Literature DB >> 25570790

iBEST: intelligent Balance assessment and Stability Training system using smartphone.

Aung Aung Phyo Wai, Pham Duy Duc, Chan Syin, Haihong Zhang.   

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.

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Year:  2014        PMID: 25570790     DOI: 10.1109/EMBC.2014.6944422

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  1 in total

1.  Measurement of Human Walking Movements by Using a Mobile Health App: Motion Sensor Data Analysis.

Authors:  Sungchul Lee; Ryan M Walker; Yoohwan Kim; Hyunhwa Lee
Journal:  JMIR Mhealth Uhealth       Date:  2021-03-05       Impact factor: 4.773

  1 in total

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