Posts Tagged gesture recognition

[Abstract] Gesture Interaction and Augmented Reality based Hand Rehabilitation Supplementary System – IEEE Conference Publication


The existing systems of hand rehabilitation always design different rehabilitation medical apparatus and systems according to the patients’ needs. This kind of system always contain problems such as complexity, using only single training programs, inconvenient to wear and high cost. For these reasons, this paper uses gesture recognition technology and augmented reality technology to design a simple and interactive hand rehabilitation supplementary system. The system uses a low-cost, non-contact device named Leap Motion as the input device, and Unity3D as the development engine, realizing three functional modules: conventional training, AR game training and auxiliary functions. This rehabilitation training project with different levels of difficulty increases the fun and challenge of the rehabilitation process. Users can use the system to assist the treatment activity of hand rehabilitation anytime and anywhere. The system, which has good application value, can also be used in other physical rehabilitation fields.

via Gesture Interaction and Augmented Reality based Hand Rehabilitation Supplementary System – IEEE Conference Publication

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[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.

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