Automatic Calibration of High Density Electric Muscle Stimulation

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

Automatic Calibration of High Density Electric Muscle Stimulation. / Knibbe, Jarrod; Strohmeier, Paul; Boring, Sebastian; Hornbæk, Kasper.

In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Vol. 1, No. 3, 68, 2017.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Knibbe, J, Strohmeier, P, Boring, S & Hornbæk, K 2017, 'Automatic Calibration of High Density Electric Muscle Stimulation', Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 1, no. 3, 68. https://doi.org/10.1145/3130933

APA

Knibbe, J., Strohmeier, P., Boring, S., & Hornbæk, K. (2017). Automatic Calibration of High Density Electric Muscle Stimulation. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 1(3), [68]. https://doi.org/10.1145/3130933

Vancouver

Knibbe J, Strohmeier P, Boring S, Hornbæk K. Automatic Calibration of High Density Electric Muscle Stimulation. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 2017;1(3). 68. https://doi.org/10.1145/3130933

Author

Knibbe, Jarrod ; Strohmeier, Paul ; Boring, Sebastian ; Hornbæk, Kasper. / Automatic Calibration of High Density Electric Muscle Stimulation. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 2017 ; Vol. 1, No. 3.

Bibtex

@article{7e3123e354d8422baed64e55f0c0387b,
title = "Automatic Calibration of High Density Electric Muscle Stimulation",
abstract = "Electric muscle stimulation (EMS) can enable mobile force feedback, support pedestrian navigation, or confer object affordances. To date, however, EMS is limited by two interlinked problems. (1) EMS is low resolution -- achieving only coarse movements and constraining opportunities for exploration. (2) EMS requires time consuming, expert calibration -- confining these interaction techniques to the lab. EMS arrays have been shown to increase stimulation resolution, but as calibration complexity increases exponentially as more electrodes are used, we require heuristics or automated procedures for successful calibration. We explore the feasibility of using electromyography (EMG) to auto-calibrate high density EMS arrays. We determine regions of muscle activity during human-performed gestures, to inform stimulation patterns for EMS-performed gestures. We report on a study which shows that auto-calibration of a 60-electrode array is feasible: achieving 52% accuracy across six gestures, with 82% accuracy across our best three gestures. By highlighting the electrode-array calibration problem, and presenting a first exploration of a potential solution, this work lays the foundations for high resolution, wearable and, perhaps one day, ubiquitous EMS beyond the lab.",
author = "Jarrod Knibbe and Paul Strohmeier and Sebastian Boring and Kasper Hornb{\ae}k",
year = "2017",
doi = "10.1145/3130933",
language = "English",
volume = "1",
journal = "Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies",
publisher = "ACM",
number = "3",

}

RIS

TY - JOUR

T1 - Automatic Calibration of High Density Electric Muscle Stimulation

AU - Knibbe, Jarrod

AU - Strohmeier, Paul

AU - Boring, Sebastian

AU - Hornbæk, Kasper

PY - 2017

Y1 - 2017

N2 - Electric muscle stimulation (EMS) can enable mobile force feedback, support pedestrian navigation, or confer object affordances. To date, however, EMS is limited by two interlinked problems. (1) EMS is low resolution -- achieving only coarse movements and constraining opportunities for exploration. (2) EMS requires time consuming, expert calibration -- confining these interaction techniques to the lab. EMS arrays have been shown to increase stimulation resolution, but as calibration complexity increases exponentially as more electrodes are used, we require heuristics or automated procedures for successful calibration. We explore the feasibility of using electromyography (EMG) to auto-calibrate high density EMS arrays. We determine regions of muscle activity during human-performed gestures, to inform stimulation patterns for EMS-performed gestures. We report on a study which shows that auto-calibration of a 60-electrode array is feasible: achieving 52% accuracy across six gestures, with 82% accuracy across our best three gestures. By highlighting the electrode-array calibration problem, and presenting a first exploration of a potential solution, this work lays the foundations for high resolution, wearable and, perhaps one day, ubiquitous EMS beyond the lab.

AB - Electric muscle stimulation (EMS) can enable mobile force feedback, support pedestrian navigation, or confer object affordances. To date, however, EMS is limited by two interlinked problems. (1) EMS is low resolution -- achieving only coarse movements and constraining opportunities for exploration. (2) EMS requires time consuming, expert calibration -- confining these interaction techniques to the lab. EMS arrays have been shown to increase stimulation resolution, but as calibration complexity increases exponentially as more electrodes are used, we require heuristics or automated procedures for successful calibration. We explore the feasibility of using electromyography (EMG) to auto-calibrate high density EMS arrays. We determine regions of muscle activity during human-performed gestures, to inform stimulation patterns for EMS-performed gestures. We report on a study which shows that auto-calibration of a 60-electrode array is feasible: achieving 52% accuracy across six gestures, with 82% accuracy across our best three gestures. By highlighting the electrode-array calibration problem, and presenting a first exploration of a potential solution, this work lays the foundations for high resolution, wearable and, perhaps one day, ubiquitous EMS beyond the lab.

U2 - 10.1145/3130933

DO - 10.1145/3130933

M3 - Journal article

VL - 1

JO - Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

JF - Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

IS - 3

M1 - 68

ER -

ID: 193794891