Abstract
Abstract This paper presents the proof-of-concept of a home-based gamified wrist rehabilitation training system for children with cerebral palsy (CCP). We describe the user-centered design process of this system, which is composed of a wrist-worn inertial measurement unit (IMU) and a tangible device with an embedded IMU. The system employs a quaternion-based algorithm for automatic real-time estimation of the range of motion (RoM) covered by adduction/abduction and flexion/extension motions of the wrist. Experimental validation shows that the RoM can be determined with sufficient accuracy to control a game and that the algorithm is applicable in CCP. A serious game, which uses the presented algorithm and enables feedback as well as motivating stimuli, is implemented and evaluated by physiotherapists.
Highlights
Cerebral palsy – a nonprogressive motor disorder in children [12] – is the most common significant childhood motor impairment in Europe with a prevalence of about 2 of 1000 in newborns [17]
This paper presents the proof-of-concept of a home-based gamified wrist rehabilitation training system for children with cerebral palsy (CCP)
We describe the user-centered design process of this system, which is composed of a wrist-worn inertial measurement unit (IMU) and a tangible device with an embedded IMU
Summary
Cerebral palsy – a nonprogressive motor disorder in children [12] – is the most common significant childhood motor impairment in Europe with a prevalence of about 2 of 1000 in newborns [17]. Commercial rehabilitation products have the advantage of providing certain therapeutic movements and detailed feedback, but due to high prices and complicated setting they are not suitable for home training. Entertainment products have the advantages of general acceptance in CCP and peers, high motivation to move as well as affordability They do neither train specific movements nor do they try to avoid unwanted movements which may increase the misalignment due to spasticity. A recent review [22] compares the results in sensor positions, sensor fusion algorithm and RoM calculations for the upper limb generated by different systems It concludes that the wrist angles can be determined by IMUs with a difference of less than 4 degrees in comparison to robotic or optical systems, but that due to the variability of study settings and algorithms used, further research is needed. A home-based wrist training system for children with cerabral palsy | 969
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