Posts Tagged gesture recognition
[ARTICLE] FarMyo: A Serious Game for Hand and Wrist Rehabilitation Using a Low-Cost Electromyography Device – Full Text PDF
One of the strategies used in recent years to increase the commitment and motivation of patients undergoing rehabilitation is the use of graphical systems, such as virtual environments and serious games. In addition to contributing to the motivation, these systems can simulate real life activities and provide means to measure and assess user performance. The use of natural interaction devices, originally conceived for the game market, has allowed the development of low cost and minimally invasive rehabilitation systems. With the advent of natural interaction devices based on electromyography, the user’s electromyographic data can also be used to build these systems. This paper shows the development of a serious game focused on aiding the rehabilitation process of patients with hand motor problems, targeting to solve problems related to cost, adaptability and patient motivation in this type of application. The game uses an electromyography device to recognize the gestures being performed by the user. A gesture recognition system was developed to detect new gestures, complementing the device’s own recognition system, which is responsible for interpreting the signals. An initial evaluation of the game was conducted with professional physiotherapists.
[Abstract] Gesture Interaction and Augmented Reality based Hand Rehabilitation Supplementary System – IEEE Conference Publication
[ARTICLE] Modeling Based on Computational Intelligence for Physiotherapeutic Rehabilitation Games – Full Text PDF
Over the last years, the use of computational environments, like serious games, has been one of the strategies to improve commitment and motivation of patients undergoing rehabilitation. Beyond providing motivation, these systems are able to simulate life activities and provide means to automatically monitor users interactions, assuring that the patient is performing the exercises correctly, thus allowing the user to perform the exercises without the need of constant monitoring by a health professional. The aim of this work is to develop a modeling for construction of serious games, whose interaction is given by gestures performed by hand and wrist. The model includes an automatic continuous evaluation of rehabilitation exercises executed by the patient and dynamic game balancing using computational intelligence methods.