research-article

Towards EMG control interface for smart garments

Authors:

Simone Benatti,

Elisabetta Farella,

Luca BeniniAuthors Info & Claims

ISWC '14 Adjunct: Proceedings of the 2014 ACM International Symposium on Wearable Computers: Adjunct Program

Pages 163 - 170

https://doi.org/10.1145/2641248.2641352

Published: 13 September 2014 Publication History

Abstract

Wearable computing devices can greatly enhance the quality of life, helping interaction with smart environment, activity recognition and healthcare applications. Smart garments offer the opportunity to integrate sensors and electronics in unobtrusive wearable systems. The paper presents a case study of an embedded hand gesture recognition system, which uses EMG electrodes embeddable in smart clothes. We analyze the main challenges of a real-time system for pattern recognition and the results of the proposed experiment demonstrate the feasibility of a real-time system for pattern recognition, which can be integrated in smart clothes.

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Cited By

Ingolfsson TBenatti SWang XBernini ADucouret PRyvlin PBeniczky SBenini LCossettini A(2024)Minimizing artifact-induced false-alarms for seizure detection in wearable EEG devices with gradient-boosted tree classifiersScientific Reports10.1038/s41598-024-52551-014:1Online publication date: 5-Feb-2024
https://doi.org/10.1038/s41598-024-52551-0
Kang SKim HPark CSim YLee SJung Y(2023)sEMG-Based Hand Gesture Recognition Using Binarized Neural NetworkSensors10.3390/s2303143623:3(1436)Online publication date: 28-Jan-2023
https://doi.org/10.3390/s23031436
Eddy EScheme EBateman S(2023)A Framework and Call to Action for the Future Development of EMG-Based Input in HCIProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580962(1-23)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580962
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Index Terms

Towards EMG control interface for smart garments
1. Human-centered computing

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Published In

cover image ACM Conferences

ISWC '14 Adjunct: Proceedings of the 2014 ACM International Symposium on Wearable Computers: Adjunct Program

September 2014

271 pages

ISBN:9781450330480

DOI:10.1145/2641248

General Chair:
Lucy Dunne
University of Minnesota Research
,
Program Chairs:
Tom Martin
Virginia Tech
,
Michael Beigl
Karlsruhe Institute of Technology, DE

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 13 September 2014

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INAIL in Vigorso di Budrio, Italy
Centro protesi
Seventh Framework Programme

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UbiComp '14

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UbiComp '14: The 2014 ACM Conference on Ubiquitous Computing

September 13 - 17, 2014

Washington, Seattle

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Overall Acceptance Rate 38 of 196 submissions, 19%

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UbiComp '24

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The 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing

October 5 - 9, 2024

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Cited By

Ingolfsson TBenatti SWang XBernini ADucouret PRyvlin PBeniczky SBenini LCossettini A(2024)Minimizing artifact-induced false-alarms for seizure detection in wearable EEG devices with gradient-boosted tree classifiersScientific Reports10.1038/s41598-024-52551-014:1Online publication date: 5-Feb-2024
https://doi.org/10.1038/s41598-024-52551-0
Kang SKim HPark CSim YLee SJung Y(2023)sEMG-Based Hand Gesture Recognition Using Binarized Neural NetworkSensors10.3390/s2303143623:3(1436)Online publication date: 28-Jan-2023
https://doi.org/10.3390/s23031436
Eddy EScheme EBateman S(2023)A Framework and Call to Action for the Future Development of EMG-Based Input in HCIProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580962(1-23)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580962
Bian SLiu MZhou BLukowicz P(2022)The State-of-the-Art Sensing Techniques in Human Activity Recognition: A SurveySensors10.3390/s2212459622:12(4596)Online publication date: 17-Jun-2022
https://doi.org/10.3390/s22124596
Ingolfsson TCossettini ABenatti SBenini L(2022)Energy-Efficient Tree-Based EEG Artifact Detection2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)10.1109/EMBC48229.2022.9871413(3723-3728)Online publication date: 11-Jul-2022
https://doi.org/10.1109/EMBC48229.2022.9871413
Mazzoni BBenatti SBenini LTagliavini G(2021)Efficient Transform Algorithms for Parallel Ultra-Low-Power IoT End NodesIEEE Embedded Systems Letters10.1109/LES.2021.306520613:4(210-213)Online publication date: Dec-2021
https://doi.org/10.1109/LES.2021.3065206
Ingolfsson TCossettini AWang XTabanelli ETagliavini GRyvlin PBenini LBenatti S(2021)Towards Long-term Non-invasive Monitoring for Epilepsy via Wearable EEG Devices2021 IEEE Biomedical Circuits and Systems Conference (BioCAS)10.1109/BioCAS49922.2021.9644949(01-04)Online publication date: 7-Oct-2021
https://doi.org/10.1109/BioCAS49922.2021.9644949
Jaramillo-Yánez ABenalcázar MMena-Maldonado E(2020)Real-Time Hand Gesture Recognition Using Surface Electromyography and Machine Learning: A Systematic Literature ReviewSensors10.3390/s2009246720:9(2467)Online publication date: 27-Apr-2020
https://doi.org/10.3390/s20092467
Kan CTang K(2020)Chemical Characterization of Fibrous MaterialsHandbook of Fibrous Materials10.1002/9783527342587.ch20(499-527)Online publication date: 3-Apr-2020
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Asai KTakase N(2019)Finger Motion Estimation Based on Sparse Multi-Channel Surface Electromyography Signals Using Convolutional Neural NetworkProceedings of the 2019 3rd International Conference on Digital Signal Processing10.1145/3316551.3316572(55-59)Online publication date: 24-Feb-2019
https://dl.acm.org/doi/10.1145/3316551.3316572
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