Advanced wearable biomedical systems through the development of an ASIC for real-time EMG-based gesture recognition.
The proposed framework integrates signal acquisition, preprocessing, feature extraction, and CNN-based classification for efficient hardware implementation, enabling low-power wearable interfaces for hands-free control, assistive technologies, and AR/VR applications.
Faculty: Debayan Das
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