Binary classification of gait impairments using a capacitance-based sensor floor system

Solveig Najork; Laura  Liebenow; Laura Pauline Scherf; Axel Steinhage; Szymon Sieciński; Marcin Grzegorzek

doi:10.1109/IEEECONF58974.2023.10404764

Binary classification of gait impairments using a capacitance-based sensor floor system

Solveig Najork^*, Laura Liebenow, Laura Pauline Scherf, Axel Steinhage, Szymon Sieciński, Marcin Grzegorzek

^*Korrespondierende/r Autor/-in für diese Arbeit

SenseProtect GmbH

Abstract

This work investigates to what extent it is possible to detect different gait restrictions compared to normal gait using a capacitive sensory floor. For this purpose, several gait parameters and a classification using Random Decision Forest (RDF) are calculated. Furthermore, the importance of the individual features for the different classes is analyzed using Recursive Feature Elimination (RFE). In this paper, different results are visible for the classification of single gaits, but results with an accuracy of up to 90.28% have been achieved.

Originalsprache	Englisch
Seiten	105-106
Seitenumfang	2
DOIs	https://doi.org/10.1109/IEEECONF58974.2023.10404764
Publikationsstatus	Veröffentlicht - 29.01.2024
Veranstaltung	2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology - Hilton Malta, St. Julian's, Malta Dauer: 07.12.2023 → 09.12.2023 https://datascience.embs.org/2023

Tagung, Konferenz, Kongress

Tagung, Konferenz, Kongress	2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology
Land/Gebiet	Malta
Ort	St. Julian's
Zeitraum	07.12.23 → 09.12.23
Internetadresse	https://datascience.embs.org/2023

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Strategische Forschungsbereiche und Zentren

Zentren: Zentrum für Künstliche Intelligenz Lübeck (ZKIL)

DFG-Fachsystematik

2.22-32 Medizinische Physik, Biomedizinische Technik

Dokumente

10.1109/IEEECONF58974.2023.10404764

Weitere Links

https://www.mendeley.com/catalogue/0f2b82fb-a1c0-35e0-be9f-23711a26e7ba/

Zitieren

Najork, S., Liebenow, L., Scherf, L. P., Steinhage, A., Sieciński, S., & Grzegorzek, M. (2024). Binary classification of gait impairments using a capacitance-based sensor floor system. 105-106. Beitrag in 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, St. Julian's, Malta. https://doi.org/10.1109/IEEECONF58974.2023.10404764

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title = "Binary classification of gait impairments using a capacitance-based sensor floor system",

abstract = "This work investigates to what extent it is possible to detect different gait restrictions compared to normal gait using a capacitive sensory floor. For this purpose, several gait parameters and a classification using Random Decision Forest (RDF) are calculated. Furthermore, the importance of the individual features for the different classes is analyzed using Recursive Feature Elimination (RFE). In this paper, different results are visible for the classification of single gaits, but results with an accuracy of up to 90.28\% have been achieved.",

author = "Solveig Najork and Laura Liebenow and Scherf, \{Laura Pauline\} and Axel Steinhage and Szymon Sieci{\'n}ski and Marcin Grzegorzek",

year = "2024",

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day = "29",

doi = "10.1109/IEEECONF58974.2023.10404764",

language = "English",

pages = "105--106",

note = "2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology ; Conference date: 07-12-2023 Through 09-12-2023",

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Najork, S, Liebenow, L, Scherf, LP, Steinhage, A, Sieciński, S & Grzegorzek, M 2024, 'Binary classification of gait impairments using a capacitance-based sensor floor system', Beitrag in 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, St. Julian's, Malta, 07.12.23 - 09.12.23 S. 105-106. https://doi.org/10.1109/IEEECONF58974.2023.10404764

Binary classification of gait impairments using a capacitance-based sensor floor system. / Najork, Solveig; Liebenow, Laura ; Scherf, Laura Pauline et al.
2024. 105-106 Beitrag in 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, St. Julian's, Malta.

Publikation: Konferenzbeiträge › Konferenzpapiere › Begutachtung

TY - CONF

T1 - Binary classification of gait impairments using a capacitance-based sensor floor system

AU - Najork, Solveig

AU - Liebenow, Laura

AU - Scherf, Laura Pauline

AU - Steinhage, Axel

AU - Sieciński, Szymon

AU - Grzegorzek, Marcin

PY - 2024/1/29

Y1 - 2024/1/29

N2 - This work investigates to what extent it is possible to detect different gait restrictions compared to normal gait using a capacitive sensory floor. For this purpose, several gait parameters and a classification using Random Decision Forest (RDF) are calculated. Furthermore, the importance of the individual features for the different classes is analyzed using Recursive Feature Elimination (RFE). In this paper, different results are visible for the classification of single gaits, but results with an accuracy of up to 90.28% have been achieved.

AB - This work investigates to what extent it is possible to detect different gait restrictions compared to normal gait using a capacitive sensory floor. For this purpose, several gait parameters and a classification using Random Decision Forest (RDF) are calculated. Furthermore, the importance of the individual features for the different classes is analyzed using Recursive Feature Elimination (RFE). In this paper, different results are visible for the classification of single gaits, but results with an accuracy of up to 90.28% have been achieved.

UR - https://www.mendeley.com/catalogue/0f2b82fb-a1c0-35e0-be9f-23711a26e7ba/

U2 - 10.1109/IEEECONF58974.2023.10404764

DO - 10.1109/IEEECONF58974.2023.10404764

M3 - Conference Papers

SP - 105

EP - 106

T2 - 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology

Y2 - 7 December 2023 through 9 December 2023

ER -

Binary classification of gait impairments using a capacitance-based sensor floor system

Abstract

Tagung, Konferenz, Kongress

UN SDGs

Strategische Forschungsbereiche und Zentren

DFG-Fachsystematik

Dokumente

Weitere Links

Fingerprint

Zitieren