research-article

CapWalk: a capacitive recognition of walking-based activities as a wearable assistive technology

Authors:

Marian Haescher,

Denys J. C. Matthies,

Bodo UrbanAuthors Info & Claims

PETRA '15: Proceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments

Article No.: 35, Pages 1 - 8

https://doi.org/10.1145/2769493.2769500

Published: 01 July 2015 Publication History

Abstract

In this research project, we present an alternative approach to recognize various walking-based activities based on the technology of capacitive sensing. While accelerometry-based walking detections suffer from reduced accuracy at low speeds, the technology of capacitive sensing uses physical distance parameters, which makes it invariant to the duration of step performance. Determining accurate levels of walking activity is a crucial factor for people who perform walking with tiny step lengths such as elderlies or patients with pathologic conditions. In contrast to other gait analysis solutions, CapWalk is mobile and less affected by external influences such as bad lighting conditions, while it is also invariant to external acceleration artifacts. Our approach enables a reliable recognition of very slow walking speeds, in which accelerometer-based implementations can fail or provide high deviations. In CapWalk we present three different capacitive sensing prototypes (Leg Band, Chest Band, Insole) in the setup of loading mode to demonstrate recognition of sneaking, normal walking, fast walking, jogging, and walking while carrying weight. Our designs are wearable and could easily be integrated into wearable objects, such as shoes, pants or jackets. We envision such gathered information to be used to assist certain user groups such as diabetics, whose optimal insulin dose is depending on bread units and physical activity or elderlies whose personalized dosage of medication can be better determined based on their physical activity.

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Cited By

Bian SLiu MZhou BLukowicz PMagno M(2024)Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer InteractionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435558:1(1-49)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643555
Somarathna RLi XBamdad MMohammadi G(2024)EmoFoot: Can Your Foot Tell How You Feel when Playing Virtual Reality Games?Adjunct Proceedings of the 26th International Conference on Mobile Human-Computer Interaction10.1145/3640471.3680234(1-6)Online publication date: 21-Sep-2024
https://dl.acm.org/doi/10.1145/3640471.3680234
Gabrecht MWang HMatthies D(2023)PneuShoe: A Pneumatic Smart Shoe for Activity Recognition, Terrain Identification, and Weight EstimationProceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence10.1145/3615834.3615853(1-5)Online publication date: 21-Sep-2023
https://dl.acm.org/doi/10.1145/3615834.3615853
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Index Terms

CapWalk: a capacitive recognition of walking-based activities as a wearable assistive technology
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction devices
      1. Touch screens
    2. Interaction paradigms

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PETRA '15: Proceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments

July 2015

526 pages

ISBN:9781450334525

DOI:10.1145/2769493

Conference Chair:
Fillia Makedon
University of Texas Arlington
,
Program Chairs:
Gian-Luca Mariottini,
Oliver Korn,
Illias Maglogiannis,
Vangelis Metsis

Copyright © 2015 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]

Sponsors

NSF: National Science Foundation
University of Texas at Austin: University of Texas at Austin
Univ. of Piraeus: University of Piraeus
NCRS: Demokritos National Center for Scientific Research
Ionian: Ionian University, GREECE

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Association for Computing Machinery

New York, NY, United States

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Published: 01 July 2015

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German Federal State of Mecklenburg-Western Pomerania and the European Social Fund

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PETRA '15

Sponsor:

NSF
University of Texas at Austin
Univ. of Piraeus
NCRS
Ionian

PETRA '15: 8th PErvasive Technologies Related to Assistive Environments

July 1 - 3, 2015

Corfu, Greece

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Cited By

Bian SLiu MZhou BLukowicz PMagno M(2024)Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer InteractionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435558:1(1-49)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643555
Somarathna RLi XBamdad MMohammadi G(2024)EmoFoot: Can Your Foot Tell How You Feel when Playing Virtual Reality Games?Adjunct Proceedings of the 26th International Conference on Mobile Human-Computer Interaction10.1145/3640471.3680234(1-6)Online publication date: 21-Sep-2024
https://dl.acm.org/doi/10.1145/3640471.3680234
Gabrecht MWang HMatthies D(2023)PneuShoe: A Pneumatic Smart Shoe for Activity Recognition, Terrain Identification, and Weight EstimationProceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence10.1145/3615834.3615853(1-5)Online publication date: 21-Sep-2023
https://dl.acm.org/doi/10.1145/3615834.3615853
Bello HZhou BSuh SSanchez Marin LLukowicz P(2022)Move With the Theremin: Body Posture and Gesture Recognition Using the Theremin in Loose-Garment With Embedded Textile Cables as AntennasFrontiers in Computer Science10.3389/fcomp.2022.9152804Online publication date: 22-Jun-2022
https://doi.org/10.3389/fcomp.2022.915280
Li XMatthies D(2022)ShoeTect: Detecting Body Posture, Ambulation Activity, Gait Abnormalities, and Terrain with Multisensory Smart FootwearProceedings of the 7th International Workshop on Sensor-based Activity Recognition and Artificial Intelligence10.1145/3558884.3558904(1-10)Online publication date: 19-Sep-2022
https://dl.acm.org/doi/10.1145/3558884.3558904
von Wilmsdorff JKolf JKuijper A(2022)Reducing Deployment Cost for Passive Electric Field SensorsProceedings of the 7th International Workshop on Sensor-based Activity Recognition and Artificial Intelligence10.1145/3558884.3558886(1-8)Online publication date: 19-Sep-2022
https://dl.acm.org/doi/10.1145/3558884.3558886
Almuteb IHua RWang Y(2022)Smart insoles review (2008-2021): Applications, potentials, and futureSmart Health10.1016/j.smhl.2022.10030125(100301)Online publication date: Sep-2022
https://doi.org/10.1016/j.smhl.2022.100301
Bello HZhou BSuh SLukowicz P(2021)MoCapaci: Posture and gesture detection in loose garments using textile cables as capacitive antennasProceedings of the 2021 ACM International Symposium on Wearable Computers10.1145/3460421.3480418(78-83)Online publication date: 21-Sep-2021
https://dl.acm.org/doi/10.1145/3460421.3480418
Matthies DWeerasinghe CUrban BNanayakkara S(2021)CapGlasses: Untethered Capacitive Sensing with Smart GlassesProceedings of the Augmented Humans International Conference 202110.1145/3458709.3458945(121-130)Online publication date: 22-Feb-2021
https://dl.acm.org/doi/10.1145/3458709.3458945
Elvitigala DMatthies DNanayakkara S(2020)StressFoot: Uncovering the Potential of the Foot for Acute Stress Sensing in Sitting PostureSensors10.3390/s2010288220:10(2882)Online publication date: 19-May-2020
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