Measuring objective changes in movement via inertial sensors makes so much sense that all therapists should be using this in the next month. But that won't occur because we don't have a great stroke association pushing out these research results to all therapists.
http://scholar.google.com/scholar_url?url=http://www.mdpi.com/1424-8220/15/7/16196/pdf&hl=en&sa=X&scisig=AAGBfm0avOyQpV8NMjk_fx5FJR9BZgyoEQ&nossl=1&oi=scholaralrt
Hsin-Ta Li 1, Jheng-Jie Huang 1, Chien-Wen Pan 2, Heng-I. Chi 1 and Min-Chun Pan 1,3,*
1 Graduate Institute of Biomedical Engineering, National Central University, Jhongli 320, Taiwan;
E-Mails: winterfrost1143@gmail.com (H.-T.L.); d0785208@hotmail.com (J.-J.H.);
nocilole@hotmail.com (H.-I.C.)
2 Hsinchu Air Base, Hsinchu City 300, Taiwan; E-Mail: kkpan535634@gmail.com
3 Department of Mechanical Engineering, National Central University, Jhongli 320, Taiwan
* Author to whom correspondence should be addressed; E-Mail: pan_minc@cc.ncu.edu.tw;
Tel.: +886-3-426-7312; Fax: +886-3-425-4501.
Academic Editor: Gert F. Trommer
Received: 27 April 2015 / Accepted: 30 June 2015 / Published: 6 July 2015
Abstract: In clinical settings, traditional stroke rehabilitation evaluation methods are
subjectively scored by occupational therapists, and the assessment results vary
individually. To address this issue, this study aims to develop a stroke rehabilitation
assessment system by using inertial measurement units. The inertial signals from the upper
extremities were acquired, from which three quantitative indicators were extracted to
reflect rehabilitation performance during stroke patients’ movement examination, i.e.,
shoulder flexion. Both healthy adults and stroke patients were recruited to correlate the
proposed quantitative evaluation indices and traditional rehab assessment scales. Especially, as
a unique feature of the study the weight for each of three evaluation indicators was estimated
by the least squares method. The quantitative results demonstrate the proposed method
accurately reflects patients’ recovery from pre-rehabilitation, and confirm the feasibility of
applying inertial signals to evaluate rehab performance through feature extraction. The
implemented assessment scheme appears to have the potential to overcome some shortcomings
of traditional assessment methods and indicates rehab performance correctly.
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