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Smartphone-based Balance Assessment System for Chronic Stroke

National Yang Ming Chiao Tung University · 2018
ClinicalTrials.gov · Datasets · License: Public Domain · 2018
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nastroke
Background: Stroke is the 4th deadly disease in Taiwan, 2016. Long term disabilities, balance impairments and limitations of activities of daily living are common characteristics of stroke. Balance assessment and training play an important role in stroke rehabilitation. However, there are some limitations. Clinical assessments (functional scales) could not avoid some errors caused by subjective observations from different test givers; instrumental assessments (force plates, Biodex system) are complex to approach, not easy to use, and difficult to get. Balance training could not meet the expected effectiveness due to inconvenient transportations, forgotten home programs, and time limitation caused by huge amount of patients with insufficient therapists. Smartphones had been used for health promoting and sport training. The balance training related applications could be found at Google Play store, but clinically proved effective App and stroke-designed App has not yet existed. The balance rehabilitation of stroke sufferers will be benefited if there is an easy-use and effective App that supports balance assessment and personalized training by combining the convenience and powerfulness of smartphones. Purpose: The purposes of this study are: Year 1 Develop a smartphone-based application to assess and train static balance for stroke sufferers, and evaluate the feasibility of the application; Year 2 Develop a smartphone-based application to assess and train dynamic balance for stroke sufferers, and evaluate the feasibility of the application; Year 3 Build a static and dynamic balance performance standard by recruiting healthy subjects, then evaluate the training effects of the application on balance performance of stroke sufferers. Methods: Android smartphones will be used to analyze the balance performance by collecting acceleration and angular velocity data from the built-in sensors. Static balance assessment and training system will be developed in the first year
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