Investigating running gait using a shoe-integrated wireless inertial sensor

Di-Kiat Chew; Darwin Gouwanda; Alpha Agape Gopalai

doi:10.1109/TENCON.2015.7373054

Investigating running gait using a shoe-integrated wireless inertial sensor

Malaysia School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

2 Citations (Scopus)

Abstract

Inertial sensor have been widely used to analyze human walking, but only few studies used inertial sensor to analyze running gait. This paper presented the use of inertial sensor to identify running gait phases and to estimate running speed. An experimental study were conducted to validate the feasibility of this approach. In this experiment, sensor were positioned on top of the third metatarsal of the foot. Subjects were requested to run at 8 km/h - 11 km/h. Raw acceleration and angular velocity were recorded. An off-phase segmentation was then employed to segment the running sequence into individual stride. The orientation of the foot was determined through integration and the running speed was estimated by integrating the acceleration data. The results were satisfactory. The root mean square error (RMSE) were found to be ranging between 4.54 and 5.59 for all the estimated running speed.

Original language	English
Title of host publication	Proceedings of the IEEE TENCON 2015
Editors	Keng Weng Lao
Place of Publication	New Jersey USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Number of pages	6
ISBN (Print)	9781479986415
DOIs	https://doi.org/10.1109/TENCON.2015.7373054
Publication status	Published - 2015
Event	IEEE Tencon (IEEE Region 10 Conference) 2015 - Holiday Inn Sands Cotai Central, Macau, China Duration: 1 Nov 2015 → 4 Nov 2015 Conference number: 35th https://ieeexplore.ieee.org/xpl/conhome/7365563/proceeding (Proceedings) http://www.ieeer10.org/meeting/Macau%20Section%20-%20TENCON%202015.pdf

Conference

Conference	IEEE Tencon (IEEE Region 10 Conference) 2015
Abbreviated title	TENCON 2015
Country/Territory	China
City	Macau
Period	1/11/15 → 4/11/15
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7365563/proceeding (Proceedings) http://www.ieeer10.org/meeting/Macau%20Section%20-%20TENCON%202015.pdf

Access to Document

10.1109/TENCON.2015.7373054

Best Paper Award - "Investigating running gait using a shoe-integrated wireless inertial sensor"
Gouwanda, D. (Recipient), 2015
Prize: Prize (including medals and awards)

Cite this

@inproceedings{3562f520754b455b929bc3eef5de8dfa,

title = "Investigating running gait using a shoe-integrated wireless inertial sensor",

abstract = "Inertial sensor have been widely used to analyze human walking, but only few studies used inertial sensor to analyze running gait. This paper presented the use of inertial sensor to identify running gait phases and to estimate running speed. An experimental study were conducted to validate the feasibility of this approach. In this experiment, sensor were positioned on top of the third metatarsal of the foot. Subjects were requested to run at 8 km/h - 11 km/h. Raw acceleration and angular velocity were recorded. An off-phase segmentation was then employed to segment the running sequence into individual stride. The orientation of the foot was determined through integration and the running speed was estimated by integrating the acceleration data. The results were satisfactory. The root mean square error (RMSE) were found to be ranging between 4.54 and 5.59 for all the estimated running speed.",

author = "Di-Kiat Chew and Darwin Gouwanda and \{Agape Gopalai\}, Alpha",

year = "2015",

doi = "10.1109/TENCON.2015.7373054",

language = "English",

isbn = "9781479986415",

editor = "Lao, \{Keng Weng\}",

booktitle = "Proceedings of the IEEE TENCON 2015",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "IEEE Tencon (IEEE Region 10 Conference) 2015, TENCON 2015 ; Conference date: 01-11-2015 Through 04-11-2015",

url = "https://ieeexplore.ieee.org/xpl/conhome/7365563/proceeding, http://www.ieeer10.org/meeting/Macau\%20Section\%20-\%20TENCON\%202015.pdf",

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Chew, D-K, Gouwanda, D & Agape Gopalai, A 2015, Investigating running gait using a shoe-integrated wireless inertial sensor. in KW Lao (ed.), Proceedings of the IEEE TENCON 2015., 7373054, IEEE, Institute of Electrical and Electronics Engineers, New Jersey USA, IEEE Tencon (IEEE Region 10 Conference) 2015, Macau, China, 1/11/15. https://doi.org/10.1109/TENCON.2015.7373054

Investigating running gait using a shoe-integrated wireless inertial sensor. / Chew, Di-Kiat; Gouwanda, Darwin ; Agape Gopalai, Alpha.
Proceedings of the IEEE TENCON 2015. ed. / Keng Weng Lao. New Jersey USA: IEEE, Institute of Electrical and Electronics Engineers, 2015. 7373054.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Investigating running gait using a shoe-integrated wireless inertial sensor

AU - Chew, Di-Kiat

AU - Gouwanda, Darwin

AU - Agape Gopalai, Alpha

N1 - Conference code: 35th

PY - 2015

Y1 - 2015

N2 - Inertial sensor have been widely used to analyze human walking, but only few studies used inertial sensor to analyze running gait. This paper presented the use of inertial sensor to identify running gait phases and to estimate running speed. An experimental study were conducted to validate the feasibility of this approach. In this experiment, sensor were positioned on top of the third metatarsal of the foot. Subjects were requested to run at 8 km/h - 11 km/h. Raw acceleration and angular velocity were recorded. An off-phase segmentation was then employed to segment the running sequence into individual stride. The orientation of the foot was determined through integration and the running speed was estimated by integrating the acceleration data. The results were satisfactory. The root mean square error (RMSE) were found to be ranging between 4.54 and 5.59 for all the estimated running speed.

AB - Inertial sensor have been widely used to analyze human walking, but only few studies used inertial sensor to analyze running gait. This paper presented the use of inertial sensor to identify running gait phases and to estimate running speed. An experimental study were conducted to validate the feasibility of this approach. In this experiment, sensor were positioned on top of the third metatarsal of the foot. Subjects were requested to run at 8 km/h - 11 km/h. Raw acceleration and angular velocity were recorded. An off-phase segmentation was then employed to segment the running sequence into individual stride. The orientation of the foot was determined through integration and the running speed was estimated by integrating the acceleration data. The results were satisfactory. The root mean square error (RMSE) were found to be ranging between 4.54 and 5.59 for all the estimated running speed.

U2 - 10.1109/TENCON.2015.7373054

DO - 10.1109/TENCON.2015.7373054

M3 - Conference Paper

SN - 9781479986415

BT - Proceedings of the IEEE TENCON 2015

A2 - Lao, Keng Weng

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - New Jersey USA

T2 - IEEE Tencon (IEEE Region 10 Conference) 2015

Y2 - 1 November 2015 through 4 November 2015

ER -

Investigating running gait using a shoe-integrated wireless inertial sensor

Abstract

Conference

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Prizes

Best Paper Award - "Investigating running gait using a shoe-integrated wireless inertial sensor"

Cite this