Designing Game-Based Myoelectric Prosthesis Training

Aaron Tabor, Scott Bateman, Erik Scheme, David Flatla, Kathrin Gerling

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

  • 4 Citations

Abstract

A myoelectric prosthesis (myo) is a dexterous artificial limb controlled by muscle contractions. Learning to use a myo can be challenging, so extensive training is often required to use a myo prosthesis effectively. Signal visualizations and simple muscle-controlled games are currently used to help patients train their muscles, but are boring and frustrating.
Furthermore, current training systems require expensive medical equipment and clinician oversight, restricting training to infrequent clinical visits. To address these limitations, we developed a new game that promotes fun and success, and shows the viability of a low-cost myoelectric input device. We adapted a user-centered design (UCD) process to receive feedback from patients, clinicians, and family members as we iteratively addressed challenges to improve our game. Through this work, we introduce a free and open myo training game, provide new information about the design of myo training games, and reflect on an adapted UCD process for the practical iterative development of therapeutic games.
LanguageEnglish
Title of host publicationCHI 2017
Subtitle of host publicationProceedings of the 2017 CHI Conference on Human Factors in Computing Systems
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Pages1352-1363
Number of pages13
ISBN (Electronic)9781450346559
DOIs
Publication statusPublished - 2 May 2017
EventCHI '17: CHI Conference on Human Factors in Computing Systems - Denver, United States
Duration: 6 May 201711 May 2017
https://chi2017.acm.org/

Conference

ConferenceCHI '17
CountryUnited States
CityDenver
Period6/05/1711/05/17
Internet address

Fingerprint

Muscle
Artificial limbs
Biomedical equipment
Boring
Visualization
Feedback
Prostheses and Implants
Costs
User centered design

Keywords

  • Prosthetic
  • myoelectric
  • training
  • games
  • UCD
  • H.5.m. Info interfaces & presentation (e.g., HCI)

Cite this

Tabor, A., Bateman, S., Scheme, E., Flatla, D., & Gerling, K. (2017). Designing Game-Based Myoelectric Prosthesis Training. In CHI 2017: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (pp. 1352-1363). New York: Association for Computing Machinery. https://doi.org/10.1145/3025453.3025676
Tabor, Aaron ; Bateman, Scott ; Scheme, Erik ; Flatla, David ; Gerling, Kathrin. / Designing Game-Based Myoelectric Prosthesis Training. CHI 2017: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. New York : Association for Computing Machinery, 2017. pp. 1352-1363
@inproceedings{1b60eff471204285b83f9043df71f5b3,
title = "Designing Game-Based Myoelectric Prosthesis Training",
abstract = "A myoelectric prosthesis (myo) is a dexterous artificial limb controlled by muscle contractions. Learning to use a myo can be challenging, so extensive training is often required to use a myo prosthesis effectively. Signal visualizations and simple muscle-controlled games are currently used to help patients train their muscles, but are boring and frustrating.Furthermore, current training systems require expensive medical equipment and clinician oversight, restricting training to infrequent clinical visits. To address these limitations, we developed a new game that promotes fun and success, and shows the viability of a low-cost myoelectric input device. We adapted a user-centered design (UCD) process to receive feedback from patients, clinicians, and family members as we iteratively addressed challenges to improve our game. Through this work, we introduce a free and open myo training game, provide new information about the design of myo training games, and reflect on an adapted UCD process for the practical iterative development of therapeutic games.",
keywords = "Prosthetic, myoelectric, training, games, UCD, H.5.m. Info interfaces & presentation (e.g., HCI)",
author = "Aaron Tabor and Scott Bateman and Erik Scheme and David Flatla and Kathrin Gerling",
note = "We would like to thank the Atlantic Clinic for Upper Limb Prosthetics, and especially Wendy Hill, for all the help and guidance that they provided throughout our study. We would like to thanks the patient and expert participants who generously gave time to help with our research. This research was funded through the support of NSERC and New Brunswick Innovation Foundation (NBIF).",
year = "2017",
month = "5",
day = "2",
doi = "10.1145/3025453.3025676",
language = "English",
pages = "1352--1363",
booktitle = "CHI 2017",
publisher = "Association for Computing Machinery",

}

Tabor, A, Bateman, S, Scheme, E, Flatla, D & Gerling, K 2017, Designing Game-Based Myoelectric Prosthesis Training. in CHI 2017: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, pp. 1352-1363, CHI '17, Denver, United States, 6/05/17. https://doi.org/10.1145/3025453.3025676

Designing Game-Based Myoelectric Prosthesis Training. / Tabor, Aaron; Bateman, Scott; Scheme, Erik; Flatla, David; Gerling, Kathrin.

CHI 2017: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. New York : Association for Computing Machinery, 2017. p. 1352-1363.

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

TY - GEN

T1 - Designing Game-Based Myoelectric Prosthesis Training

AU - Tabor, Aaron

AU - Bateman, Scott

AU - Scheme, Erik

AU - Flatla, David

AU - Gerling, Kathrin

N1 - We would like to thank the Atlantic Clinic for Upper Limb Prosthetics, and especially Wendy Hill, for all the help and guidance that they provided throughout our study. We would like to thanks the patient and expert participants who generously gave time to help with our research. This research was funded through the support of NSERC and New Brunswick Innovation Foundation (NBIF).

PY - 2017/5/2

Y1 - 2017/5/2

N2 - A myoelectric prosthesis (myo) is a dexterous artificial limb controlled by muscle contractions. Learning to use a myo can be challenging, so extensive training is often required to use a myo prosthesis effectively. Signal visualizations and simple muscle-controlled games are currently used to help patients train their muscles, but are boring and frustrating.Furthermore, current training systems require expensive medical equipment and clinician oversight, restricting training to infrequent clinical visits. To address these limitations, we developed a new game that promotes fun and success, and shows the viability of a low-cost myoelectric input device. We adapted a user-centered design (UCD) process to receive feedback from patients, clinicians, and family members as we iteratively addressed challenges to improve our game. Through this work, we introduce a free and open myo training game, provide new information about the design of myo training games, and reflect on an adapted UCD process for the practical iterative development of therapeutic games.

AB - A myoelectric prosthesis (myo) is a dexterous artificial limb controlled by muscle contractions. Learning to use a myo can be challenging, so extensive training is often required to use a myo prosthesis effectively. Signal visualizations and simple muscle-controlled games are currently used to help patients train their muscles, but are boring and frustrating.Furthermore, current training systems require expensive medical equipment and clinician oversight, restricting training to infrequent clinical visits. To address these limitations, we developed a new game that promotes fun and success, and shows the viability of a low-cost myoelectric input device. We adapted a user-centered design (UCD) process to receive feedback from patients, clinicians, and family members as we iteratively addressed challenges to improve our game. Through this work, we introduce a free and open myo training game, provide new information about the design of myo training games, and reflect on an adapted UCD process for the practical iterative development of therapeutic games.

KW - Prosthetic

KW - myoelectric

KW - training

KW - games

KW - UCD

KW - H.5.m. Info interfaces & presentation (e.g., HCI)

UR - https://www.youtube.com/watch?v=Aq83ldWpOGk

U2 - 10.1145/3025453.3025676

DO - 10.1145/3025453.3025676

M3 - Conference contribution

SP - 1352

EP - 1363

BT - CHI 2017

PB - Association for Computing Machinery

CY - New York

ER -

Tabor A, Bateman S, Scheme E, Flatla D, Gerling K. Designing Game-Based Myoelectric Prosthesis Training. In CHI 2017: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. New York: Association for Computing Machinery. 2017. p. 1352-1363 https://doi.org/10.1145/3025453.3025676