Human motion modeling and evaluation using wearable sensor devices



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Wearable sensors devices are getting integrated into our daily life. Giving precise and accurate data on individual's exercises and practices are one of the most important tasks in extensive computing. These sensor devices provide a range of applications for development like entertainment, medical, security and tactical scenarios. Even though current research provides a variety of techniques for recognizing gesture movement, there are still key aspects that need to be addressed for recognizing human activities. In this research, we propose a technique that has not only provide a gesture movement recognition but also calculate the accuracy percentage with which the patient or subject is going to do the gesture movement with respect to the accurate model. In this process, we first receive the raw sensor data that are subjected to the preprocessing and feature extraction techniques prior sending these data to calculate the accuracy percentage. The final data that are obtained by passing through activity detection algorithm and accuracy calculation technique is then transferred to the cloud, where physiotherapist or specialist will analyze these data and provide the required feedback to the patient or subject.