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Regression Model-Based Walking Speed Estimation Using Wrist-Worn Inertial Sensor

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  • Shaghayegh Zihajehzadeh
  • Edward J Park

Abstract

Walking speed is widely used to study human health status. Wearable inertial measurement units (IMU) are promising tools for the ambulatory measurement of walking speed. Among wearable inertial sensors, the ones worn on the wrist, such as a watch or band, have relatively higher potential to be easily incorporated into daily lifestyle. Using the arm swing motion in walking, this paper proposes a regression model-based method for longitudinal walking speed estimation using a wrist-worn IMU. A novel kinematic variable is proposed, which finds the wrist acceleration in the principal axis (i.e. the direction of the arm swing). This variable (called pca-acc) is obtained by applying sensor fusion on IMU data to find the orientation followed by the use of principal component analysis. An experimental evaluation was performed on 15 healthy young subjects during free walking trials. The experimental results show that the use of the proposed pca-acc variable can significantly improve the walking speed estimation accuracy when compared to the use of raw acceleration information (p

Suggested Citation

  • Shaghayegh Zihajehzadeh & Edward J Park, 2016. "Regression Model-Based Walking Speed Estimation Using Wrist-Worn Inertial Sensor," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-16, October.
    • Handle: RePEc:plo:pone00:0165211
    DOI: 10.1371/journal.pone.0165211
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    References listed on IDEAS

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    1. Deirdre A Robertson & George M Savva & Bellinda L King-Kallimanis & Rose Anne Kenny, 2015. "Negative Perceptions of Aging and Decline in Walking Speed: A Self-Fulfilling Prophecy," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-17, April.
    2. Yoshifumi Abe & Atsuhiko Matsunaga & Ryota Matsuzawa & Toshiki Kutsuna & Shuhei Yamamoto & Kei Yoneki & Manae Harada & Ryoma Ishikawa & Takaaki Watanabe & Atsushi Yoshida, 2016. "Determinants of Slow Walking Speed in Ambulatory Patients Undergoing Maintenance Hemodialysis," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-15, March.
    3. Nicolas Bayle & Amar S Patel & Diana Crisan & Lanjun J Guo & Emilie Hutin & Donald J Weisz & Steven T Moore & Jean-Michel Gracies, 2016. "Contribution of Step Length to Increase Walking and Turning Speed as a Marker of Parkinson’s Disease Progression," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-13, April.
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    1. Hang Zhou & Jin Gao & Fan Zhang & Junxiong Zhang & Song Wang & Chunlong Zhang & Wei Li, 2023. "Evaluation of Cutting Stability of a Natural-Rubber-Tapping Robot," Agriculture, MDPI, vol. 13(3), pages 1-23, February.
    2. Delaram Jarchi & Alexander J. Casson, 2016. "Description of a Database Containing Wrist PPG Signals Recorded during Physical Exercise with Both Accelerometer and Gyroscope Measures of Motion," Data, MDPI, vol. 2(1), pages 1-13, December.
    3. Seonjeong Byun & Hyang Jun Lee & Ji Won Han & Jun Sung Kim & Euna Choi & Ki Woong Kim, 2019. "Walking-speed estimation using a single inertial measurement unit for the older adults," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-16, December.

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