Descripció del projecte

The dynamic biometrics information of Hand/Wrist movements such moving finger, hand, applying force and etc. are correlated with electro-mascular signals. In our research, we will capture combination of both biomechanical and neurophysiological parameters of hand. Currently, no consistent data-set exists comprising the full anatomy of these upper extremity parts. The aim of this study is to collect a complete anatomical data-set of the hand and wrist, including the intrinsic and extrinsic muscles. 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 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. Optimize back-end and develop application layer using Artificial Intelligence/Deep Learning solutions to capture and analyze data and predict hand biometric responses to user, and will be able to predict possible risks for hand injuries or provide optimized therapy combination of beneficial for each patient, improving personalized treatments.

Use machine learning, network analysis and modern technologies to analyze already acquired biometric and EMG data. Classification and Recognizing of the hand gestures using combination of biometric and EMG data.



MÉS INFORMACIÓ

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