Abstract
In recent years, we have witnessed a growing adoption of serious games in telerehabilitation by taking advantage of advanced multimedia technologies such as motion capture and virtual reality devices. Current serious game solutions for telerehabilitation suffer form lack of personalization and adaptiveness to patients’ needs and performance. This paper introduces “RehaBot”, a framework for adaptive generation of personalized serious games in the context of remote rehabilitation, using 3D motion tracking and virtual reality environments. A personalized and versatile gaming platform with embedded virtual assistants, called “Rehab bots”, is created. Utilizing these rehab bots, all workout session scenes will include a guide with various sets of motions to direct patients towards performing the prescribed exercises correctly. Furthermore, the rehab bots employ a robust technique to adjust the workout difficulty level in real-time to match the patients’ performance. This technique correlates and matches the patterns of the precalculated motions with patients’ motions to produce a highly engaging gamified workout experience. Moreover, multimodal insights are passed to the users pointing out the joints that did not perform as anticipated along with suggestions to improve the current performance. A clinical study was conducted on patients dealing with chronic neck pain to prove the usability and effectiveness of our adjunctive online physiotherapy solution. Ten participants used the serious gaming platform, while four participants performed the traditional procedure with an active program for neck pain relief, for two weeks (10 min, 10 sessions/2 weeks). Feasibility and user experience measures were collected, and the results of experiments show that patients found our game-based adaptive solution engaging and effective, and most of them could achieve high accuracy in performing the personalized prescribed therapies.
Highlights
As of late, the challenge of designing a highly engaging serious game has been a subject of interest to various fields including training, simulation, healthcare, and education, among others.the direction towards creating a home-based individualized training plan for patients diagnosed with mental and/or physical disorders has attracted more interest due to the recent advancesSensors 2020, 20, 7037; doi:10.3390/s20247037 www.mdpi.com/journal/sensorsSensors 2020, 20, 7037 of technologies and techniques related to gamified telerehabilitation
We introduce the “RehaBot” system to overcome the challenges presented by the traditional therapy solutions, and it differs from existing work in many ways: (i) RehaBot is comprehensive in that it was not designed for rehabilitating specific body parts, but rather it accepts various therapies to cover the whole body; (ii) in addition, RehaBot embeds virtual assistants to direct patients to perform the exercises correctly through 3D illustrations, while in case of failure, it indicates the joints/gestures that need improvement; (iii) RehaBot is intelligent in assessing patients’ range of motions of various body parts and adjust the game’s level of difficulty in real-time tailored to the patients’ abilities, so that they do not lose interest of the game due to unrealistic difficulty levels
This paper extends our previous work introduced in [4,5] by demonstrating all algorithmic details behind our posture matching, smoothing, and adaptation techniques in “RehaBot”, and by conducting a clinical study to investigate the impact of this adaptive game-based physiotherapy solution on patients dealing with chronic neck pain as a case study
Summary
The challenge of designing a highly engaging serious game has been a subject of interest to various fields including training, simulation, healthcare, and education, among others.the direction towards creating a home-based individualized training plan for patients diagnosed with mental and/or physical disorders has attracted more interest due to the recent advancesSensors 2020, 20, 7037; doi:10.3390/s20247037 www.mdpi.com/journal/sensorsSensors 2020, 20, 7037 of technologies and techniques related to gamified telerehabilitation. The direction towards creating a home-based individualized training plan for patients diagnosed with mental and/or physical disorders has attracted more interest due to the recent advances. The patient-to-therapist ratio for physical rehabilitation is generally unable to comply with the ideal guidelines for staffing assumptions [1]. This usually results in appointment delays and reduced treatment time. Patients are, in most cases, required to perform additional exercises at home, allow timely recovery, and reduce the recurrent expensive visits to hospitals or rehabilitation centers [2]. Home-based exercises are considered as non-attractive, and are kept unmonitored without advanced analytics that allow measuring the patient’s key performance indicators [3]
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