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. Slideshow Project DOI: /JRRD JSP 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
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. Slideshow Project DOI: /JRRD JSP 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.
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. Slideshow Project DOI: /JRRD JSP 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.
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. Slideshow Project DOI: /JRRD JSP Results Classifier achieved average accuracy of 96.6%.
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. Slideshow Project DOI: /JRRD JSP 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.