Wearable Gait Recognition Systems Based on MEMS Pressure and Inertial Sensors : A Review

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

35 Scopus Citations
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Author(s)

  • Wenchao Li
  • Wenqian Lu
  • Xiaopeng Sha
  • Hualin Xing
  • Jiazhi Lou
  • Yuliang Zhao

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)1092-1104
Journal / PublicationIEEE Sensors Journal
Volume22
Issue number2
Online published30 Nov 2021
Publication statusPublished - 15 Jan 2022

Abstract

Gait is a basic characteristic of human motion. Different gaits are usually associated with different body functions. Gait recognition has wide applications in clinical medicine, rehabilitation training, posture recognition, and other fields. At present, many wearable systems based on MEMS pressure and inertial sensors have been developed and used for gait recognition. However, there has been a lack of a comprehensive summary and comparison of these systems from the perspectives of their hardware compositions, working principles, algorithm models, and applications. This review aims to promote the development of wearable gait recognition devices. First, sensor technologies for gait measurement are summarized from the perspectives of their working principles and characteristics. Then, these technologies are compared in terms of the performance of algorithms for data preprocessing, cycle and phase segmentation, and gait recognition. Next, the applications of MEMS sensor-based gait recognition systems in various fields are summarized. Finally, some limitations of existing wearable gait recognition systems and their future directions are discussed.

Research Area(s)

  • Capacitive sensors, Gait recognition, MEMS sensor, Micromechanical devices, multi-sensor fusion, plantar pressure, Pressure sensors, Sensor phenomena and characterization, Sensor systems, Sensors

Citation Format(s)

Wearable Gait Recognition Systems Based on MEMS Pressure and Inertial Sensors: A Review. / Li, Wenchao; Lu, Wenqian; Sha, Xiaopeng et al.
In: IEEE Sensors Journal, Vol. 22, No. 2, 15.01.2022, p. 1092-1104.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review