Ankle rehabilitation system with feedback from a smartphone wireless gyroscope platform and machine learning classification

Robert Lemoyne, Timothy Mastroianni, Anthony Hessel, Kiisa C Nishikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

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 languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages406-409
Number of pages4
ISBN (Print)9781509002870
DOIs
StatePublished - Mar 2 2016
EventIEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015 - Miami, United States
Duration: Dec 9 2015Dec 11 2015

Other

OtherIEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015
CountryUnited States
CityMiami
Period12/9/1512/11/15

Fingerprint

Smartphones
Gyroscopes
Patient rehabilitation
Learning systems
Feedback
Printing
Electronic mail
Support vector machines
Brain
Internet

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

Lemoyne, R., Mastroianni, T., Hessel, A., & Nishikawa, K. C. (2016). Ankle rehabilitation system with feedback from a smartphone wireless gyroscope platform and machine learning classification. In Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015 (pp. 406-409). [7424346] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMLA.2015.213

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 proceedingConference contribution

Lemoyne, R, Mastroianni, T, Hessel, A & Nishikawa, KC 2016, Ankle rehabilitation system with feedback from a smartphone wireless gyroscope platform and machine learning classification. in Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015., 7424346, Institute of Electrical and Electronics Engineers Inc., pp. 406-409, IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015, Miami, United States, 12/9/15. https://doi.org/10.1109/ICMLA.2015.213
Lemoyne R, Mastroianni T, Hessel A, Nishikawa KC. Ankle rehabilitation system with feedback from a smartphone wireless gyroscope platform and machine learning classification. In 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 https://doi.org/10.1109/ICMLA.2015.213
Lemoyne, Robert ; Mastroianni, Timothy ; Hessel, Anthony ; Nishikawa, Kiisa C. / Ankle rehabilitation system with feedback from a smartphone wireless gyroscope platform and machine learning classification. Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 406-409
@inproceedings{b67b917d84944f87bc281edee00fbf83,
title = "Ankle rehabilitation system with feedback from a smartphone wireless gyroscope platform and machine learning classification",
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 = "3D printing, Ankle rehabilitation, Dorsiflexion, Gyroscope, Machine learning, Smartphone, Support vector machine, Therapy, Therapy quantification, Wireless gyroscope, Wireless sensor",
author = "Robert Lemoyne and Timothy Mastroianni and Anthony Hessel and Nishikawa, {Kiisa C}",
year = "2016",
month = "3",
day = "2",
doi = "10.1109/ICMLA.2015.213",
language = "English (US)",
isbn = "9781509002870",
pages = "406--409",
booktitle = "Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

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 -