Gait Phase Recognition using Textile-based Sensor

Abdulkadir Pazar; Fidan Khalilbayli; Kadir Ozlem; Ayse Feyza Yilmaz; Asli Tuncay Atalay; Ozgur Atalay; Gokhan Ince

doi:10.1109/UBMK55850.2022.9919491

Gait Phase Recognition using Textile-based Sensor

Abdulkadir Pazar, Fidan Khalilbayli, Kadir Ozlem, Ayse Feyza Yilmaz, Asli Tuncay Atalay, Ozgur Atalay, Gokhan Ince

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

3 Atıf (Scopus)

Özet

Human gait phase detection has become an emerging field of study due to its impact in various clinical studies. In this study, a system is developed to detect the toe-off, mid-swing, heel-strike, and heel-off phases of a gait cycle in real-time by using a textile-based capacitive strain sensor mounted on the kneepad. Five healthy subjects performed walks including those four phases of the gait at a constant speed and gait distance in a laboratory environment while wearing the kneepad. The phases are labeled according to the gyroscope data of the Inertial Measurement Unit (IMU) located on the kneepad. An Long Short-Term Memory (LSTM) based network is utilized to detect the phases using the capacitance data obtained from the strain sensor. Recognition of four phases with 87 % accuracy is accomplished.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	338-343
Sayfa sayısı	6
ISBN (Elektronik)	9781665470100
DOI'lar	https://doi.org/10.1109/UBMK55850.2022.9919491
Yayın durumu	Yayınlandı - 2022
Etkinlik	7th International Conference on Computer Science and Engineering, UBMK 2022 - Diyarbakir, Turkey Süre: 14 Eyl 2022 → 16 Eyl 2022

Yayın serisi

Adı	Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	7th International Conference on Computer Science and Engineering, UBMK 2022
Ülke/Bölge	Turkey
Şehir	Diyarbakir
Periyot	14/09/22 → 16/09/22

Bibliyografik not

Publisher Copyright:
© 2022 IEEE.

Finansman

VII. ACKNOWLEDGEMENTS The authors disclose the receipt of the following financial support for research and authorship. This work was funded by Scientific and Technological Research Council of Turkey (TUBITAK) Research Grant No:120C118.

Finansörler	Finansör numarası
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu	:120C118

Belgeye Erişim

10.1109/UBMK55850.2022.9919491

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Pazar, A., Khalilbayli, F., Ozlem, K., Yilmaz, A. F., Atalay, A. T., Atalay, O., & Ince, G. (2022). Gait Phase Recognition using Textile-based Sensor. In Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022 (pp. 338-343). (Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/UBMK55850.2022.9919491

Pazar, Abdulkadir ; Khalilbayli, Fidan ; Ozlem, Kadir et al. / Gait Phase Recognition using Textile-based Sensor. Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 338-343 (Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022).

@inproceedings{3aef206d4eb14f768cf3fbb46f136828,

title = "Gait Phase Recognition using Textile-based Sensor",

abstract = "Human gait phase detection has become an emerging field of study due to its impact in various clinical studies. In this study, a system is developed to detect the toe-off, mid-swing, heel-strike, and heel-off phases of a gait cycle in real-time by using a textile-based capacitive strain sensor mounted on the kneepad. Five healthy subjects performed walks including those four phases of the gait at a constant speed and gait distance in a laboratory environment while wearing the kneepad. The phases are labeled according to the gyroscope data of the Inertial Measurement Unit (IMU) located on the kneepad. An Long Short-Term Memory (LSTM) based network is utilized to detect the phases using the capacitance data obtained from the strain sensor. Recognition of four phases with 87 % accuracy is accomplished.",

keywords = "Gait Analysis, Inertial Measurement Unit, Long Short-Term Memory, Real-time Gait Phase Recognition, Textile-based Strain Sensor",

author = "Abdulkadir Pazar and Fidan Khalilbayli and Kadir Ozlem and Yilmaz, {Ayse Feyza} and Atalay, {Asli Tuncay} and Ozgur Atalay and Gokhan Ince",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 7th International Conference on Computer Science and Engineering, UBMK 2022 ; Conference date: 14-09-2022 Through 16-09-2022",

year = "2022",

doi = "10.1109/UBMK55850.2022.9919491",

language = "English",

series = "Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "338--343",

booktitle = "Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022",

address = "United States",

}

Pazar, A, Khalilbayli, F, Ozlem, K, Yilmaz, AF, Atalay, AT , Atalay, O & Ince, G 2022, Gait Phase Recognition using Textile-based Sensor. in Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022. Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022, Institute of Electrical and Electronics Engineers Inc., pp. 338-343, 7th International Conference on Computer Science and Engineering, UBMK 2022, Diyarbakir, Turkey, 14/09/22. https://doi.org/10.1109/UBMK55850.2022.9919491

Gait Phase Recognition using Textile-based Sensor. / Pazar, Abdulkadir; Khalilbayli, Fidan; Ozlem, Kadir et al.
Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 338-343 (Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022).

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

TY - GEN

T1 - Gait Phase Recognition using Textile-based Sensor

AU - Pazar, Abdulkadir

AU - Khalilbayli, Fidan

AU - Ozlem, Kadir

AU - Yilmaz, Ayse Feyza

AU - Atalay, Asli Tuncay

AU - Atalay, Ozgur

AU - Ince, Gokhan

PY - 2022

Y1 - 2022

N2 - Human gait phase detection has become an emerging field of study due to its impact in various clinical studies. In this study, a system is developed to detect the toe-off, mid-swing, heel-strike, and heel-off phases of a gait cycle in real-time by using a textile-based capacitive strain sensor mounted on the kneepad. Five healthy subjects performed walks including those four phases of the gait at a constant speed and gait distance in a laboratory environment while wearing the kneepad. The phases are labeled according to the gyroscope data of the Inertial Measurement Unit (IMU) located on the kneepad. An Long Short-Term Memory (LSTM) based network is utilized to detect the phases using the capacitance data obtained from the strain sensor. Recognition of four phases with 87 % accuracy is accomplished.

AB - Human gait phase detection has become an emerging field of study due to its impact in various clinical studies. In this study, a system is developed to detect the toe-off, mid-swing, heel-strike, and heel-off phases of a gait cycle in real-time by using a textile-based capacitive strain sensor mounted on the kneepad. Five healthy subjects performed walks including those four phases of the gait at a constant speed and gait distance in a laboratory environment while wearing the kneepad. The phases are labeled according to the gyroscope data of the Inertial Measurement Unit (IMU) located on the kneepad. An Long Short-Term Memory (LSTM) based network is utilized to detect the phases using the capacitance data obtained from the strain sensor. Recognition of four phases with 87 % accuracy is accomplished.

KW - Gait Analysis

KW - Inertial Measurement Unit

KW - Long Short-Term Memory

KW - Real-time Gait Phase Recognition

KW - Textile-based Strain Sensor

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U2 - 10.1109/UBMK55850.2022.9919491

DO - 10.1109/UBMK55850.2022.9919491

M3 - Conference contribution

AN - SCOPUS:85141834680

T3 - Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022

SP - 338

EP - 343

BT - Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th International Conference on Computer Science and Engineering, UBMK 2022

Y2 - 14 September 2022 through 16 September 2022

ER -

Pazar A, Khalilbayli F, Ozlem K, Yilmaz AF, Atalay AT , Atalay O et al. Gait Phase Recognition using Textile-based Sensor. In Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 338-343. (Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022). doi: 10.1109/UBMK55850.2022.9919491

Gait Phase Recognition using Textile-based Sensor

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Bibliyografik not

Finansman

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