The Cognitive Motivation-based APBMR Algorithm in Physical Rehabilitation

Guzsvinecz, Tibor and Szücs, Veronika and Magyar, Attila (2022) The Cognitive Motivation-based APBMR Algorithm in Physical Rehabilitation. ACTA POLYTECHNICA HUNGARICA. ISSN 1785-8860 (Submitted)

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Abstract

This article presents a new, alternative method of gesture recognition using the cognitive properties of intelligent decision-making systems to support the rehabilitation process of people with disabilities: the Asynchronous Prediction-Based Movement Recognition (APBMR) algorithm. The algorithm “predicts” the next movement of the user by evaluating the previous three with the goal to maintain motivation. Based on the prediction, it creates acceptance domains and decides whether the next user-input gesture can be considered the same movement. For this, the APBMR algorithm uses six mean techniques: the Arithmetic, Geometric, Harmonic, Contrahamonic, Quadratic and the Cubic ones. The purpose of this article besides presenting this new method is to evaluate which mean technique to use with the three different acceptance domains. The authors evaluated the algorithm in real-time using a general and an advanced computer, as well as they tested it by predicting from a file and also compared the algorithm to one of their earlier works. The tests were done by four groups of users, respectively, each group doing four gestures. After analyzing the results, the authors concluded that the Contraharmonic mean technique gives the best average gesture acceptance rates in the ±0.05 m and ±0.1 m acceptance domains, while the Arithmetic mean technique provides the best average gesture acceptance rate in the ±0.15 m acceptance domain when using the APBMR algorithm.

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