Step Length Estimation with Wearable Wrist Sensor using ANN

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 2022, pp. 1125–1128

Abstract

Step Length is an important metric that can be used for the analysis and assessment of the gait. Proper dynamical models are not available in current literature associated with the wrist that can adequately determine the step length using recursive estimation techniques. This study presents a method to estimate the step length using angular velocity data from the wrist sensor. The technique maps the dynamical region corresponding to periods of activity of the gait manifested in angular velocity from the inertial measurement unit located at the wrist to that of the thigh using an artificial neural network, upon which an unscented Kalman filter is used to determine the horizontal position of the foot relative to the hip, and consequently, determine step length. The results for Step Length indicate an average accuracy of 81.8% and 91.1% for the young and elderly, respectively, when compared to a reference system, which, in our study, is data from a treadmill.

Authors 7

1. Sanjay Chandrasekaran

   ETH Zurich

   Affiliation as printed

   ETH Zurich,Department of Information Technology and Electrical Engineering,Switzerland

   Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland

2. Markus Lueken Aachen Department of Medical Information Technology

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Department of Medical Information Technology,Aachen,Germany

   Department of Medical Information Technology, RWTH Aachen University, Aachen, Germany

3. Steffen K. Leonhardt Aachen Department of Medical Information Technology

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Department of Medical Information Technology,Aachen,Germany

   Department of Medical Information Technology, RWTH Aachen University, Aachen, Germany

4. Uma Gandhi

   National Institute of Technology Tiruchirappalli

   Affiliation as printed

   National Institute of Technology Tiruchirappalli,Department of Instrumentation and Control Engineering

   Department of Instrumentation and Control Engineering, National Institute of Technology Tiruchirappalli

5. Thea Laurentius Aachen Chair for Geriatrics

   Universitätsklinikum Aachen

   Affiliation as printed

   University Hospital Aachen,Chair for Geriatrics,Germany

   Chair for Geriatrics, University Hospital Aachen, Germany

6. Cornelius Bollheimer Aachen Chair for Geriatrics

   Universitätsklinikum Aachen

   Affiliation as printed

   University Hospital Aachen,Chair for Geriatrics,Germany

   Chair for Geriatrics, University Hospital Aachen, Germany

7. Chuong Ngo Aachen Department of Medical Information Technology

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Department of Medical Information Technology,Aachen,Germany

   Department of Medical Information Technology, RWTH Aachen University, Aachen, Germany