Human machine interaction using zero force sensing switches incorporating self-adaptation

Martin Langner; David A. Sanders; Giles Tewkesbury; Shikun Zhou; Malik Haddad

doi:10.1007/978-3-031-25191-7_20

Human machine interaction using zero force sensing switches incorporating self-adaptation

Martin Langner, David A. Sanders, Giles Tewkesbury, Shikun Zhou, Malik Haddad

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 Downloads (Pure)

Abstract

A novel human machine interface is presented that ‘self-adapts’ to accommodate for changes in position between an operator and a non-contact sensor. Zero force sensing has been especially suitable for people with small amounts of movement force that has made switch operation difficult or impossible. A common issue with existing switches concerned maintaining a workable operating position for a user. Testing of new “auto adapting” sensors demonstrated the viability of the approach and optical sensors provided a workable solution, but problems were encountered in strong light. Further work addressed this problem.

Original language	English
Title of host publication	Biomedical and Computational Biology
Subtitle of host publication	Second International Symposium, BECB 2022, Virtual Event, August 13–15, 2022, Revised Selected Papers
Editors	Shiping Wen, Cihui Yang
Publisher	Springer
Pages	256-264
Number of pages	9
ISBN (Electronic)	9783031251917
ISBN (Print)	9783031251900
DOIs	https://doi.org/10.1007/978-3-031-25191-7_20 https://doi.org/10.1007/978-3-031-25191-7_20
Publication status	Published - 2 Feb 2023
Event	2nd International Symposium on Biomedical and Computational Biology, BECB 2022 - Virtual, Online Duration: 13 Aug 2022 → 15 Aug 2022

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Nature
Volume	13637
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Symposium on Biomedical and Computational Biology, BECB 2022
City	Virtual, Online
Period	13/08/22 → 15/08/22

Keywords

assistive technology
human machine interaction
powered mobility
zero force sensing

Access to Document

Human_machine_interaction_AAMAccepted author manuscript (Post-print), 443 KB

Using artificial intelligence to share control of a powered-wheelchair between a wheelchair user and an intelligent sensor system
Sanders, D., Gegov, A. & Haddad, M.
Engineering and Physical Sciences Research Council
1/11/18 → 1/11/22
Project: Research

File

Presentation to the 2nd International Symposium on Automation, Information and Computing
Malik Haddad (Speaker)
6 Dec 2021
Activity: Talk or presentation types › Oral presentation

Cite this

Langner, M., Sanders, D. A., Tewkesbury, G., Zhou, S., & Haddad, M. (2023). Human machine interaction using zero force sensing switches incorporating self-adaptation. In S. Wen, & C. Yang (Eds.), Biomedical and Computational Biology: Second International Symposium, BECB 2022, Virtual Event, August 13–15, 2022, Revised Selected Papers (pp. 256-264). (Lecture Notes in Computer Science; Vol. 13637). Springer. https://doi.org/10.1007/978-3-031-25191-7_20, https://doi.org/10.1007/978-3-031-25191-7_20

Langner, Martin ; Sanders, David A. ; Tewkesbury, Giles et al. / Human machine interaction using zero force sensing switches incorporating self-adaptation. Biomedical and Computational Biology: Second International Symposium, BECB 2022, Virtual Event, August 13–15, 2022, Revised Selected Papers. editor / Shiping Wen ; Cihui Yang. Springer, 2023. pp. 256-264 (Lecture Notes in Computer Science).

@inproceedings{91cc4886a0d3460fbdd451513ecdaac7,

title = "Human machine interaction using zero force sensing switches incorporating self-adaptation",

abstract = "A novel human machine interface is presented that {\textquoteleft}self-adapts{\textquoteright} to accommodate for changes in position between an operator and a non-contact sensor. Zero force sensing has been especially suitable for people with small amounts of movement force that has made switch operation difficult or impossible. A common issue with existing switches concerned maintaining a workable operating position for a user. Testing of new “auto adapting” sensors demonstrated the viability of the approach and optical sensors provided a workable solution, but problems were encountered in strong light. Further work addressed this problem.",

keywords = "assistive technology, human machine interaction, powered mobility, zero force sensing",

author = "Martin Langner and Sanders, {David A.} and Giles Tewkesbury and Shikun Zhou and Malik Haddad",

year = "2023",

month = feb,

day = "2",

doi = "10.1007/978-3-031-25191-7_20",

language = "English",

isbn = "9783031251900",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "256--264",

editor = "Shiping Wen and Cihui Yang",

booktitle = "Biomedical and Computational Biology",

note = "2nd International Symposium on Biomedical and Computational Biology, BECB 2022 ; Conference date: 13-08-2022 Through 15-08-2022",

}

Langner, M, Sanders, DA , Tewkesbury, G , Zhou, S & Haddad, M 2023, Human machine interaction using zero force sensing switches incorporating self-adaptation. in S Wen & C Yang (eds), Biomedical and Computational Biology: Second International Symposium, BECB 2022, Virtual Event, August 13–15, 2022, Revised Selected Papers. Lecture Notes in Computer Science, vol. 13637, Springer, pp. 256-264, 2nd International Symposium on Biomedical and Computational Biology, BECB 2022, Virtual, Online, 13/08/22. https://doi.org/10.1007/978-3-031-25191-7_20, https://doi.org/10.1007/978-3-031-25191-7_20

Human machine interaction using zero force sensing switches incorporating self-adaptation. / Langner, Martin; Sanders, David A.; Tewkesbury, Giles et al.
Biomedical and Computational Biology: Second International Symposium, BECB 2022, Virtual Event, August 13–15, 2022, Revised Selected Papers. ed. / Shiping Wen; Cihui Yang. Springer, 2023. p. 256-264 (Lecture Notes in Computer Science; Vol. 13637).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Human machine interaction using zero force sensing switches incorporating self-adaptation

AU - Langner, Martin

AU - Sanders, David A.

AU - Tewkesbury, Giles

AU - Zhou, Shikun

AU - Haddad, Malik

PY - 2023/2/2

Y1 - 2023/2/2

N2 - A novel human machine interface is presented that ‘self-adapts’ to accommodate for changes in position between an operator and a non-contact sensor. Zero force sensing has been especially suitable for people with small amounts of movement force that has made switch operation difficult or impossible. A common issue with existing switches concerned maintaining a workable operating position for a user. Testing of new “auto adapting” sensors demonstrated the viability of the approach and optical sensors provided a workable solution, but problems were encountered in strong light. Further work addressed this problem.

AB - A novel human machine interface is presented that ‘self-adapts’ to accommodate for changes in position between an operator and a non-contact sensor. Zero force sensing has been especially suitable for people with small amounts of movement force that has made switch operation difficult or impossible. A common issue with existing switches concerned maintaining a workable operating position for a user. Testing of new “auto adapting” sensors demonstrated the viability of the approach and optical sensors provided a workable solution, but problems were encountered in strong light. Further work addressed this problem.

KW - assistive technology

KW - human machine interaction

KW - powered mobility

KW - zero force sensing

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UR - https://www.becbinfo.com/#/

U2 - 10.1007/978-3-031-25191-7_20

DO - 10.1007/978-3-031-25191-7_20

M3 - Conference contribution

SN - 9783031251900

T3 - Lecture Notes in Computer Science

SP - 256

EP - 264

BT - Biomedical and Computational Biology

A2 - Wen, Shiping

A2 - Yang, Cihui

PB - Springer

T2 - 2nd International Symposium on Biomedical and Computational Biology, BECB 2022

Y2 - 13 August 2022 through 15 August 2022

ER -

Langner M, Sanders DA , Tewkesbury G , Zhou S, Haddad M. Human machine interaction using zero force sensing switches incorporating self-adaptation. In Wen S, Yang C, editors, Biomedical and Computational Biology: Second International Symposium, BECB 2022, Virtual Event, August 13–15, 2022, Revised Selected Papers. Springer. 2023. p. 256-264. (Lecture Notes in Computer Science). doi: 10.1007/978-3-031-25191-7_20, 10.1007/978-3-031-25191-7_20

Human machine interaction using zero force sensing switches incorporating self-adaptation

Abstract

Publication series

Conference

Keywords

Access to Document

Projects

Using artificial intelligence to share control of a powered-wheelchair between a wheelchair user and an intelligent sensor system

Activities

Presentation to the 2nd International Symposium on Automation, Information and Computing

Cite this