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About

Pornchai Phukpattaranont is a biomedical engineering researcher whose work spans biosignal processing, human-computer interfaces, and rehabilitation robotics. His research centers on extracting meaningful information from electrophysiological signals—particularly surface electromyography (sEMG) and electrooculography (EOG)—to bridge the gap between human intention and machine response. His most influential contributions include pioneering work on EOG-based human-computer interfaces, which has garnered 50 citations, and advancing wavelet transform techniques for sEMG noise reduction, cited 39 times. These foundational studies established robust signal processing frameworks that continue to inform the field. More recently, Phukpattaranont has extended his expertise into rehabilitation robotics, developing innovative systems that combine EMG signals with intelligent control strategies. His work on autonomous adaptive resistance generation using Fuzzy-PI control and Gaussian Process Regression for real-time force estimation represents a significant step toward more natural, therapist-like robotic rehabilitation for stroke patients. Across his career, Phukpattaranont has demonstrated a consistent commitment to translating sophisticated signal processing methods into practical clinical and assistive technology applications, making his research particularly valuable for students and practitioners working at the intersection of biomedical engineering and human-machine interaction.