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Optimal selection of electrodes for muscle electrical stimulation using twitching motion measurement

Authors:

Hiroyuki KajimotoAuthors Info & Claims

AH '13: Proceedings of the 4th Augmented Human International Conference

Pages 237 - 238

https://doi.org/10.1145/2459236.2459279

Published: 07 March 2013 Publication History

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Abstract

Muscle electrical stimulation envisions a wide range of human augmentation application. However, the applications commonly have issue of optimal electrodes placement. In this paper, we propose a method to select the optimal electrodes placement for finger flexion using twitching motion measurement. We delivered electrical stimulation producing twitching motion and measured the acceleration. By summing and averaging the acceleration waveforms and taking the difference between the maximum and minimum value, we measured the contribution of the electrical stimulation and used it to select the optimal electrodes pair for the movement. Preliminary experiment with four electrodes showed feasibility of our method.

References

[1]

Tamaki, E. et al., 2011. PossessedHand: Techniques for controlling human hands using electrical muscles stimuli. In proccedings of the SIGCHI Conference of Human Factors in Computing Systems (Vancouver, Canada, May 07--12, 2011). CHI '11. ACM, New York, NY, 543--552. DOI= http://dx.doi.org/10.1145/1978942.1979018.

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[2]

Popovic-Bijelic, A. et al., 2005. Multi-Field Surface Electrode for Selective Electrical Stimulation. Artificial Organs 29: 448--452.

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[3]

Malesevic, N. et al., 2010. Muscle twitch responses for shaping the multi-pad electrode for functional electrical stimulation. Journal of Automatic Control 20: 53--58.

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Cited By

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Zhou DHayakawa WNakajima YTadano K(2022)Development of a Wearable Haptic Glove Presenting Haptic Sensation by Electrical StimulationSensors10.3390/s2301043123:1(431)Online publication date: 30-Dec-2022
https://doi.org/10.3390/s23010431
Faltaous SKoelle MSchneegass S(2022)From Perception to Action: A Review and Taxonomy on Electrical Muscle Stimulation in HCIProceedings of the 21st International Conference on Mobile and Ubiquitous Multimedia10.1145/3568444.3568460(159-171)Online publication date: 27-Nov-2022
https://dl.acm.org/doi/10.1145/3568444.3568460
Nith RTeng SLi PTao YLopes P(2021)DextrEMS: Increasing Dexterity in Electrical Muscle Stimulation by Combining it with BrakesThe 34th Annual ACM Symposium on User Interface Software and Technology10.1145/3472749.3474759(414-430)Online publication date: 10-Oct-2021
https://dl.acm.org/doi/10.1145/3472749.3474759
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Index Terms

Optimal selection of electrodes for muscle electrical stimulation using twitching motion measurement
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI theory, concepts and models
    2. Interaction devices
      1. Haptic devices
  2. Interaction design
    1. Interaction design process and methods
      1. Interface design prototyping
    2. Interaction design theory, concepts and paradigms

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Published In

AH '13: Proceedings of the 4th Augmented Human International Conference

March 2013

254 pages

ISBN:9781450319041

DOI:10.1145/2459236

General Chair:
Albrecht Schmidt
University of Stuttgart, Germany
,
Program Chairs:
Andreas Bulling
Max Planck Institute for Informatics Saarbrücken, Germany
,
Christian Holz
Hasso Plattner Institute, Germany

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 March 2013

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SimTech
Universität Stuttgart

AH'13: 4th Augmented Human International Conference

March 7 - 8, 2013

Stuttgart, Germany

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AH '13 Paper Acceptance Rate 49 of 69 submissions, 71%;

Overall Acceptance Rate 121 of 306 submissions, 40%

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Zhou DHayakawa WNakajima YTadano K(2022)Development of a Wearable Haptic Glove Presenting Haptic Sensation by Electrical StimulationSensors10.3390/s2301043123:1(431)Online publication date: 30-Dec-2022
https://doi.org/10.3390/s23010431
Faltaous SKoelle MSchneegass S(2022)From Perception to Action: A Review and Taxonomy on Electrical Muscle Stimulation in HCIProceedings of the 21st International Conference on Mobile and Ubiquitous Multimedia10.1145/3568444.3568460(159-171)Online publication date: 27-Nov-2022
https://dl.acm.org/doi/10.1145/3568444.3568460
Nith RTeng SLi PTao YLopes P(2021)DextrEMS: Increasing Dexterity in Electrical Muscle Stimulation by Combining it with BrakesThe 34th Annual ACM Symposium on User Interface Software and Technology10.1145/3472749.3474759(414-430)Online publication date: 10-Oct-2021
https://dl.acm.org/doi/10.1145/3472749.3474759
Takahashi ABrooks JKajimoto HLopes PKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)Increasing Electrical Muscle Stimulation's Dexterity by means of Back of the Hand ActuationProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445761(1-12)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445761
Nishida JYagi KHassan MSuzuki K(2019)Wearable Kinesthetic I/O Device for Sharing Wrist Joint Stiffness2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)10.1109/EMBC.2019.8857538(3306-3310)Online publication date: Jul-2019
https://doi.org/10.1109/EMBC.2019.8857538
Pohl HHornbæk KKnibbe J(2018)Wanding Through SpaceProceedings of the 9th Augmented Human International Conference10.1145/3174910.3174948(1-5)Online publication date: 6-Feb-2018
https://dl.acm.org/doi/10.1145/3174910.3174948
Knibbe JStrohmeier PBoring SHornbæk K(2017)Automatic Calibration of High Density Electric Muscle StimulationProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/31309331:3(1-17)Online publication date: 11-Sep-2017
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Nishida JSuzuki KMark GFussell SLampe Cschraefel mHourcade JAppert CWigdor D(2017)bioSyncProceedings of the 2017 CHI Conference on Human Factors in Computing Systems10.1145/3025453.3025829(3316-3327)Online publication date: 2-May-2017
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Lopes PIon AMueller WHoffmann DJonell PBaudisch PBegole BKim JInkpen KWoo W(2015)Proprioceptive InteractionProceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems10.1145/2702123.2702461(939-948)Online publication date: 18-Apr-2015
https://dl.acm.org/doi/10.1145/2702123.2702461

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Recommendations

Muscle Extension Model for FES-Assisted Knee Swinging Ergometer for Stroke Patient

Effect of functional electrical stimulation (FES) when combined with gait training on treadmill in children with spastic diplegia

A phenomenological model for electrical stimulation of the upper limb

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