evaluation of the use of exoskeletons in the range of motion of...

Evaluation of the Use of Exoskeletons in the Range of Motion of Workers

Master Degree Project in Virtual Product Realization One year Level 16.5 ECTS Spring term 2019 Estela Pérez Luque Supervisors: Dan Högberg

Aitor Iriondo Examiner: Peter Thorvald

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Abstract

Although the automation level is high within the automotive industry, there is still a high number of manual

labour tasks such as in assembly areas. Taking ergonomics programs into account is essential to improve the

workstation designs and conditions, which should result in increases in worker output and reductions of

discomfort. Work-related musculoskeletal disorders continue to be one of the main problems at industry

today. Exoskeletons are a new technology becoming increasingly important due to its potential reducing

loads, they suppose a possible promising solution to advantage in manufacturing environments.

The purpose of this study is to evaluate and compare how the use of three different models of exoskeletons

affects the range of motion of workers at overhead assembly operations. EksoVest from EksoBionics, Paexo

from Ottobock and MATE from Comau have been the passive upper body exoskeletons involved in the

present project. To develop the comparison analysis an experiment was designed in which seventeen subjects

participated including factory operators and students. The experiment consists of performing three different

tasks (drilling operation and stretching) four times, one with each of the exoskeleton models and another

without them. Observations, interviews and video and motion capture (Xsens equipment) recordings have

been the elements involved in collecting the data.

The results have shown that all the subjects agree that exoskeletons help in this specific overhead task, on the

contrary, for tasks requiring a larger range of motion the performance decreases. Paexo was the preferred

model followed by EksoVest and MATE respectively. However, none of the models got a complete positive

valuation. In addition, statistical analysis of the motion capture recorded data have described a trend of

keeping the arms raised when using the exoskeletons during the tasks than performing it without them.

Positive and negative aspect, activation zone and uses of each of the exoskeleton models are also discussed.

To conclude, the results of this thesis highlight the need for design improvements in order to allow a full range

of movement to workers and increase user performance in a broader number of applications or tasks as well as

to assure a more suitable implementation.

Keywords: Exoskeletons, range of motion, musculoskeletal disorders, ergonomics, overhead operations.

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Acknowledgements

First of all, I would like to express my thankfulness to the University of Skövde and Volvo Cars Corporation,

highlighting my supervisors Dan Högberg and Dan Lämkull, for giving me the opportunity to work in

collaboration with them, provide great resources and instrumentation, help for the development of this master

thesis, and for allow me to get a great deal of knowledge in my area of studies which is going to help me in

my future.

In addition, I especially thank my co-supervisor and friend Aitor Iriondo for his support, guidance, and

patience during the development of this interesting project, and be available to my questions at any time.

Likewise, I gratefully acknowledge Tony Rohdin, Senior Manufacturing Engineer Technology Development

from Volvo Cars Skövde, for all his help and advice building the testbed as well as getting operators for the

experiment.

I also want to place on record, my sense of gratitude to my examiner Peter Thorvald, for his support, advice,

and his way of make me think about the research field.

Last but not least, I would like to make a special mention to my family who have been supporting and

motivating me my entire life to give my best, and to my friends Francisco Garcia and David Hoyos, my

fellows of adventures, the ones who have made feel at home even being abroad.

Skövde, May 2019

Estela Pérez Luque

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Certificate of Authenticity

Submitted by Estela Pérez Luque to the University of Skövde as a Master Degree Thesis at the School of

Engineering.

I certify that all material in this Master Thesis Project which is not my own work has been properly

referenced.

Estela Pérez Luque

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Table of Contents

1 Introduction ................................................................................................................................................. 1

1.1 Background.......................................................................................................................................... 1

1.2 Formulation of the problem ................................................................................................................. 2

1.3 Research Methodology ........................................................................................................................ 2

1.4 Process Diagram .................................................................................................................................. 3

2 Literature Review ........................................................................................................................................ 5

2.1 Ergonomics .......................................................................................................................................... 5

2.2 Musculoskeletal Disorders (MSDs) ..................................................................................................... 6

2.2.1 Why are musculoskeletal disorders important? ........................................................................... 6

2.2.2 What are Musculoskeletal Disorders (MSDs)? ........................................................................... 6

2.2.3 What are the causes and risk contributing to MSDs? .................................................................. 7

2.2.4 How to tackle MSDs? ................................................................................................................ 10

2.3 Musculoskeletal Disorders at Industry .............................................................................................. 11

2.4 Exoskeletons ...................................................................................................................................... 12

2.5 Exoskeletons at Industry .................................................................................................................... 14

2.5.1 EksoVest .................................................................................................................................... 15

2.5.2 Paexo ......................................................................................................................................... 16

2.5.3 MATE ........................................................................................................................................ 17

2.6 Ergonomic Assessments .................................................................................................................... 17

2.7 Range of motion / Motion Capture .................................................................................................... 19

3 Method ....................................................................................................................................................... 21

3.1 Approach ........................................................................................................................................... 21

3.2 Scenario ............................................................................................................................................. 21

3.3 Subjects ............................................................................................................................................. 23

3.4 Task Description ................................................................................................................................ 23

3.5 Apparatus and instrumentation .......................................................................................................... 24

3.5.1 Comparison of exoskeletons ...................................................................................................... 24

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3.5.2 Instrumentation: Xsens equipment ............................................................................................ 25

3.5.3 Tools .......................................................................................................................................... 26

3.6 Procedure ........................................................................................................................................... 27

3.7 Data collection and analysis .............................................................................................................. 28

4 Results ....................................................................................................................................................... 31

4.1 Qualitative results .............................................................................................................................. 31

4.2 Quantitative results ............................................................................................................................ 33

5 Discussion.................................................................................................................................................. 35

5.1 Results ............................................................................................................................................... 35

5.2 Research Method ............................................................................................................................... 37

5.2.1 Data Collection and Analysis .................................................................................................... 37

5.2.2 Experiment ................................................................................................................................ 38

5.3 Theoretical contribution .................................................................................................................... 39

5.4 Application ........................................................................................................................................ 40

6 Conclusion ................................................................................................................................................. 42

7 Future Work............................................................................................................................................... 43

References ......................................................................................................................................................... 44

Appendix A: Statistical Analysis ................................................................................................................ 52

7.1 Subject 2 ............................................................................................................................................ 52

7.2 Subject 3 ............................................................................................................................................ 53

7.3 Subject 4 ............................................................................................................................................ 54

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Table of Figures

Figure 1. Project Process Diagram. ..................................................................................................................... 4

Figure 2. Body parts affected by MSDs. (Image provided from EU-OSHA, 2018) ........................................... 7

Figure 3. Conceptual framework of psychological factors contributing to musculoskeletal disorders. (Image

obtained from NCBI, 1999) ................................................................................................................................. 9

Figure 4. Exposure to different possible risks in the work-area indices (0-100), by countries. (Image from

(Parent-Thirion et al., 2017)). ............................................................................................................................ 11

Figure 5. Exposure to different posture-related risks, by sexes (%). (Image from Parent-Thirion et al., 2017).

........................................................................................................................................................................... 11

Figure 6. Upper body, lower body and full-body exoskeletons. (Image from Ashley, 2017; Thilmany, 2017;

Wang, 2015) ...................................................................................................................................................... 13

Figure 7. EksoVest exoskeleton (EksoBionics). ............................................................................................... 16

Figure 8. Paexo exoskeleton (Ottobock). .......................................................................................................... 16

Figure 9. MATE exoskeleton (Comau). ............................................................................................................ 17

Figure 10. Dimensions testbed. ......................................................................................................................... 22

Figure 11. Nuts in testbed to screwed operation. .............................................................................................. 22

Figure 12. Involved movements in the tasks (a. Rotation; b. Bending; c. Stretching). ..................................... 24

Figure 13. Comparison of exoskeletons (a. EksoVest; b. Paexo; c. MATE) (Image from a. (EksoVest, n.d.); b.

(Paexo, n.d.); c. (Comau, n.d.)) ......................................................................................................................... 25

Figure 14. Position of Xsens sensors in human body. ....................................................................................... 26

Figure 15. Tools: screwdriver and screws M12. ............................................................................................... 26

Figure 16. Experimental procedure. .................................................................................................................. 27

Figure 17. Body dimensions and initial positions for calibration (N-pose and T-pose) .................................... 27

Figure 18. Basic shoulder movements. (Image from https://sequencewiz.org/2016/03/16/loosen-up-your-

shoulders/) ......................................................................................................................................................... 29

Figure 19. Example of joint angle data by Xsens system. ................................................................................. 30

Figure 20. Statistical analysis: Task 1 ............................................................................................................... 34

Figure 21. Statistical analysis: Task 2. .............................................................................................................. 34

Figure 22. Statistical analysis: Task 3. .............................................................................................................. 34

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Figure 23. Arm adjustment Paexo. .................................................................................................................... 35

Figure 24. Comparison adjustments to the arms (EksoVest, Paexo, and MATE). ............................................ 36

Figure 25. Comparison adjustments to the lower back and chest (Paexo and MATE). .................................... 36

Figure 26. Comparison design exoskeletons model (EksoVest, Paexo and MATE). ....................................... 37

Figure 27. Activation zones. .............................................................................................................................. 40

Figure 28. In-front assembly operations. ........................................................................................................... 41

Figure 29. Subject 2. Statistical analysis: Task 1 .............................................................................................. 52









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Index of Tables

Table 1. Ergonomic Assessment Tool Use in the Industry. .............................................................................. 18

Table 2. Comparison of exoskeleton models. .................................................................................................... 25

Table 3. Colour criteria. ..................................................................................................................................... 31

Table 4. Subject preferences of exoskeleton models. ........................................................................................ 31

Table 5. Positive and negative points: EksoVest. .............................................................................................. 32

Table 6. Positive and negative points: Paexo. ................................................................................................... 32

Table 7. Positive and negative points: Mate. ..................................................................................................... 32

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1 Introduction

This chapter introduces the background to the problem as well as describes the main goal and

objectives in the thesis.

1.1 Background

In an ever-faster world, where the vision of the 4th industrial revolution is currently being triggered

and is characterized by the global market competence, the large amounts of information, and

especially the rapid advances and changes in technology, the improvement of efficiency and

productivity in industry is a key factor to survive and assure the future of the company and its

enlargement. In order to achieve this goal, the business should face these aspects by searching for

and implementing new suitable methods to boot the company’s profit while keeping customer

demands (Cherrafi et al., 2016; Deeb et al., 2018). Automation and the data exchange in

manufacturing technology, which includes the cyber-physical systems (CPS), internet of things and

the cloud computing services are the concepts of the Industry 4.0, and which integration in

production systems affects both the job design and the way of work for employees.

Although automation is getting a high level of implementation in industry, there is still a large

number of manual tasks at factories such as final assembly areas. The need to incorporate and

consider ergonomics is unquestionable and required for the implementation and development of

these aforementioned concepts as well as to improve working designs and conditions. People

constitute the most important asset of a company, from customers to workers themselves (Bicheno

and Holweg, 2009). To ensure their satisfaction and well-being is a fundamental point for the

enterprise. Ergonomics manage the interaction between humans and machines in a specific work

environment, with the purpose to optimize such interaction (Kukula and Elliott, 2006). Moreover,

ergonomics can be also considered in the product development process as well as in the business

strategy to improve the aforementioned interaction between humans and machinery from an early

stage, and in this way, avoid future costs in improvements (Dul and Neumann, 2009). Another chief

point is that by implementing ergonomic measurements, work-related musculoskeletal disorders

(WMSDs) the major health issue in the industry that supposes costs and damage for both the

company and the humans, is addressed.

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At this point is where exoskeletons come. Exoskeletons are a new technology with very limited

implementation in practice. They are rather in a testing or experimental stage. However, the interest

in them is considerably increased due to its potential reducing loads for workers, they are seen as a

promising solution to reduce the level of discomfort as well as the number of musculoskeletal

disorders.

1.2 Formulation of the problem

The aim of the present project is to research and evaluate the use of exoskeleton systems at the

assembly plant when performing overhead operations in the automotive industry (Volvo Cars). It is

performed from an ergonomic perspective, as a preventive method for musculoskeletal disorders as

well as for increasing the well-being of workers. In more detail, the project consists of analysing and

comparing the range of motion and impressions of the workers when performing the overhead

operations, with and without wearing three different exoskeletons. The range of motion is recorded

with Xsens, a kinematic measurement system which works with sensors (inertial measurement units).

The holistic goal is to know if the implementation of this system suppose benefits for the involved

workers and further the company from a range of motion approach, or whether, on the contrary, it

does not contribute to advance. The company provided for the development of the thesis three

different upper body exoskeleton models. The objectives involved in the development of the present

study are as follows:

- Design and build a testbed scenario as realistic as possible to the workstations at the real

factory to carry out the tests.

- Design an experiment to evaluate the effect of the exoskeletons in the range of motion of

workers.

- Investigate the strengths and weaknesses of each exoskeleton (EksoVest, Paexo, and MATE).

- Analyse and compare the range of motion of users with each of the models and without.

1.3 Research Methodology

The present project consists of studying how the use of exoskeletons devices affects the range of

motion of workers. It aims to find what is the cause and effect relationship between the mentioned

system devices and the movements of workers. Following this line, the research strategy of the

present argument is an experiment, which definition according to the book Researching Information

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Systems and Computing is “a strategy that investigates cause and effect relationship, seeking to

prove or disprove a causal link between a factor and an observed outcome” (Oates, 2006). The

evaluation of this link between the involved factors and outcomes will be based on both qualitative

and quantitative analysis, and objectivity is considered in the whole experiment development.

1.4 Process Diagram

Figure 1 below shows how the project was organized and the different steps involved in its

development. After formulating the problem, defining the objectives and establishing a project plan,

the first step was to get an overview of the main aspects involved in the targeted research, which are

Musculoskeletal Disorders, Exoskeletons, and Range of Motion. Definitions, types, and studies of

these mentioned areas were investigated to gain information of the general picture of the problem

and use it in the development of the thesis as well as a base to design the experiment. After that, the

experiment development took place in the designed and built testbed as a working example of the

real factory situation. The experimental execution constitutes the data collection based on

observations, interviews, and recordings by video camera and a motion capture system. The

experiment consisted of the performance of three different tasks with three exoskeletons provided by

the company in collaboration in this project and without them. After that, the subjects were

interviewed. The next step addressed the quantitative and qualitative analysis of the collected data

during the experiments. The process concluded with the documentation and presentation of the

thesis.

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Figure 1. Project Process Diagram.

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2 Literature Review

This chapter presents different essential concepts as well as related studies to the targeted research

such as Ergonomics, Musculoskeletal Disorders, Exoskeletons, Ergonomic Assessments and Range

of Motion.

2.1 Ergonomics

According to the International Ergonomics Association (IEA) ergonomics or human factors “is the

scientific discipline concerned with the understanding of interactions among humans well-being and

the overall system performance” (“IEA,” 2000). By this definition can be seen that ergonomics not

only has the social goal (well-being), but also the economic goal (total system performance), in other

words, the purpose of ergonomics is to achieve an optimal relationship between them, to provide a

safe workplace to worker’s comfort while fulfilling the company’s objectives as well as the

productivity and product quality. In general, the ergonomics aims to adapt or fit the work to

individuals, instead of adapting individuals to the work (Jaffar et al., 2011; Kukula and Elliott, 2006).

The broad ergonomic discipline is divided into three different domains of specialization depending

on the human attributes or human characteristic interaction: Physical ergonomics (physical activity),

Cognitive ergonomics (mental processes) and Organizational ergonomics (sociotechnical systems)

(“IEA,” 2000).

Ergonomic improvement processes not only increase human performance and productivity but also

reduce the level of risk factors in the work environment, which lead to musculoskeletal diseases.

Recently, the global business competence and some issues as the increment of the retirement age

have increased the interest of implementing ergonomics aspects within organizations, it can be a key

contributor to better work experience as well as to company’s competitiveness (Dombrowski and

Wagner, 2014; Middlesworth, 2016).

On another hand, ergonomics often is associated with the health and work conditions (manufacturing

process), nonetheless, it can and should be also considered in the product development process, and

even further in the company’s strategy as a fundamental key for success; by considering the working

and workers' conditions from an earlier stage, future improvements costs and time would be avoided

(Diban and Gontijo, 2015; Dul and Neumann, 2009).

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2.2 Musculoskeletal Disorders (MSDs)

Musculoskeletal Disorders (MSDs) is one of the main cause why companies contemplate the

implementation of new systems that make improvements in the work environment and workers’

well-being (Beevis, 2003). Next, such problem will be developed and explained in detail.

2.2.1 Why are musculoskeletal disorders important?

Musculoskeletal disorders are the second largest causal to disability worldwide, and the most

common work-related problem in Europe. They cost business, national economies and employers

billions of Euros due to huge administrative, medical and worker compensation costs. In addition,

the aforesaid is not the only issue for employers, the reduction in efficiency because of loss of

productivity and sickness absences should be considered. With respect to the suffers, MSDs may also

have severe consequences as loss of self-belief or mental health problems caused by not being able to

be active because of the developed pain(“EU-OSHA - Guide,” 2018).

2.2.2 What are Musculoskeletal Disorders (MSDs)?

Musculoskeletal Disorders (MSDs) are injuries and disorders that affect the human body’s

movement or musculoskeletal system, that is muscles, ligaments, bones, nerves or joints of the neck,

upper and lower limbs (Middlesworth, 2011).

Between one in five and one in three people live with pain and disabling musculoskeletal condition,

which means, musculoskeletal disorders affect people in all the regions of the world through their

life-course. Although it increases its impact across the old age, younger people are also affected

especially in their income years in working (“WHO,” 2018). Pain is the main noticeable symptoms

related to MSDs, which can result in limitation of motion, difficulties for keeping a body position for

long periods of time, or in a further step in disability (Woolf and Pfleger, 2003). MSDs can have a

specific medical diagnosis, but in some cases, such pain, swelling, tingling, numbness or physical

discomfort may do not have a specific diagnostic (Palmer, 2000; Spallek et al., 2010).

Musculoskeletal disorders are primarily caused or aggravated by the effect of the environment where

the work is carried out and by the work itself. The most common MSDs that worker experiences are

neck or back pain, muscle injuries, joint conditions, and bone conditions (“EU-OSHA - Guide,”

2018); and more specifically osteoarthritis, rheumatoid arthritis, osteoporosis, and low back pain

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(Woolf and Pfleger, 2003). Figure 2 below shows in a graphic way the body parts that can be

affected by MSDs.

Figure 2. Body parts affected by MSDs. (Image provided from EU-OSHA, 2018)

2.2.3 What are the causes and risk contributing to MSDs?

Contrary to popular belief, accidents or unexpected mishaps that strain ligaments or break bones and

muscles are not the cause of the majority of musculoskeletal disorders. Usually, there is no single

cause of MSDs; but rather it comes as a combination of several factors working together. Such

injuries can be also developed slightly as a consequence of repeated micro trauma, which is often

ignored until the symptoms become evident and result in permanent or chronic injuries (Putz-

Anderson, 1988). Different groups of factors acting uniquely or in combination contribute to the

development of MSDs, containing biomechanical and physical factors, as well as organizational,

psychological and personal factors.

Biomechanical and physical factors

The biomechanical and physical factors involve the function, motion and structure of the mechanical

aspects of the biological systems (muscles skeletal system) (Hatze, 1974).

- Handling loads, especially when bending and twisting.

When a particular tissue receives a new change influence over a long period, the

musculoskeletal system (bones, muscles, tendons, etc.) starts developing the resilience to

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adopt the required new demand until the aforementioned stimulus becomes regular. Without

training over a long time, the muscle’s strength and volume are reduced, and that fact makes

that by the overexposure of load and the friction between the tendons and its adjacent

surfaces can lead to damage and degeneration in tendons itself (Ashton-Miller, 1999).

Duration of the load, its size, time lag, and repetition are key parameters to determine the

tissues adaption and estimate the possible consequences on the human organism.

- Repetitive or forceful movements.

Not only the handling load, but the number of movement’s repetitions can also come as a

chief problem leading MSDs since the involved joints and tissues in the task are demanded

ongoing work performing the same monotone operation. The short lag time between the

stimulus can involve inflammatory reactions due to the lack of the needed time to rest and

help up. In addition, it may also lead changes to more serious or chronical problems. In this

type of repetitive tasks, long periods of time increase the negative impact of getting

musculoskeletal disorders.

- Awkward and static working postures.

Awkward and static positions are causes of MSDs as well. Nevertheless, they are more

difficult to identify than, for example, a high level of load, which has the focus of ergonomic

measurement due to its evidence. Standing or working in the same corporal position during

long times increase the stress in the involved tissues of the musculoskeletal system, as well as

foster sedentary behaviours that trigger in morbidity and mortality illness (cardiovascular

disease, diabetes, and some cancers) (Buckley et al., 2015). Tissues (muscles, ligaments,

cartilages…) need the change of stimulus (alteration of loads and reliefs) over them to be

supplied by enough amount of nutrients (Jerosch, 2011; Snedeker and Foolen, 2017).

Consequently, keeping a static position for long periods of time reduces the aforementioned

alteration of stimulus, and therefore, the supplied nutrients are also reduced inducing to

bodily damage.

- Vibrations

Animal models experiments have demonstrated that the daily exposition of vibration can

cause intraneural oedema, functional changes in both nerve fibers and non-neuronal cells, as

well as structural changes in myelinated and unmyelinated fibers in the sciatic nerve. Related

to people, vibration exposure from hand tools at work can generate changes in structural

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neuronal of fingers as well as the proximal nerves trunk to the wrist (Dahlin and Lundborg,

1999).

All in all, the human organism is able and tend to adapt itself to new demands or situations very

flexible. However, the intensity of loads, duration and the recovery time are keys in this process of

adaptation, which is not always successful, and actually may trigger diseases and body injuries. The

aforementioned points are the main responsible causes when developing musculoskeletal disorders,

but not the only ones. Other factors that involve and can lead musculoskeletal disorders are the poor

lighting, extreme temperatures in work environments or fast-paced work (Daub, 2017).

Psychological, organizational and personal factors

On another hand, there are also non-physical and non-biomechanical factors that have an influence

on the development of musculoskeletal disorders. The evidence linking psychological risk factors

and MSDs is growing, and it particularly increases in combination with biomechanical factors (“EU-

OSHA,” 2019). Figure 2 below shows a conceptual framework of the psychological factors affecting

the musculoskeletal disorders, in which organizational, social and individual factors are the root

sources directly affecting musculoskeletal disorders. MSDs normally do not result only from the

aforementioned points in isolation, they rather come from a combination of biomechanical,

psychological, organizational and personal factors.

Figure 3. Conceptual framework of psychological factors contributing to musculoskeletal disorders. (Image obtained from NCBI, 1999)

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Organizational and social variants are job content and demands, time pressure, workload, job control,

job autonomy, and social support; such factors are directly associated with the level of psychological

stress. However, positive aspects are also considered, such as job enjoyment and job satisfaction

(Anderson et al., 1997). One example of how this factor works would be that due to the high-

pressure time, the worker increases the speed of movements in the tasks, and therefore, the dynamic

forces involved in the respectively used tissues.

With respect to an individual or personal factors, they are the ones that do not have any relationship

with the work activities, and hence, differ in each individual person. The susceptibility from each

different person affects also in a different grade. Age and prior medical conditions are the variants

with a stronger influence of biomedical mechanism, but also other factors with less mechanism

evidence are equally strong epidemiological, like gender, obesity or smoking, and going a step

further it would come genetics (Faucett, 1999).

The psychological stress is the main representation across the organizational, social and individual

factors, and it has a causal character as the root of musculoskeletal problems. Nonetheless, the

percentage of non-biomechanical factors is quite lower than the biomechanical ones as a cause of

musculoskeletal disorders (NCBI, 1999).

2.2.4 How to tackle MSDs?

By tackling MSDs not only the life of workers improves, but it also becomes better the business.

That statement is the fundamental reason to tackle MSDs. Consider holistic approach management

including not only the prevention of new injuries but also the rehabilitation, retention, and

reintegration of workers who already have suffered the disorders is necessary to face the problem

(“EU-OSHA-Factsheet 71,” 2007). Face preventive actions for musculoskeletal disorders could

include changes in workplace layout, workers, equipment, tasks, management and organizational

factors (“EU-OSHA-Factsheet 4,” 2000). However, musculoskeletal disorders are also influenced for

non-biomechanical risks like obesity, smoking or poor nutrition, aspects that cannot be covered for

companies (“WHO,” 2018).

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2.3 Musculoskeletal Disorders at Industry

Regarding the 6th European Working Conditions Survey (EWCS) (Parent-Thirion et al., 2017), a

survey that aims to measure, analyse and identify the working conditions across 35 European

countries performed in 2017, posture-related problems are the most frequent risk within industry in

Europe, as can be observed in Figure 3 below. Figure 3 shows the exposure level indices to three

different risks (posture-related, biological and chemical, and ambient) by countries, in which

posture-related factor is the most repeated as highest.

Figure 4. Exposure to different possible risks in the work-area indices (0-100), by countries. (Image from (Parent-Thirion et al., 2017)).

In particular, within posture-related risks, repetitive movement of hands and arms is the most

reported task from workers (men and women) in some 61%, Figure 4.

Figure 5. Exposure to different posture-related risks, by sexes (%). (Image from Parent-Thirion et al., 2017).

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The expressed data illustrates the high rate of reported injuries in the work environment, and that is

why is important to prevent and manage WMSDs problem in the industry.

Overhead work is defined as any work that requires the hands in a position above the height of the

shoulders, in essence, above the head (Grieve and Dickerson, 2008). Postures with greater angle than

60º of shoulder flexion or abduction, although the hands may not be over the acromial height, are

defined as awkward due to this type of operation constitutes a challenge on the shoulder complex.

These postures are not only awkward but they also include limitations in the range of motion and

repetitive issues. Several studies have demonstrated the evidence of the association between these

exposures and the development of pathologies as tendonitis, impingement, rotator cuff syndrome or

muscle fatigue that can lead to the inability to work in short or long term (NIOSH, 1997).

According to J.R. Grieve and C.R. Dickerson (2008), shoulder's musculoskeletal disorders cause an

average of twelve lost working days per affected person per year. WMSDs in the neck, back, and

upper extremity meant the direct cost of $3.8 billion per year, and more in detail, rotator cuff

syndrome injuries exceeded $25,000 in costs at Washington State during 1994 and 2004 (Silverstein

and Adams, 2006). All in all, overhead operations in the industry can cause musculoskeletal

disorders that result in a loss of both productivity and financial costs. In addition, these injuries may

also lead to physiological and biomechanical consequences.

2.4 Exoskeletons

Exoskeletons can be defined as wearable mechanical devices that work collaboratively with the user

(Marinov, 2015; Wesslèn, 2018). It does not constitute an autonomous device that replaces the

operator, it rather consists of a way of support and assists the user or worker. Some identify and

define these devices, especially the powered ones, as wearable robots trying to the increment a

human’s physical performance (Knaepen et al., 2014).

Exoskeletons can be divided in different categories depending on the several aspects, as their form

factor, construction material, power requirement or intended use (Kara, 2018; Looze et al., 2016):

- Upper body, lower body and full-body exoskeletons. Depending on the human part where the

exoskeletons will support or provide power. Upper body (Figure 6a) devices cover back,

shoulder complex, elbow complex and wrist joint, lower body (Figure 6b) devices are

focused on the leg and pelvis complex and the full-body exoskeletons (Figure 6c) fill both the

previous said.

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Figure 6. Upper body, lower body and full-body exoskeletons. (Image from Ashley, 2017; Thilmany, 2017; Wang, 2015)

- Powered and unpowered exoskeletons. Active exoskeletons compromise one or more power

sources (electric motors, pneumatic or hydraulic actuator, among others) to actuate in the

human joints (Gopura and Kiguchi, 2009). A passive system uses mechanism as springs and

dampers to store the energy of the human movements and reuse it later on.

- Rigid and soft exoskeletons. Exoskeletons can be made of rigid materials such as metal or

carbon fiber, as well as of elastic, lightweight and soft ones. The last mentioned material is

increasingly being used due to they are easier to adapt to the natural human movements and

reduce the number of injuries.

- Final use. Depending on the intended use, exoskeletons can also be divide into three different

categories (Wang et al., 2017; Young and Ferris, 2017):

1. Human Performance Augmentation (HPA) where the devices aim to increase the

physical capabilities of the users, normally in industry. Lifting, carrying and

working with heavy tools are some examples.

2. Assistive devices, which allow disable people to perform movements they could

not complete by their own (for instance, walking or arm movements).

3. Rehabilitation, where the robotic suits are used to train the user’s muscle and

nerve injuries, and in this way, overcome such limitation in the higher possible

range.

The main application of exoskeletons has been in the medical/rehabilitation field, with the purpose of

assisting disabled people and injuries as well as improve the range of daily activities motion, and

therefore, the quality of patient’s life (Rupal et al., 2017). Another area of application is military;

exoskeletons have been designed aiming to augment the soldier’s strength and carrying capabilities.

However, these are not the only areas where exoskeletons are involved. In the last years, the interest

to introduce them in the industry has considerably raised mainly with the advances in robotics and

a b

a

c

a

14

automation. Nevertheless, it is still barely implemented. They are rather in a testing stage to

overcome some challenges regarding the human-robot interaction (Dollar and Herr, 2008; Looze et

al., 2016; Wang et al., 2017).

2.5 Exoskeletons at Industry

The implementation of the exoskeletons systems in the industry aims to exploit the interaction

between human and robots in the performance of tasks, by combining the operator’s intelligence

capabilities and the device’s endurance. Following this line, exoskeletons technology can be seen as

a way out or solution between the complexity of manual work, and those operations that typically

would demand the use of robots, mainly repetitive tasks (Kara, 2018; Weidner et al., 2013).

Several scientific articles have reviewed and addressed the technical aspects of the use of

exoskeletons in the industry like Yang et al., (2008), Pirondini et al., (2016), Wang et al., (2017)

among others. Looze et al., (2016) provide an overview of 26 different exoskeletons (19 active and 7

passive models) that have been developed or are in process of development for industrial uses,

obtaining in most of the models, both passive and active models, positive impact results on the user.

Huysamen et al., (2018) also demonstrate the positive effects with a reduction of muscle activity

when using a passive exoskeleton for static upper limbs activities. On another hand, Dahmen and

Hefferle, (2018) applied various ergonomic assessment methods, which evidenced positive changes

at a workplace example (typical of the automotive industry) with a sample of a passive exoskeleton.

Although the good aforementioned effects of exoskeletons, especially on muscle activity, the use of

these devices in the industry is scarce. There is still a need to further develop and improve key

technical issues related to the anthropometric compatibility with operators, design of actuators or

model’s weight (Daub, 2017; Viteckova et al., 2013; Wang et al., 2017), as well as the lack of a

holistic method able to generic an assessment of the use of this device (Dahmen and Hefferle, 2018).

Not many articles have addressed the possible negative aspects of the implementation of

exoskeletons in industry, for example, the shift of biomechanical load to other muscles group or

joints in the body, or limitations on compatibility with the users and their range of motion, even

when some studies have shown postural changes with specific models of exoskeletons (Ulrey and

Fathallah, 2013a; Weston et al., 2018).

Baltrusch et al. (2018) obtained both positive and negative results when studying how a passive trunk

exoskeleton affect the functional performance of different tasks, based on general and local

15

discomfort and perceived task difficulty. Wearing the exoskeleton increased the performance of

specific and static tasks such as assembly works, however, it showed adverse effects and limitations

on tasks requiring a larger range of motion like walking. Sylla et al. (2014) also investigated the

impact of exoskeletons on postures and movements. Their results described a favourable significant

reduction on the joints torques for assembly operations at overhead position in the automotive

industry.

Currently, the AnDy project, which has received funding from the European Union’s Horizon 2020

Research and Innovation Programme, aims to improve the ability of robots in collaboration with

humans in a domestic and industrial environment (Dring, 2017). The second part of this project

(three different studies) has the purpose of researching the effects of the use of the exoskeleton on

the human body evaluating both kinematic and dynamic measures. The exoskeleton used in this

study is Paexo model from the company Ottobock, one of the models used in the present project,

however, the results have still not been officially published (Ivaldi et al., 2017).

Next, the three passive upper body exoskeletons involved in the development of the present thesis

will be described, they were provided by the company in collaboration, Volvo Cars.

2.5.1 EksoVest

EksoVest (Figure 7), from the company Ekso Bionics, is a passive upper body exoskeleton indicated

for elevating and supporting user’s arms while performing tasks in a range from chest height to

overhead position. This exoskeleton model also offers a kit with additional components to adjust the

fit for operators of different sizes (“EksoVest,” n.d.). A collaboration between EksoWorks (part of

Ekso Bionics) and Ford Motor Company introduced pilot tests of the EksoVest exoskeleton at two

plants of USA and soon in Europe and South America as well (Dearborn, 2017). BMW Group has

been also investigating this exoskeleton model during 2016 and beginning of 2017, they plan to

introduce around 44 more units of them at the plant of Spartanburg (Marinov, 2017). Kim et al.

(2018) addressed a study about the effectiveness of wearing an example of this exoskeleton at

overhead work. The obtained results showed no significant discomfort and reductions in muscle

activity and function performance. However, the number of errors during performing the drilling task

increased with the use of the exoskeleton. Table 2 below describes the main characteristics of the

model.

16

Figure 7. EksoVest exoskeleton (EksoBionics).

2.5.2 Paexo

The Paexo exoskeleton (Figure 8), from Ottobock company, is the second passive exoskeleton for

the upper body used in the experiment. It assists employees in production during activities, especially

overhead by a mechanical cable pull technology (“Paexo,” n.d.). Thirty Paexo exoskeletons are

currently being used in a long-term pilot test in the series production at Volkswagen’s Bratislava

plant (Bärbock and Gautsche, 2018). In addition, this exoskeleton model has not been only

introduced at overhead work in the automotive industry but also in the yacht building. Table 2

describes the main features of the model.

Figure 8. Paexo exoskeleton (Ottobock).

17

2.5.3 MATE

MATE exoskeleton (Figure 9), from Comau Company, is an upper-body exoskeleton that uses

spring-based structure to support workers of excessive effort during daily tasks performance. This

exoskeleton had been designed and developed in close collaboration with workers at AGAP

(Avvocato Giovanni Agnelli Plant) assembly plant (Lorenza, 2018), and thanks to the partnership

between Comau, IUVO, company specialized in wearable technology of the BioRobotics Institute

and ÖSSUR, an orthopedic company. It was officially presented in October 2018 in the annual

Congress on Asset Management and Maintenance and Exhibition of Products, Services, and

Equipment in Brazil (Horizonte, 2018). Table 2 describes the main characteristics of this exoskeleton

model.

Figure 9. MATE exoskeleton (Comau).

2.6 Ergonomic Assessments

One of the main task to deal with the work-related musculoskeletal disorders (WMSDs) problem is

to evaluate the work environment. By quantifying the risk within them is possible to develop and

implement an improvement measurements plan, that thereby, makes jobs ensure tasks are within the

worker’s capabilities. The efficient and effective use of the correct ergonomic assessment is required

to achieve the aforesaid. In short, the aim of ergonomic assessments is to identify the level of risk for

the task or job evaluated (David, 2005).

18

Currently, there is a broad range of different scientific assessment methods to use, they all try to

evaluate the ergonomic situation focusing on ergonomic and biomechanical factors such as time,

load and body posture. Likewise, each of them also follows as base one of the next aspects:

questionnaires, forms for monitoring tasks, norms and threshold tables (Daub, 2017). On another

hand, to choose the correct analysis method, which has to match with the type of job task, is

essential. Table 1 below collect the main ergonomic assessment tools in the industry, and the type of

task they are used for (Dahmen and Hefferle, 2018).

Table 1. Ergonomic Assessment Tool Use in the Industry.

Type of Task Ergonomic Assessment Tool

Lifting/Lowering WISHA Lifting Calculator

NIOSH Lifting

Upper Body Posture Rapid Upper Limb Assessment

(RULA)

Entire Body Posture Rapid Entire Body Assessment

(REBA)

Pushing / Pulling / Carrying

Snook Tables

Vibration Hand-Arm Vibration Calculator

The previously mentioned tools do not need much equipment; they basically can be applied by

following a guide of steps. Observation method is the general source of information, which include

some degree of subjectivity and can change depending on the perception of the assessor. That makes

the ergonomic assessment vulnerable to errors, and this error may increase when regarding posture

and load estimations (Denis et al., 2000; Spielholz et al., 2001). However, the use of technical

devices allows measuring directly the physical exertion and human movements during work. This

provides objective and high accuracy data, but also increase the costs involved in the ergonomic

assessments. In a state-for-the-art step, ergonomic analysis and assessment can be measured by

digital human modelling tools, and predict the risk before implementation in real life (Keyvani et al.,

2014).

There is no established method yet to evaluate exoskeletons. The use of direct measurement methods

that collect kinematic and kinetic, as well as EMG (electromyography), which determine what

muscles are stressed (Gillette and Stephenson, 2017; Jones and Kumar, 2007) would provide more

useful and accurate information to assess. Subdividing into different parts or studies is a useful

strategy to deal with the exoskeletons’ assessment (Daub, 2017). The fact that there is no established

method to evaluate the influence of exoskeletons in a holistic way is another reason for its bare

implementation in industry.

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2.7 Range of motion / Motion Capture

Range of Motion (ROM) is the available amount of movement, linear or angular distance, around a

specific joint. To get the full range of motion of a joint is essential the flexibility, which is the ability

of tissue structures (ligaments, tendons, muscles) to elongate the joint or joints effectively through

the available range of motion (Konin and Jessee, 2012). Physiologic conditions may lead to

limitations in the range of motion, reductions in the ability of joints to move. Traumatic incidents

like surgery or disuse of tissue such as lack of searching can lead joint swelling, pain or stiffness,

these are some factors that may contribute to the loss of range of motion (Harner et al., 1992;

Shanley et al., 2011). Other factors that affect the loss of joint range of motion are the age and gender

(Doriot and Wang, 2006).

Physical and occupational therapy can help to prevent the development of muscle or ligament

shortening, contractures as well as provide sensory stimulation and treat injuries. There are three

main types of range of motion exercises (Dutton, 2014):

- Active Range of Motion (APOM). The patient performs the exercise to move the joint around

the range of motion independently, without any assistance.

- Active Assisted Range of Motion (AAROM). The patient needs some assistance from the

therapist or equipment (manually, mechanical, or by gravity) to perform the exercise and

move the joint.

- Passive Range of Motion (POM). The physical therapist or specific equipment moves the

joint with no effort from the patient through the range of motion.

To measure range of motion in the joints, therapists commonly use goniometers and inclinometers,

which are devices that consist of a stationary arm, a fulcrum, a protractor, and a movement arm to

measure the angle from the axis of the joint (Brosseau et al., 2001; Gajdosik and Bohannon, 1987).

Some specific parts of the body (ankle) can be also measured with tape measures (Hoch et al., 2011;

Verhagen et al., 2001).

Recent technological advances in 3D motion capture, a way of digitally record the movement of

objects or people, has extended the way of measuring the range of motion. Motion capture is used in

a wide range of industries, including military, medical, sports, and entertainment (Metcalf et al.,

2013). Through the years, different methods of system capture have been developed, they can be

categorized in optical, mechanical, magnetic, acoustic and inertial trackers (“Xsens Motion Capture -

20

History,” n.d.). The use of this technology not only allows the measure of range of motion of joints

in the human body (distance or angle), but also significant parameters of body motion like the

postural transitions (the nature of motion) and its features of space and time (acceleration, velocity,

displacement, rotation, etc.) (Aminian and Najafi, 2004).

Related to designing exoskeletons, to promote high performance, ensure safe operation and

comfortability of users is essential to consider the degrees of freedom, orientation as well as the

range of motion of all the involved joints in the model (Perry et al., 2007).

21

3 Method

This chapter describes all the elements involved in the experiment research as well as the procedure

and data collection and analysis techniques.

3.1 Approach

An experimental study was designed to determine the possible effects on the range of motion of

workers while using an exoskeleton during a manual assembly operation. The experiment included

three tasks to perform whit three different models of exoskeletons (EksoVest, Paexo, and MATE),

and without them. The implementation of these devices was simulated at a workplace example, a

testbed. Using the Xsens motion capture system in combination with a video camera, the kinematic

data and the subjective opinions of the participants during the performance of the test's experiments

were measured to carry out the comparative analysis.

3.2 Scenario

The scenario involved in the experiment is a real workplace example of overhead assembly

operations. The company involved in the project, Volvo Cars, provided images about the assembly

operation area and tasks in order to design and build a replica as realistic as possible. The actual

operation in the factory consists in the attachment of plastic plates beneath the car station, however,

such operation has variables depending on the car model. The cars are statics and lifted up in a height

of 1.75 cm from the floor, at this height is where the assembly takes place. The “takt time” in the line

is around 60 cars per hour.

Considering the aforementioned information, to replicate the real work station but also to be able to

perform the experiment in good space conditions, the testbed was designed with 164 cm x 246 cm x

200 cm (width x depth x height) dimensions, Figure 10. A mobile mechanism makes possible to

adjust the height of the plate for the task. The workers stand below the frame and can access the

“underfloor of the car” where four fixing nuts have been added in order to execute the screwed tasks,

Figure 11.

22

Figure 10. Dimensions testbed.

Figure 11. Nuts in testbed to screwed operation.

200 cm

23

3.3 Subjects

Seventeen healthy subjects (eleven men and six women) with no recent injuries reported in the back

and upper body were involved in the development of the test experiments, with an average age of

24± 6 years, and an average height of 176 ± 9 cm. Between the seventeen participants, eight were

operators from Volvo Cars factory, seven students from Volvogymnasiet (Volvo School), and two

students from the University of Skövde. All of them were not familiar with the tasks and equipment

involved in the experiment as well as provided informed consent for the performance of it.

3.4 Task Description

The experiment involves the performance of three different tasks that have been designed to

investigate the impact of using exoskeletons in the range of motion of workers as well as the

exoskeleton’s versatility. The first and second tasks try to simulate the work done in the real factory,

and the third task focuses on the range of motion. They are described in more detail as follow:

1. The first task consists of performing several screwed taking the electric screwdriver and

screws from one of the sides of the testbed. The operator stands under the frame and turns

his/her back to the side where the tools are, keeping the legs in a static position for this first

movement, Figure 12a. After taking the tools, the participant performs the rest of the task

naturally.

2. The second task is basically equal to the first one with the difference of taking the

screwdriver the floor. In this case, the participant has to flex the back and legs, Figure 12b.

The rest of the task is developed naturally.

3. The third task consists of performing two different movements, first stretching of arms up

and down, followed for circles movements with the arms, Figure 12c.

24

Figure 12. Involved movements in the tasks (a. Rotation; b. Bending; c. Stretching).

The first and second task, based in workplace images observations, try to simulate the assembly

work at overhead position in the factory while considering possible difficulties like the need to take

tools from the floor after falling down during performing the manual task. Instead, the third

operation aims to see what are the limitations in the range of motion of the workers and the

exoskeleton making extreme or unusual movements in the work area like stretching or circle

movements with the arms. The participants received no specific instructions for the task execution in

order to keep the performance as close as possible to the real situations.

3.5 Apparatus and instrumentation

Three different models of exoskeletons have been provided by the company in collaboration for the

development of the experiment and have been studied in relation to the range of motion of workers

by wearing them. The three exoskeletons, described in section 2, are passive models, and their

functionality is based on a mechanical system like springs, they do not need to use an energy supply

what makes them also lightweight. They are worn similar to a backpack, close to the body with

attachments in the arms, low back and chest. They transfer help to the arms to raise and hold them up

easier, and in this way reduce the effort in the shoulder and neck region. Next, a comparison between

the three exoskeleton models as well as the used tools and instrumentation involved in the project,

are presented.

3.5.1 Comparison of exoskeletons

The three exoskeletons are different models of passive upper body system available in the market to

provide help to workers and reduce the effort during daily tasks. This have been the models used in

the development of the thesis and experiment since they have been the choose and provided models

a b c

25

by the company (Volvo Cars) to analyse. Table X and Figure 13 below shows the models as well as

the main characteristic of each of the exoskeletons.

Table 2. Comparison of exoskeleton models.

Model of Exoskeletons

EksoVest from Ekso Bionics Paexo from Ottobock MATE from Comau

Weight Approx. 4.3 kg Approx. 2 kg Approx. 4 kg

Lift Assistance 4 assistance levels

(2.2-6.8 kg per arm) Adjustable assistance 7 assistance levels

Height Range S-M-L sizes 152-193 cm 160-190 cm S/M and L/XL sizes

Figure 13. Comparison of exoskeletons (a. EksoVest; b. Paexo; c. MATE) (Image from a. (EksoVest, n.d.); b. (Paexo, n.d.); c. (Comau, n.d.))

3.5.2 Instrumentation: Xsens equipment

The Xsens MVN equipment is an inertial motion capture system, based upon miniature inertial

sensors, advanced multi-sensors fusion algorithms and wireless communication solutions combined

with biomechanical models. It is a completely portable system, which means no problem to choose

where to perform the recording of the experiment (“Xsens MVN User Manual,” 2018). However, the

limitation is established by the wireless range (10 m using the Awinda dongle and 50 m using the

Awinda station). The MVN system is able to measure and record kinematic data including segments,

joint angles, and centre of mass data. Also, it provides graphical output and makes possible to export

data to other software.

26

MVN Awinda has been the equipment used in the present project. It contains several sized shirts and

straps to adjust 17 wireless motion trackers (MTw) in the body (Paulich et al., n.d.; Schepers et al.,

n.d.), Figure 14.

Figure 14. Position of Xsens sensors in human body.

3.5.3 Tools

An electric screw drill (approx. 2kg) was the used tool in the performing of the task since it is the

main assembly operation in the real factory to study, Figure 15.

Figure 15. Tools: screwdriver and screws M12.

27

3.6 Procedure

The procedure of the experiment involves all the aforementioned sections. Figure 16 describes the

main steps of the development process.

After arriving at the experimental scenario placed in ASSAR, the study project and the experiment to

perform was briefed to the subjects. They were asked for informed consent to be recorded and

interviewed, and any question they might have related to the study development was also solved. The

first step was the setup of the Xsens MVN system, which consists of fitting the Xsens equipment, 17

sensors on the participants’ body with the help of straps to get the motion capture data (Figure 10),

subject’s body dimensions to define the anthropometric of the subjects in MVN software (Figure 12),

and sensor calibration. Segment calibration aligns the segments of the subject to the motion trackers;

a good calibration performance is essential to ensure accurate results (Xsens MVN User Manual,

2018). For that, the subject should stand in an initial pose (N-pose or T-pose) (Figure 12), and walk

back and forth. This alignment was done with each of the participants.

Figure 17. Body dimensions and initial positions for calibration (N-pose and T-pose)

Figure 16. Experimental procedure.

28

Once the system calibration was successful, the recordings could be done. The experiment consisted

of the execution of three different tasks, they are explained in section 5.4. Each of these operations

was performed four times with each of the subjects. The first performance of tasks was done without

using any of the exoskeletons models, just wearing the sensors of Xsens system, in that way the

subject got familiar with the operations and tools. After that, the performance of the tasks was carried

out with each of the exoskeletons models: EksoVest, Paexo, and MATE respectively. The order of

wearing the exoskeletons during the experiment was the aforementioned (first EksoVest, second

Paexo and third MATE) with all the subjects. Each of the exoskeletons was adjusted to suit the

subject’s bodily characteristics. The subjects started the tests in a standing position without the tool.

At the beginning of each task (task 1 and 2) first, subjects reach the tool and screws with different

movements (taking it from the side or from the floor) and then go on with the operations. The last

step consisted of interviewing the subjects after conducting the experiment with all the models of

exoskeletons, with a complete view of them and their differences. However, during the experiment’s

development, questions were also asked about the impressions when using each of the models. It was

instructed to the subjects execute the tasks naturally within the provided indications. All the

experimental trials were not only recorded with the motion capture system but also with a video

camera. The duration to perform the whole experiment was around 50-60 min per subject.

3.7 Data collection and analysis

An inductive approach is addressed in this study to evaluate the use of exoskeletons on workers’

range of motion. Qualitative and quantitative data have been analysed with the aim to see a

relationship between using exoskeletons and the range of motion of users (Burnard et al., 2008).

Observation, interviews and motion capture records (Xsens equipment) have been the tools to gather

information in the experiment performance. Observation of the experiment in life and video

recordings give a general but not accurate insight of the human behaviour with and without the

exoskeletons. The interviews constitute the main source of information since it comes directly from

the final intended user. Moreover, these interviews are essential to understand the quantitative data,

which is recorded with the motion capture system and collects accurate kinetics information.

The qualitative data consists of the observations and mainly on the interviews done after performing

the experiment. Semi-structured interviews were carried out once the subjects finished the

performance of the tasks with the three different models of exoskeletons and without them. The

questions were related to the performing of the specific drilling task, to the limitations on movements

29

taking the tool from the side or floor and during the task, main advantages and disadvantages, or

assistance support of each model. Some question examples are as follows:

- What do you think of each of the exoskeletons? Pros and cons? (Weight, comfortability,

adjustment, use in general)

- Which one do you think is the best one for overhead assembly operations? Why?

- Which one do you think is the best one related to the range of motion? Why?

The quantitative data analysis has consisted of analysing specific data from the motion capture

records from Xsens MVN system. The joint angles of both right and left shoulders have been studied

since they are the main affected area at overhead assembly operation, as it was described in the

literature review section. The motion capture records from Xsens provided three different movement

data of the shoulders (Abduction/Adduction, Internal/External Rotation and Flexion/Extension),

Figure 18 and Figure 19. A statistical study based on percentiles has been used to compare and

observe significant changes in the subjects’ range on motion with the different models of

exoskeletons during the performance of the experimental tasks. Percentiles are used for a large

number of observations and continuous probability distribution. It indicates the value below which to

a given percentage of observations in a group. With this method, it possible to see in what range the

shoulder joint angles spend more time, depending on the model of the exoskeleton. For task 1 and 2

flexion/extension is the movement studied and in the third task abduction/adduction, they have

chosen based on the task performance (section 5.4). The software used has been Excel (Microsoft

Office).

Figure 18. Basic shoulder movements. (Image from https://sequencewiz.org/2016/03/16/loosen-up-your-shoulders/)

30

Figure 19. Example of joint angle data by Xsens system.

31

4 Results

This chapter provides a summary of the main obtained results, which are divided into two different

parts depending on the type of analysis, qualitative and quantitative.

4.1 Qualitative results

Table 3 below shows the preference for the exoskeleton model (EksoVest, Paexo, and Mate) of each

subject involved in the experimental study. The table follows the colour criteria showed as follows.

Table 3. Colour criteria.

Criteria best option second option third option

The choice of the subjects was based on his/her personal impressions wearing each of the models,

which include mainly aspects as comfortability, limitation in the range of motion and assistance

support.

Table 4. Subject preferences of exoskeleton models.

Subjects EksoVest (Ekso

Bionics) Paexo (Ottobock) Mate (Comau)

Subject 1

Subject 2

Subject 3

Subject 4

Subject 5

Subject 6

Subject 7

Subject 8

Subject 9

Subject 10

Subject 11

Subject 12

Subject 13

Subject 14

Subject 15

Subject 16

Subject 17

Total

9 12 0

4 3 6

4 2 11

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On another hand, the next table describes the most repeated positive and negative aspects of each of

the models during the testing the exoskeletons in the performance of the tasks by the subjects (Table

4, 5 and 6).

Table 5. Positive and negative points: EksoVest.

EksoVest (EksoBionics)

Positive points Negative points

Assistance support Not flexibility in the back

Comfortability Back, shoulders and sides discomfort

Adjustment to arms Heavy

Clumsy feeling

Table 6. Positive and negative points: Paexo.

Paexo (Ottobock)


Comfortability Adjustment to the arms

No limitations in the range of motion Shoulders discomfort

Lightweight

Table 7. Positive and negative points: Mate.

Mate (Comau)


Earlier assistance support Limitations in the range of motion

Adjustments to the arms and lower back Back and shoulder discomfort

Heavy Limited support at overhead position Clumsy and stuck feeling

The EksoVest model has good assistance support and adjustment to the arms. Instead, it also

produced back, shoulder and sides discomfort. Heavy and clumsy were other of the most repeated

comments through the experiment's development. The Paexo exoskeleton was the favourite model

for most of the subjects, a textile material composition makes it the most lightweight of the three

involved models. Subjects expressed that it was the model better replicating the natural movement

and better fitting on the body. However, the adjustment to the arms was considered a negative point

by almost every subject. The last tested exoskeleton, Mate from Comau, was the model with more

negative valuation obtained. Although the assistance support started earlier and the adjustment in the

lower back and arms were qualified as the best of the three models, the design limits the range of

33

motion of workers, the movement, especially during task number three, was stuck. Moreover, it also

produced discomfort in the back as well as heavy and clumsy feelings.

Regarding the movements involved in the tasks to reach the tool at the beginning of each trial, no

problems were obtaining taking the tool from the side, in contrast, reaching the screw drill from the

floor was not that easy for all the subjects with the EksoVest and MATE exoskeletons, due to hip

pain consequence of the lower back adjustment and the devices' weight. On another hand, all the

subjects agree that the use of these devices helps at this specific overhead operation although

performing the experiment and tasks without any of the exoskeletons provided a full the range of

motion, and no stuck and clumsy feeling.

4.2 Quantitative results

The statistical analysis aims to observe changes in the movement behaviour or range of motion of the

participants. With a study based on percentiles, it is possible to observe the points distribution of a

data sample. In this case, the data sample is the angles of the right and left shoulder recorded with the

motion capture system. With this study, it is observed the angle distributions during the execution of

each task and each exoskeleton model. Following this line, it will possible to observe changes with

each model in the same tasks, what are the movement tend. If by wearing any of the models, this one

keeps the arms raised up longer time due to the assistance support, or instead, the movement and

tend is similar to the "optimal" or natural performance (without wearing an exoskeleton).

The obtained results through the statistical analysis based on percentiles for the first participant

involved in the experiment are shown in the next figures, rest of analysis results are shown in

Appendix 1. Series 1(green) corresponds to the first recordings of the experiment just wearing the

Xsens equipment without any of the exoskeletons, it is considered the “optimal” or natural

movement to follow and constitutes a reference to compare the rest of data. Series 2 (blue), Series 3

(grey) and Series 4 (yellow) correspond to the experimental recordings with the exoskeletons

EksoVest, Paexo and Mate respectively. The horizontal axis with the values 1-7 constitutes the

percentiles (P1, P5, P25, P50, P75, P95, and P99).

Figures 20 and 21 (task 1 and task 2) can be observed how the value of percentiles start raising from

P75 (5) to P99 (7) for series 1 (EksoVest), series 2 (Paexo) and series 3 (MATE), what means that

the movement registers a higher number of values at overhead position (higher number of flexion

angles). In other words, it could be said that the use of exoskeletons tends to keep the arms up due to

34

the assistance support in the development of the task for both shoulders. The change is more

significant with Mate exoskeleton model. EksoVest and Paexo instead describe values more similar

to the “optimal performance” without the exoskeleton.

Figure 20. Statistical analysis: Task 1

Figure 21. Statistical analysis: Task 2.

Figure 22. Statistical analysis: Task 3.

During task 3 (Figure 22), it can be observed that the percentiles increment from P25 (3) to P75 (5),

which correspond to the medium values, around 90º. The reason is that when performing the circular

35

movements, the participant took more time doing an effort to overcome the assistance support power

of the exoskeletons (around 90º flexion angle) and be able to put the arms back down.

5 Discussion

This chapter discusses the research results as well as the research process including research method,

and theoretical contributions and application.

5.1 Results

Quantitative results have shown that Paexo from Ottobock is the model with fewer changes respect

the natural movement (without exoskeleton) of the subjects according to the qualitative and

quantitative analysis. Nonetheless, both positive and negative aspects have been also registered when

using each of the models, and depending on the task, like Baltrusch et al., (2018) obtained in his

study. None of the models received a completely positive valuation. According to the subjects'

opinions, all of the models have something to improve.

Although Paexo model obtained the best assessment in relation to the range of motion, the

adjustment to the arms was a problem. Performing the task number three, when the subjects had to

stretch the arms up and down and make circular movements, the adjustment slipped to the forearm,

and therefore, the arms did not receive the assistance force anymore, Figure 23.

Figure 23. Arm adjustment Paexo.

Circular movements with arms are not a daily movement involved in a real assembly plant,

nevertheless, it is important to consider that the users are not able to stretch their arms up to avoid the

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adjustment moves. This problem directly affects the overhead position for every person, especially

shorter people, requiring to raise their arms more than 90 degrees to do the assembly operation.

Figure 24 below shows the different types of adjustments to the arms, it can be seen that EksoVest

and MATE use thicker straps than Paexo. By improving this adjustment Paexo exoskeleton would

not move to the forearm and the assistance support would be applied in the correct area all the time.

With respect to the adjustment in the lower back (Figure 25), models ElsoVest and Paexo share the

same design, in contrast, MATE model uses also a thicker strap that suits and feels more comfortable

on the subjects’ body.

Figure 24. Comparison adjustments to the arms (EksoVest, Paexo, and MATE).

Figure 25. Comparison adjustments to the lower back and chest (Paexo and MATE).

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EksoVest and MATE have a design and components heavier than Paexo, as it can be seen in Figure

26. By improving mainly this aspect the model would fit better on the users and might back,

shoulder, and sides discomfort would also be reduced on the users.

Figure 26. Comparison design exoskeletons model (EksoVest, Paexo and MATE).

Thinking about the current studied exoskeleton models, according to the results, it could be said that

the implementation of these systems would help to support the arms at overhead assembly

operations. Nonetheless, negative aspects of some of the models (EksoVest and MATE) got in the

results as lower back, shoulder and sides discomfort may suppose problems, and lead other types of

injuries. In addition, the clumsy and stuck feeling could also develop psychological damages if they

are present during long periods of time. That would mean that by implementing the exoskeletons

systems shoulder musculoskeletal disorders would be avoided but other injuries could be also

developed with the designed models so far.

5.2 Research Method

The research addressed in this thesis consists in evaluating how the use of exoskeletons affects the

range of motion of workers. Experiment with an inductive approach was the methodological strategy

addressed to develop this investigation. The different methods to gather and analyse the data as well

as the experimental development are discussed as follows.

5.2.1 Data Collection and Analysis

Interviews with the subjects have constituted the main source of data in this project. Taking notes

and video recordings have been the methods used to collect the result. It could be improved by using

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transcription methods or any ergonomic software like Timer Pro Professional (how it was thought to

do), however, due to the similarity in the results and the lack of time to analyse them, the used

approach was considered enough.

Data analysis consists of two different parts, qualitative is the main and direct information source

since it comes from the final targeted user, it gives the path to develop the quantitative analysis. The

quantitative analysis allows verify the obtained results from the subjects’ impressions as well as

observe in a numerical and accurate way the difference between performing the tasks with the three

different models. The motion capture system might also provide erroneous data as it can be seen in

some of the graphs (Figure 17, series 1), it is due to the proximity between sensors and contact

between different parts of the body. Statistical analysis based in percentiles has been the chosen way

to analyse the angles distributions during the task’ performances with the exoskeletons models and

compare the differences and tends between them. This type of study can indicate the work behaviour

of a group in a general way, and it has been used in other previous projects (Pascual et al., 2019).

Other statistical parameters as mean, or standard deviation to make more complete the study. On

another hand, it has not been possible to carry out the statistical study for all the subjects involved in

the experiment due to the time consuming of it.

5.2.2 Experiment

Both the experiment and the involved tasks were design to replicate the assembly operation and

conditions as realistic as possible to the factory. The tasks not only intended to simulate the assembly

operations but also included some movements that implicated to test the range of motion while

wearing the exoskeletons system. Another additional task could be also included in order to further

extend the study, however, it would increment the duration of the experiment over 50-60 minutes per

person, and also the analysis data process.

On another hand, more of the expected subjects were considered on the experiment. At first, the

expectation was to test it with 10 subjects, nevertheless, 17 people were finally involved, what was

positive due to the increment of the subjective information, the main source of data on the project but

it also supposed a larger time of analysis. Also, different unexpected problems came when

developing the experiment. A non-recognition hardware problem with the Xsens MVN software

during one of the tests did not allow recording the motion capture of one of the subjects, nonetheless,

the interview was done and considered in the qualitative data analysis. On another hand, the meeting

with some of the participants had to be changed several times due to last moment health problems

39

and unavailability. Another issue was that Xsens sensors (especially shoulder sensors) were moved

and fall from the users’ body when the exoskeletons were being changed, that made necessary the

calibration setup again and meant longer durations. It was solved fixing the sensors with some tape

to the users’ body.

Another problem was not randomizing the wearing of exoskeletons on the subjects during the

experiment. It was used always the same order: first EksoVest, followed by Paexo, and MATE

exoskeletons, in order to keep an organized sequence of steps. However, this sequence may lead to

erroneous subjective data. One example of it would be that conducting always the same order of

exoskeletons makes the subjects perform always the last trial with MATE exoskeleton when they

might be a bit more tired, consequently, the impressions and feelings regarding the last exoskeleton

could change negatively. Considering the random use of the exoskeleton models in the experimental

process would have guaranteed better subjective results.

5.3 Theoretical contribution

Numerous exoskeletons are already available to commercialize and introduce into the industry

(Looze et al., 2016), although investigations so far may have not evaluated all their possible effects.

Most studies focus on examining the muscle activity changes of muscle groups that are intended to

be supported by these exoskeletons devices (Huysamen et al., 2018; Looze et al., 2016). Positive

results are obtained since the objective of exoskeletons is to reduce the loading effort of the worker.

However, there are not many articles approaching the negative aspects like postural changes,

limitations in the range of motion, or biomechanical load shift to other muscles (Baltrusch et al.,

2018; Ulrey and Fathallah, 2013b, 2013a). The present study evaluates how the use of exoskeletons

affect the range of motion of worker. EksoVest, Paexo, and Mate exoskeletons are the models

involved in the experiment, and these are three examples of models of exoskeletons that are already

being tested in real industrial factories. The qualitative results presented in this thesis can be

considered as a theoretical contribution for both companies interested in the product (for example

automation industry) and the exoskeletons’ companies itself. The results extend the exoskeletons

knowledge concerning the main strengths and weaknesses (positive and negative aspects) in the

design affecting the workers’ movement. They can be considered in order to improve, and therefore,

achieve better performing.

40

5.4 Application

During the experiment, subjects were also asked about the activation zone wearing the three

exoskeletons, it is the area where the exoskeleton starts providing support to operators’ arms by the

mechanical system or springs, it differs depending on the user. EksoVest has three different

activation zone settings (low, standard during the experiment, and high), unlike Paexo and Mate that

do not have. Figure 27 shows the registered activation zones results of the subjects with the

exoskeletons: EksoVest and Paexo around 60-90º and Mate exoskeleton quite earlier, from 15-25º

the supported from the springs was experienced. That means companies could not only consider

these systems to cover overhead operations but also “in-front” (around 90º or superior), as it can be

seen in Figure 28.

Figure 27. Activation zones.

Paexo

Mate

EksoVest

41

Figure 28. In-front assembly operations.

Taking a deeper step in the implementation of exoskeletons for this specific task, it would be

necessary to reflect if even improving the models that are currently on the market, the use of these

devices would be a valid option to solve the problem of musculoskeletal injuries, since the position

itself is still equally harmful (Dahmen and Hefferle, 2018). This might constitute a "band-aid" to the

problem or a cheap alternative to a real solution, as it would be for instance changing the

organization in the assembly line or implement machinery that would allow the operation to be

carried out in a more ergonomic vertical position. However, it is not always possible for reasons of

budget or others. In these cases, it is important that companies still consider the implementation of

devices that helps to reduce injuries and improve the workers' conditions, although they may be not

the best solution.

In addition to this, it is also important to consider the expected life time and retirement age is and

will increase, what means higher degree of elderly people at factories and among the future working

force (Middlesworth, 2016). Considering the aforementioned fact, to have safer workstations gets

even more importance for companies since older workers experience loss in their physical and

physiological capabilities, what put them in a higher risk level to develop musculoskeletal disorders

or other types of injuries. At this point, the use of exoskeletons could be seen as a useful method to

help this sector of workers, however, improvements in the design should be really necessary to

ensure greater versatility in the models. To add more movements limitations from the exoskeletons

to the range of motion of older workers that could be already affected by the aging, would suppose a

problem and not a solution (Bryant et al., 2018; Milanović et al., 2013).

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6 Conclusion

The present study has shown a comparison of how the use of three different models of exoskeletons

affects the range of motion of workers at overhead assembly operations but also from a general view.

Paexo exoskeleton from Ottobock company has been the preferred model for most of the subjects

involved in the study due to its lightweight and simple design, followed by EksoVest from

EksoBionics and MATE model from Comau. Although exoskeletons showed discomfort or adverse

effects on tasks requiring a larger range of motion like lifting from the floor or stretching, all

participants involved in the project agree with the idea of exoskeletons devices help at overhead

operation. Nevertheless, none of the models obtained a complete positive valuation. Statistical

analysis had shown how the exoskeletons vary the movement of arms (flexion/extension) tending to

keep them up when performing overhead tasks due to the assistance support of these exoskeletons

devices.

This project focussed on simulating the use of a device at a working place example. The design and

construction of the testbed in which the experiment was carried out were successful and followed the

characteristics of the real scenario at the factories. Due to the recent interest and development of

these exoskeleton systems, each combination of exoskeleton and workplace requires an individual

analysis to determine its impact (Theurel et al., 2018). So far this approach is time-consuming but

required due to the lack of information; a holistic system approach to evaluating the use of

exoskeletons, including muscle activity not only of a particular musculoskeletal joint (shoulders) but

also considering other parameters as the range of motion, could be base to determine in a holistic

way the general impact of them.

Considering all the aforementioned, the results presented in this project are specific to the

exoskeletons involved (EksoVest, Paexo and MATE) and the workplace conditions tested. Similar to

Baltrusch et al., (2018) study results, it can be concluded that exoskeletons can obtain positive results

mainly for industrial applications and in working environments, for specifics type of operations such

as overhead assembly. Nonetheless, there are still important limitations in the range of motion when

using these systems. According to the negative registered aspects during the experiment, it is also

important to reflex about the possibility of developing a new type of injuries through the

implementation of the tested exoskeletons. Improvements in design aspects for each of the models

would increase their comfortability, versatility, and therefore, applicability not only for a wider

number of users but also in more work settings.

43

7 Future Work

To perform the statistical analysis for the rest of the subjects would constitute the first future work

step of the present thesis, the work behaviour of each participant will be verified to their subjects’

opinions, and in this way it may be concluded stating a general relationship between the use of

exoskeletons and range of motion of workers. In addition, other parameters recorded by the motion

capture system could be also analysed (velocity, acceleration of any involved joint, duration of tasks,

and so on) in order to make more complete the study and get a wider knowledge of how exoskeletons

affect the range of motion at overhead assembly operations.

On another hand, to be able to know if exoskeletons are a suitable investment for companies helping

the workers, more investigations and case studies, with the holistic approach if possible, required to

be carried out within the organization. One example of possible future work could by the gradual

implementation in a long period view of the system at the factory, for a specific assembly task as

overhead operation, and for specifics participants. In that way, it could be analysed the possible

benefits and harms. However, as future work also could cover the investigation of alternatives to this

kind of operations at the automotive industry.

44

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Appendix A: Statistical Analysis

This Appedix shows the statistical analysis based on percentiles for some of the subjects involved in

the project.

7.1 Subject 2

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evaluation of the use of exoskeletons in the range of motion of...

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