Quantitative EEG (QEEG) Quantitative electroencephalogram (QEEG) has become an important technique for psychophysiological assessment of brain disorders. This QEEG course enables the extraordinary potential of QEEG analysis to be fully exploited and guides the clinician/researcher toward a powerful analytic system in Quantitative Analysis that moves beyond the identification of simple statistical deviance.

Expert team of QEEG researchers will teach the fundamental tools used

in EEG analysis including reading and de-artifacting of the EEG record,

montages, topographic aspects and comparison with normalized EEG

data, frequency and wavelet analysis and others. Furthermore, the team

will expand the possibilities of brain analysis towards neural networks

and explain the brain functional and effective connectivity and their

potential roles in studying the changes in brain connections due various

brain disorders, like stress, anxiety, alcoholism and epileptic seizures.

Neurofeedback Neurofeedback uses real-time digital technology to measure electrical activity of the brain (EEG) and present this information in a form that enables an individual to perceive changes in the state of the brain and learn to modify abnormal EEG patterns. Neurofeedback has been shown to be effective in the treatment of ADHD, seizure disorders, anxiety (e.g., obsessive-compulsive disorder, generalized anxiety disorder, post-traumatic stress disorder, and phobias), depression, reading disabilities, and addictive disorders. Expert team in neurofeedback training and development will encompass the fundamentals of neurofeedback and its protocols. The course will cover the details on selecting the protocols and stimulus contents for different neurofeedback applications.

Upon completion of this course, participants will

be able to:

Record and clean EEG signals from artifacts. Analyse EEG signals in time, frequency

and time-frequency domains. Use the topographic maps and functional

and effective connectivity in brain analysis.

Apply various Neurofeedback montages and protocols and use QEEG to optimize the brain training process.

EEG Principals and Foundations Univariable-based QEEG Analysis

Bivariable-based QEEG Analysis Granger Causality and Brain’s Effective Connectivity Brain Maps Analysis and z-score

Neurofeedback Training from Theory to Practices NF Advancements and Hands-on Experience

CENTER FOR INTELLIGENT SIGNAL & IMAGING RESEARCH (NATIONAL HiCOE FOR BRAIN IMAGING, UNDER MINISTRY

OF EDUCATION, MALAYSIA) PRESENTS

Brain signals’ researchers

Biomedical Students

Medical Doctors

Neurofeedback therapists

Practitioners and Clinicians

AP. Dr. Nidal Kamel received his PhD degree

(Hons) from the Technical University of Gdansk,

Poland, in 1993. Since 1993 he has been involved

in research projects related to estimation theory,

noise reduction, optimal filtering, and pattern

recognition.

He developed single-trial subspace-based technique for ERP

extraction from brain background noise, time-constraints

optimization technique for speckle noise reduction in SAR

images, and introduced data glove for online signature

verification. His present research interest is mainly in EEG signal

processing for localization of brain sources, assessment of

cognitive and visual distraction, Neurofeedback, learning and

memory recall, as well as fMRI- EEG data fusion. He has been the

editor of EEG/ERP Analysis: Methods and Applications, CRC

Press, NY, 2015 and co-author of Brain Source Localization Using

EEG Signal Analysis, Taylor and Francis, Ny, 2018.

AP. Dr. Syed Saad Azhar Ali received the

B.E. degree in electrical engineering from NED

University, Karachi, Pakistan, and the master’s and

doctoral degrees in nonlinear control from the

King Fahd University of Petroleum & Minerals. He

was with Air University and Iqra University prior

to being engaged as Associate Professor with the Center of

Intelligent Signal and Imaging Research, Universiti Teknologi

PETRONAS. Recently, he has been involved in neurosignal

processing. He has authored over 70 peer- reviewed

publications, including four books/chapters. His research focus

has been on intelligent control, signal processing, underwater

robotics with the emphasis on image enhancement and 3-D scene

reconstruction. He is the PI for several funded research projects.

RM 2,040 (Professionals) - 2 days RM 2,600 (Professionals) - 3 days 10% Discount (UTP Alumni,

PETRONAS & Group Registration) 20% Discount (Student) Course fee is not inclusive of 6% SST.

Group registration is applicable for 3 pax

and above from the same company.

The fees include refreshments and the

course materials.

A certificate of attendance will be issued

Course Coordinator: Assoc. Prof. Dr. Nidal Kamel

Tel: +605-368 7871 Email: nidalkamel@utp.edu.my

Course Registration: Mr. Farhan Zulkefly Tel: +603-2276 0136 / +60143150602 Email: farhan.zulkefly@utp.edu.my

Email cape@utp.edu.my for registration by 14th October 2019.

Seats are limited. A seat will be confirmed once the payment / LOU

is received. Confirmed participants will be informed via email.