The aim of this research is to optimize current system and analizing big data using machine learning to facilitate the accurate classification of the hand gestures using all incorporated biomechanical sensors and electromyography (EMG) signals. We have developed advanced technological solution (SmartGlove) to capture big database for majority of biometrics information related to the hand gestures. The aim of this study is to collect a complete anatomical data-set of the hand and wrist, including the intrinsic and extrinsic muscles. Currently, no consistent data-set exists comprising the full anatomy of these upper extremity parts. ![]() In our research, we will capture combination of both biomechanical and neurophysiological parameters of hand. ![]() are correlated with electro-mascular signals. ![]() The dynamic biometrics information of Hand/Wrist movements such moving finger, hand, applying force and etc.
0 Comments
Leave a Reply. |