Physical rehabilitation is an important medical activity sector for the recovery of physical functions and clinical treatment of people affected by different pathologies, as neurodegenerative diseases (i.e. multiple sclerosis, Parkinson and Alzheimer diseases, amyotrophic lateral sclerosis), neuromuscular disorders (i.e. dystrophies, myopathies, amyotrophies and neuropathies), neurovascular disorders/trauma (i.e. stroke and traumatic brain injuries), and mobility for the elderly. During the rehabilitation, the patient has to perform different exercises specific for the own disease: while some exercises have to be performed with specific equipment and under the supervision of professional staff, others can be performed by patients without the supervision of physiotherapists. In this last case, it is possible to reduce the costs of health and care national system and to accomplish the treatment at home. In this work, a computer vision system for physical rehabilitation at home is proposed. The vision system exploits a low cost RGB-D camera and open source libraries for the image processing, in order to monitor the exercises performed by the patients, and returns a video feedback to improve the treatment effectiveness and to increase the user’s motivation, interest, and perseverance. Moreover, the vision system evaluates an exercise score in order to monitor the rehabilitation progress, an helpful information both for the clinician staff and patients, and allow physiotherapists to monitor the patients at home and correct their posture if the exercises are not well performed. This approach has been implemented and experimentally tested using the Microsoft Kinect camera, demonstrating good and reliable performances.

Low Cost RGB-D Vision Based System to Support Motor Disabilities Rehabilitation at Home

FREDDI, ALESSANDRO;
2015

Abstract

Physical rehabilitation is an important medical activity sector for the recovery of physical functions and clinical treatment of people affected by different pathologies, as neurodegenerative diseases (i.e. multiple sclerosis, Parkinson and Alzheimer diseases, amyotrophic lateral sclerosis), neuromuscular disorders (i.e. dystrophies, myopathies, amyotrophies and neuropathies), neurovascular disorders/trauma (i.e. stroke and traumatic brain injuries), and mobility for the elderly. During the rehabilitation, the patient has to perform different exercises specific for the own disease: while some exercises have to be performed with specific equipment and under the supervision of professional staff, others can be performed by patients without the supervision of physiotherapists. In this last case, it is possible to reduce the costs of health and care national system and to accomplish the treatment at home. In this work, a computer vision system for physical rehabilitation at home is proposed. The vision system exploits a low cost RGB-D camera and open source libraries for the image processing, in order to monitor the exercises performed by the patients, and returns a video feedback to improve the treatment effectiveness and to increase the user’s motivation, interest, and perseverance. Moreover, the vision system evaluates an exercise score in order to monitor the rehabilitation progress, an helpful information both for the clinician staff and patients, and allow physiotherapists to monitor the patients at home and correct their posture if the exercises are not well performed. This approach has been implemented and experimentally tested using the Microsoft Kinect camera, demonstrating good and reliable performances.
978-3-319-18373-2
978-3-319-18374-9
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11389/16716
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