TY - GEN
T1 - Reliability of stride length estimation in self-pace and brisk walking with an inertial measurement unit on shank
AU - Kasai, R.
AU - Kodama, T.
AU - Gu, Z.
AU - Zhang, D.
AU - Kong, W.
AU - Cosentino, S.
AU - Sessa, S.
AU - Kawakami, Y.
AU - Takanishi, A.
N1 - Funding Information:
This research has been supported by the JSPS Grant-in-Aid for Young Scientists (Wakate B) [15K21437]. The present work was also supported in part by the Program for Leading Graduate Schools, `Graduate Program for Embodiment Informatics'' of the Ministry of Education, Culture, Sports, Science and Technology. The authors would like to express their thanks to the Italian Ministry of Foreign Affairs, General Directorate for Cultural Promotion and Cooperation for its support to RoboCasa; Waseda University Program for Leading Graduate Schools; Tokyo Women’s Medical University/Waseda University Joint Institution for Advanced Biomedical Sciences (TWIns); and International Center for Science and Engineering Programs (ICSEP) of Waseda University. The authors would also like to express their gratitude to STMicroelectronics, Life Performance Research, Okino Industries LTD, Japan ROBOTECH LTD, SolidWorks Corp, Dyden, Kyoto Kagaku Co. Ltd., and Asahi Kasei for their support to the research.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/23
Y1 - 2017/8/23
N2 - The use of Inertial Measurement Unit (IMU) for gait analysis is gaining popularity because of its advantages of low cost and non-limited workspace. In this context, researchers are focusing on methods for automated data analysis. For example, many algorithms for stride length estimation have been developed. These algorithms rely on event detection to compute gait parameters during walking and on orientation estimation for a more precise double integration of acceleration. However, at the present, there is not comparison between existing algorithms, and the applicability of each algorithm for different walking patterns is not clear. In this paper, we studied the effect on the stride length estimation using three different techniques of event detection and two techniques of orientation estimation, by using an IMU on the lateral side of shank above the ankle. In total 6 patterns of stride estimation algorithms were compared on different walking patterns of normal and brisk walking. We evaluated the techniques in terms of precision, accuracy, and shape of the histogram of the stride estimation error.
AB - The use of Inertial Measurement Unit (IMU) for gait analysis is gaining popularity because of its advantages of low cost and non-limited workspace. In this context, researchers are focusing on methods for automated data analysis. For example, many algorithms for stride length estimation have been developed. These algorithms rely on event detection to compute gait parameters during walking and on orientation estimation for a more precise double integration of acceleration. However, at the present, there is not comparison between existing algorithms, and the applicability of each algorithm for different walking patterns is not clear. In this paper, we studied the effect on the stride length estimation using three different techniques of event detection and two techniques of orientation estimation, by using an IMU on the lateral side of shank above the ankle. In total 6 patterns of stride estimation algorithms were compared on different walking patterns of normal and brisk walking. We evaluated the techniques in terms of precision, accuracy, and shape of the histogram of the stride estimation error.
KW - Double integration
KW - Gait analysis
KW - IMU
KW - R-adaptive
KW - Stride length estimation
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U2 - 10.1109/ICMA.2017.8015896
DO - 10.1109/ICMA.2017.8015896
M3 - Conference contribution
AN - SCOPUS:85030308225
T3 - 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017
SP - 671
EP - 676
BT - 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE International Conference on Mechatronics and Automation, ICMA 2017
Y2 - 6 August 2017 through 9 August 2017
ER -