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