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.
Original language | English (US) |
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Title of host publication | Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 406-409 |
Number of pages | 4 |
ISBN (Print) | 9781509002870 |
DOIs | |
State | Published - Mar 2 2016 |
Event | IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015 - Miami, United States Duration: Dec 9 2015 → Dec 11 2015 |
Other
Other | IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015 |
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Country | United States |
City | Miami |
Period | 12/9/15 → 12/11/15 |
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Keywords
- 3D printing
- Ankle rehabilitation
- Dorsiflexion
- Gyroscope
- Machine learning
- Smartphone
- Support vector machine
- Therapy
- Therapy quantification
- Wireless gyroscope
- Wireless sensor
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
Cite this
Ankle rehabilitation system with feedback from a smartphone wireless gyroscope platform and machine learning classification. / Lemoyne, Robert; Mastroianni, Timothy; Hessel, Anthony; Nishikawa, Kiisa C.
Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 406-409 7424346.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Ankle rehabilitation system with feedback from a smartphone wireless gyroscope platform and machine learning classification
AU - Lemoyne, Robert
AU - Mastroianni, Timothy
AU - Hessel, Anthony
AU - Nishikawa, Kiisa C
PY - 2016/3/2
Y1 - 2016/3/2
N2 - 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.
AB - 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.
KW - 3D printing
KW - Ankle rehabilitation
KW - Dorsiflexion
KW - Gyroscope
KW - Machine learning
KW - Smartphone
KW - Support vector machine
KW - Therapy
KW - Therapy quantification
KW - Wireless gyroscope
KW - Wireless sensor
UR - http://www.scopus.com/inward/record.url?scp=84969705851&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84969705851&partnerID=8YFLogxK
U2 - 10.1109/ICMLA.2015.213
DO - 10.1109/ICMLA.2015.213
M3 - Conference contribution
AN - SCOPUS:84969705851
SN - 9781509002870
SP - 406
EP - 409
BT - Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -