Chuchart Pintavirooj
Papers
2
Total Citations
11
H-Index
2
About
Chuchart Pintavirooj is a biomedical engineer whose research centers on electromyography (EMG) signal processing, prosthetic control, and human-machine interfaces. His major contributions lie in developing accurate, low-cost methods for classifying muscular contractions to control robotic prostheses and assistive devices. In his most cited work, “An accurate forearm EMG signal classification method using two‐channel electrode” (2013, 8 citations), he introduced a novel algorithm using independent component analysis (ICA) for blind-source separation of EMG signals, enabling a virtual hand prosthesis with 12 degrees of freedom from just two surface electrodes—a significant step toward practical, non-invasive prosthetic control. Earlier, in “Robotic arm controller using muscular contraction classification based on independent component analysis” (2008, 3 citations), he demonstrated a multi-channel EMG acquisition system built on a low-cost programmable system-on-chip (PSOC) microcontroller, using an array of inexpensive EKG electrodes and B-spline interpolation to classify muscle activity for robotic arm control. Pintavirooj’s work emphasizes accessibility and real-world applicability, making advanced prosthetic control more affordable and deployable. His research continues to influence the fields of rehabilitation engineering and biosignal processing, offering promising pathways for next-generation assistive technologies.
Research Focus
Key Achievements
Top Papers
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