DocumentCode
140206
Title
iBEST: Intelligent balance assessment and stability training system using smartphone
Author
Aung Aung Phyo Wai ; Pham Duy Duc ; Chan Syin ; Zhang Haihong
Author_Institution
Neural & Biomed. Technol. Dept., A*STAR, Singapore, Singapore
fYear
2014
fDate
26-30 Aug. 2014
Firstpage
3683
Lastpage
3686
Abstract
Patients with postural instability could lead to falls and injuries while walking due to balance disorders. So those patients need regular balance training and evaluation to improve and examine balance deficiencies. But many do not notice such balance issues; resulting lack of timely preventive measures. This shows the needs of affordable and accessible solution for balance training and assessment. So iBEST (intelligent Balance assessment and Stability Training) is proposed enabling to train and assess balance conveniently anywhere anytime. Moreover, therapists can remotely evaluate and manage their recovery progress. These benefits can be realized leveraging sensors from smartphone, cloud-based data analytics and web applications. iBEST employs sensorised automated balance assessment in digitizing Berg Balance Scale (BBS) clinical risk assessment tool. The initial feasibility study showed average accuracy of 90.22% using smartphone in classifying the specified BBS test items.
Keywords
cloud computing; medical computing; mobile computing; patient monitoring; smart phones; Berg balance scale clinical risk assessment tool; balance disorders; cloud-based data analytics; iBEST; intelligent balance assessment and stability training; postural instability; recovery progress; remote evaluation; smart phone; web applications; Accuracy; Mobile communication; Senior citizens; Sensors; Stability analysis; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location
Chicago, IL
ISSN
1557-170X
Type
conf
DOI
10.1109/EMBC.2014.6944422
Filename
6944422
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