el

ectro

de

was

de

sign

ed,

easi

ly

fabr

icat

ed

and

impl

ante

d w

ith

no

com

plic

atio

ns in

to ra

ts w

ith a

n in

com

plet

e SC

I.

•Th

is e

lect

rode

cau

ses

min

imal

tiss

ue d

amag

e.

•Its

pre

senc

e in

the

quad

ricep

s an

d ha

mst

rings

in th

e ra

t did

not

appe

ar to

alte

r the

ga

it no

r the

dai

ly b

ehav

iour

alac

tiviti

es o

f the

rat.

•Th

e el

ectro

de is

dur

able

, ine

xpen

sive

and

mos

t im

porta

ntly

use

r frie

ndly

•Fu

ture

pla

ns in

volv

e ex

amin

ing

the

path

ophy

siol

ogy

of F

ES in

rats

with

inco

mpl

ete

mod

erat

e sp

inal

cor

d in

jurie

s

24

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