Gait Segmentation and Grouping in Daily Data Collected from Wearable IMU Sensors-Reference-Cited by-同舟云学术

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Gait Segmentation and Grouping in Daily Data Collected from Wearable IMU Sensors

Published:2023-11-15 Issue: Volume: Page:
ISSN:
Container-title:ECSA 2023
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Author:

Wang Zhuoli¹,Xia Chengshuo²,Sugiura Yuta³

Affiliation:

1. Graduate School of Science and Technology, Keio University, Yokohama 223-8522, Japan

2. Advanced Manufacturing Technology Innovation Center, Guangzhou Institute of Technology, Xidian University, Guangzhou 510555, China

3. Department of Information and Computer Science, Faculty of Science and Technology, Keio University, Yokohama 223-8522, Japan

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/58/1/46/pdf

Reference14 articles.

1. Gait quantification and visualization for digital healthcare;Anwary;Health Policy Technol.,2020

2. Gait Changes in Older Adults: Predictors of Falls or Indicators of Fear?;Maki;J. Am. Geriatr. Soc.,1997

3. Stride segmentation of inertial sensor data using statistical methods for different walking activities;Jain;Robotica,2022

4. Gujarathi, T., and Bhole, K. (2019, January 6–8). Gait analysis using imu sensor. Proceedings of the 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Kanpur, India.

5. Detection of gait from continuous inertial sensor data using harmonic frequencies;Ullrich;IEEE J. Biomed. Health Inf.,2020

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