Dr. Angkoon Phinyomark

The human body is a biomechanical structure that is made up of three systems: muscular system, skeletal system and neural system. These three systems (the so-called "Neuro-Musculo-Skeletal System'') are profoundly interconnected and a change in one system affects other two systems. Unfortunately, researchers often study human body systems and develop related computing technologies in relative isolation. To develop the ability to conduct  research on these three major systems together, my academic career has taken me on a journey. Since 2009, I have developed an H-index of 44 (i10-index of 80) and my 129 published refereed journals, book chapters, conference proceedings, abstracts, and invited talks have been cited 8516 times. Forty-six papers have been published in ISI indexed journals (25 as the first author).

During my undergraduate studies, I participated in an internship at the Faculty of Computer Sciences, University of Murcia, Spain (2007). After completing my Bachelor's degree, with First Class Honors in Computer Engineering (computer networks and software engineering) at Prince of Songkla University, Thailand (June 2004-February 2008), I pursued my PhD in Electrical Engineering with special emphasis on signal processing and pattern recognition (June 2008-April 2012). My collective dissertation research also received the "Best PhD Thesis Award" from the National Research Council of Thailand.

My PhD research was focused on the muscular system and developing algorithms to accurately classify upper-extremity movement patterns from electromyographic (EMG) patterns. These patterns can be used as information sources for the control of multifunctional assistive and rehabilitative devices referred to as "Myoelectric Control" systems or "muscle-computer interfaces". During the final year of my PhD studies (2011-2012), at the University of Essex, in the UK, and during my first postdoctoral training (2012-2013), at Université Grenoble Alpes, France, I began to focus my research on improving the robustness and generalization ability of these systems. This work focused not only on developing the algorithms under laboratory well-controlled conditions, but also to address and validate the assumptions with regard to user behavior in real world contexts.

The muscular system together with the skeletal system form the musculoskeletal system which is responsible for movement of the human body. To expand my knowledge and experience with the musculo-skeletal system, my second postdoctoral research position (2013-2016) at the University of Calgary, Canada, was aimed at advanced machine learning approaches, involving thousands of runners and walkers, to detect both major and subtle changes in "Gait Biomechanics" for the purpose of injury prevention and optimal rehabilitation. These two systems, however, are controlled through the nervous system. Therefore, a study of the brain and nervous system (so-called "Neuroscience") is necessary. As a researcher (2016-2017) at ISI Foundation, Italy, my research was aimed at a set of techniques rooted in algebraic topology, collectively referred to as topological data analysis (TDA), to study human brain functional connectivity in neurodegenerative diseases.

I am currently a Senior Research Scientist at the Institute of Biomedical Engineering at the University of New Brunswick, Fredericton, NB, Canada (Sep 2019-Present; postdoctoral fellow, 2017-2019) under the supervision of Dr. Erik Scheme. more (about me)

Based on my research expertise, I have served as an Invited Reviewer for 54 different peer-reviewed journals in ISI Web of Science over the past 9 years. In total, I have reviewed more than 145 manuscripts, which were related to my area of research expertise. I am currently an Associate Editor at IRBM (Innovation and Research in BioMedical engineering), an ISI indexed journal. I also have a number of computer programming language certificates, i.e., Sun Certified Programmer for the Java 2 Platform 1.4 (SCJP), Microsoft Certified Professional Developer, Web Developer (MCPD), and Microsoft Certified Technology Specialist, .NET Framework 2.0 Web (MCTS).  more (professional activities)

Current Project : Floor Sensor-based Gait Recognition / Footstep Recognition

News & Highlights

Highly Cited Articles

Review Articles / Surveys

Feature Reduction and Selection for EMG Signal Classification

Expert Systems with Applications (IF2018: 4.292)

(IF2018: 1.122) in ISI Web of Science (among 386 articles)

Application of Wavelet Analysis in EMG Feature Extraction for Pattern Classification

(IF2018: 0.684) in ISI Web of Science (among 1977 articles)

Feature Extraction and Reduction of Wavelet Transform Coefficients for EMG Pattern Classification