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Angkoon Phinyomark

Angkoon Phinyomark

D-Index & Metrics

Engineering and Technology

D-Index
41
Citations
8087
World Ranking
6864
National Ranking
280

Overview

Angkoon Phinyomark is affiliated with the University of New Brunswick in Canada and has contributed extensively to the fields of engineering and neuroscience, with a focus on biomedical engineering and cognitive neuroscience. Their research spans multiple interconnected domains, including muscle activation and electromyography studies, EEG and brain-computer interfaces, advanced sensor and energy harvesting materials, neuroscience and neural engineering, diabetic foot ulcer assessment and management, advanced chemical sensor technologies, and gait recognition and analysis.

Their recent scholarly publications highlight a diverse research agenda. Notable papers include:

  • Current Trends and Confounding Factors in Myoelectric Control: Limb Position and Contraction Intensity (2020), published in Sensors
  • Electromyography-Based Gesture Recognition: Is It Time to Change Focus From the Forearm to the Wrist? (2020), published in IEEE Transactions on Industrial Informatics
  • Unsupervised Domain Adversarial Self-Calibration for Electromyography-Based Gesture Recognition (2020), published in IEEE Access
  • Fractal Analysis of Human Gait Variability via Stride Interval Time Series (2020), published in Frontiers in Physiology
  • A Transferable Adaptive Domain Adversarial Neural Network for Virtual Reality Augmented EMG-Based Gesture Recognition (2021), published in IEEE Transactions on Neural Systems and Rehabilitation Engineering

Phinyomark's collaborations include frequent co-authors such as Erik Scheme, Robyn Larracy, Evan Campbell, Fady S. Botros, and Eve MacDonald, reflecting an active engagement with peers in their research community.

Their publications are predominantly featured in journals and venues including IEEE Access, arXiv (Cornell University), the 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), the Journal of Clinical Oncology, and Sensors.

The scope of Phinyomark's work focuses largely on advancing biomedical understanding and applications, particularly in muscle activation through electromyography and exploring brain-computer interfaces. Their involvement in topics such as gait recognition and diabetic foot ulcer assessment illustrates the interdisciplinary nature of their research, bridging engineering principles with clinical and physiological applications.

Best Publications

  • Feature reduction and selection for EMG signal classification

    Angkoon Phinyomark;Pornchai Phukpattaranont;Chusak Limsakul

  • EMG feature evaluation for improving myoelectric pattern recognition robustness

    Angkoon Phinyomark;Franck Quaine;Sylvie Charbonnier;Christine Serviere

  • The Usefulness of Mean and Median Frequencies in Electromyography Analysis

    Angkoon Phinyomark;Sirinee Thongpanja;Huosheng Hu;Pornchai Phukpattaranont

  • Feature Extraction and Selection for Myoelectric Control Based on Wearable EMG Sensors.

    Angkoon Phinyomark;Rami N. Khushaba;Erik J. Scheme

  • Application of Wavelet Analysis in EMG Feature Extraction for Pattern Classification

    A. Phinyomark;C. Limsakul;P. Phukpattaranont

  • EMG Pattern Recognition in the Era of Big Data and Deep Learning

    Angkoon Phinyomark;Erik J. Scheme

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

    A. Phinyomark;A. Nuidod;P. Phukpattaranont;C. Limsakul

  • Mean and Median Frequency of EMG Signal to Determine Muscle Force based on Time-Dependent Power Spectrum

    S. Thongpanja;A. Phinyomark;P. Phukpattaranont;C. Limsakul

  • Analysis of Big Data in Gait Biomechanics: Current Trends and Future Directions

    Angkoon Phinyomark;Angkoon Phinyomark;Giovanni Petri;Esther Ibáñez-Marcelo;Sean T. Osis

  • Interpreting Deep Learning Features for Myoelectric Control: A Comparison With Handcrafted Features.

    Ulysse Côté-Allard;Evan Campbell;Angkoon Phinyomark;François Laviolette

  • A Novel Feature Extraction for Robust EMG Pattern Recognition

    Angkoon Phinyomark;Chusak Limsakul;Pornchai Phukpattaranont

  • Evaluation of EMG feature extraction for hand movement recognition based on Euclidean distance and standard deviation

    A. Phinyomark;S. Hirunviriya;C. Limsakul;P. Phukpattaranont

  • Gender differences in gait kinematics for patients with knee osteoarthritis

    Angkoon Phinyomark;Sean T. Osis;Blayne A. Hettinga;Dylan Kobsar

  • Feature extraction of the first difference of EMG time series for EMG pattern recognition

    Angkoon Phinyomark;Franck Quaine;Sylvie Charbonnier;Christine Serviere

  • Current Trends and Confounding Factors in Myoelectric Control: Limb Position and Contraction Intensity.

    Evan Campbell;Angkoon Phinyomark;Erik J. Scheme

  • Fractal analysis features for weak and single-channel upper-limb EMG signals

    Angkoon Phinyomark;Pornchai Phukpattaranont;Chusak Limsakul

  • Electromyography-Based Gesture Recognition: Is It Time to Change Focus From the Forearm to the Wrist?

    Fady S. Botros;Angkoon Phinyomark;Erik J. Scheme

  • An optimal wavelet function based on wavelet denoising for multifunction myoelectric control

    A. Phinyomark;C. Limsakul;P. Phukpattaranont

  • Gender and age-related differences in bilateral lower extremity mechanics during treadmill running.

    Angkoon Phinyomark;Blayne A. Hettinga;Sean T. Osis;Reed Ferber

  • Kinematic gait patterns in healthy runners: A hierarchical cluster analysis.

    Angkoon Phinyomark;Sean Osis;Blayne A. Hettinga;Reed Ferber

  • A Review of Control Methods for Electric Power Wheelchairs Based on Electromyography Signals with Special Emphasis on Pattern Recognition

    Angkoon Phinyomark;Pornchai Phukpattaranont;Chusak Limsakul

  • Surface Electromyography (EMG) Signal Processing, Classification, and Practical Considerations

    Angkoon Phinyomark;Evan Campbell;Erik Scheme

  • Gender differences in gait kinematics in runners with iliotibial band syndrome

    A. Phinyomark;S. Osis;B. A. Hettinga;R. Leigh

  • A Comparative Study of Wavelet Denoising for Multifunction Myoelectric Control

    Angkoon Phinyomark;Chusak Limsakul;Pornchai Phukpattaranont

  • Probability Density Functions of Stationary Surface EMG Signals in Noisy Environments

    Sirinee Thongpanja;Angkoon Phinyomark;Franck Quaine;Yann Laurillau

Frequent Co-Authors

Erik Scheme
Erik Scheme University of New Brunswick
François Laviolette
François Laviolette Université Laval
Huosheng Hu
Huosheng Hu University of Essex

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