Research Article
Depth Images Processing Algorithm to Analyze and Correct in Real Time the Verticality of Multiple Sclerosis Patients during Exercise
@INPROCEEDINGS{10.4108/icst.pervasivehealth.2014.255322, author={Bego\`{o}a Garc\^{\i}a Zapirain and Gonzalo Eguiluz-Perez}, title={Depth Images Processing Algorithm to Analyze and Correct in Real Time the Verticality of Multiple Sclerosis Patients during Exercise}, proceedings={REHAB 2014}, publisher={ICST}, proceedings_a={REHAB}, year={2014}, month={7}, keywords={image processing time-of-flight verticality improvement}, doi={10.4108/icst.pervasivehealth.2014.255322} }- Begoña García Zapirain
Gonzalo Eguiluz-Perez
Year: 2014
Depth Images Processing Algorithm to Analyze and Correct in Real Time the Verticality of Multiple Sclerosis Patients during Exercise
REHAB
ICST
DOI: 10.4108/icst.pervasivehealth.2014.255322
Abstract
Any person with Multiple Sclerosis (MS), regardless of the severity of their disability, needs regular physical activity. Poorly performed exercises could aggravate muscle imbalances and worsen the patient’s health. In this paper, we propose a human body verticality detection system using a time-of-flight camera as a tool to detect incorrect postures and improve them in real time. The prototype uses a depth images processing algorithm to analyze and evaluate the position of patients during exercise. Preliminary results, based on a test with people without musculoskeletal problems and/or neurodegenerative diseases are promising and suggest that the system may be useful both for patients and medical professionals.
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