DocumentCode :
3756804
Title :
Ankle Rehabilitation System with Feedback from a Smartphone Wireless Gyroscope Platform and Machine Learning Classification
Author :
Robert LeMoyne;Timothy Mastroianni;Anthony Hessel;Kiisa Nishikawa
Author_Institution :
Dept. of Biol. Sci., Northern Arizona Univ., Flagstaff, AZ, USA
fYear :
2015
Firstpage :
406
Lastpage :
409
Abstract :
With the prevalence of traumatic brain injury and associated motor function impairment, an advance in the capacity to measure the efficacy of a rehabilitation strategy is a topic of considerable interest. For example, the development of a rehabilitation system that can quantify the efficacy to an ankle dorsiflexion therapy prescription would be beneficial. An ankle rehabilitation system is presented that amalgamates multiple technologies, such as a smartphone (iPhone) wireless gyroscope platform, machine learning, and 3D printing. The ankle rehabilitation system is produced by mostly 3D printing. A smartphone wireless gyroscope platform records the ankle rehabilitation system´s therapy usage with wireless transmission to the Internet as an email attachment. The gyroscope signal data is processed for machine learning. A support vector machine attains 97% classification between a hemiplegic affected ankle and unaffected ankle feature set while using the ankle rehabilitation system. The application can be readily applied to a homebound setting of the subject´s convenience.
Keywords :
"Gyroscopes","Wireless communication","Wireless sensor networks","Medical treatment","Communication system security","Support vector machines","Electronic mail"
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications (ICMLA), 2015 IEEE 14th International Conference on
Type :
conf
DOI :
10.1109/ICMLA.2015.213
Filename :
7424346
Link To Document :
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