The Virtual Trainer: Supervising Movements Through a Wearable Wireless Sensor Network

Recent technological advances in integrated circuits, wireless communications, and physiological sensing have boosted the development of miniaturized, lightweight, ultra-low power, intelligent monitoring devices. A number of these devices can be integrated to form a wireless body area network (WBAN), a wireless sensor network whose devices, called motes, are positioned on the body of a person to monitor biometric parameters and vital signs. To this extent, the latest advances in mircoelectro mechanical systems (MEMS) technology have opened up the opportunity to realize miniaturized accelerometers, a sensing element that measures acceleration. The aim of the presented work is to showcase an integrated system to monitor execution of fitness and rehabilitation exercises and to provide a feedback to the user in order to correct errors and avoid hurts. The focus of our work is to analyze a simple fitness exercise like biceps curl by using a network of wireless sensors equipped with two-axes accelerometers. The sensed data from the acceleromenters is delivered to a PC which runs a graphical interface and a movement analyzer which returns in real-time the "goodness" of the performed exercise. Moreover, the analyzer also generates a more accurate analysis of the exercise which is returned to the user upon completion of the movement.