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This article and any supplementary material should be cited as follows: Redfield MT, Cagle JC, Hafner BJ, Sanders JE. Classifying prosthetic use via accelerometry.

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Presentation on theme: "This article and any supplementary material should be cited as follows: Redfield MT, Cagle JC, Hafner BJ, Sanders JE. Classifying prosthetic use via accelerometry."— Presentation transcript:

1 This article and any supplementary material should be cited as follows: Redfield MT, Cagle JC, Hafner BJ, Sanders JE. Classifying prosthetic use via accelerometry in persons with transtibial amputations. J Rehabil Res Dev. 2013;50(9):XXX–XXX. http://dx.doi.org/10.1682/JRRD.2012.12.0233 Slideshow Project DOI:10.1682/JRRD.2012.12.0233JSP Classifying prosthetic use via accelerometry in persons with transtibial amputations Morgan T. Redfield, MSEE; John C. Cagle, BSE; Brian J. Hafner, PhD; Joan E. Sanders, PhD

2 This article and any supplementary material should be cited as follows: Redfield MT, Cagle JC, Hafner BJ, Sanders JE. Classifying prosthetic use via accelerometry in persons with transtibial amputations. J Rehabil Res Dev. 2013;50(9):XXX–XXX. http://dx.doi.org/10.1682/JRRD.2012.12.0233 Slideshow Project DOI:10.1682/JRRD.2012.12.0233JSP Aim – Use 3-axis accelerometer to characterize activities and body postures in transtibial amputation. Relevance – How persons with amputation use their prostheses over time may facilitate rehabilitation and enhance understanding of prosthesis functionality. – Existing monitoring and classification systems are often limited, record data over short periods, and/or classify limited activities and body postures.

3 This article and any supplementary material should be cited as follows: Redfield MT, Cagle JC, Hafner BJ, Sanders JE. Classifying prosthetic use via accelerometry in persons with transtibial amputations. J Rehabil Res Dev. 2013;50(9):XXX–XXX. http://dx.doi.org/10.1682/JRRD.2012.12.0233 Slideshow Project DOI:10.1682/JRRD.2012.12.0233JSP Method Accelerometers were mounted on prosthetic pylons of 10 persons with transtibial amputation as they performed preset routine of actions. Accelerometer data was postprocessed with binary decision tree to: – Identify when prosthesis was being worn. – Classify use as movement, standing, or sitting. Classifications were compared to visual observation by study researchers.

4 This article and any supplementary material should be cited as follows: Redfield MT, Cagle JC, Hafner BJ, Sanders JE. Classifying prosthetic use via accelerometry in persons with transtibial amputations. J Rehabil Res Dev. 2013;50(9):XXX–XXX. http://dx.doi.org/10.1682/JRRD.2012.12.0233 Slideshow Project DOI:10.1682/JRRD.2012.12.0233JSP Results Classifier achieved average accuracy of 96.6%.

5 This article and any supplementary material should be cited as follows: Redfield MT, Cagle JC, Hafner BJ, Sanders JE. Classifying prosthetic use via accelerometry in persons with transtibial amputations. J Rehabil Res Dev. 2013;50(9):XXX–XXX. http://dx.doi.org/10.1682/JRRD.2012.12.0233 Slideshow Project DOI:10.1682/JRRD.2012.12.0233JSP Conclusion Information provided by this system may: – Help clinicians in fitting prostheses, selecting components, or training patients. – Be useful for automatic feedback control to adjust prosthesis mechanisms based on activity and posture.

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