Literature DB >> 20185136

Walking speed estimation using a shank-mounted inertial measurement unit.

Q Li1, M Young, V Naing, J M Donelan.   

Abstract

We studied the feasibility of estimating walking speed using a shank-mounted inertial measurement unit. Our approach took advantage of the inverted pendulum-like behavior of the stance leg during walking to identify a new method for dividing up walking into individual stride cycles and estimating the initial conditions for the direct integration of the accelerometer and gyroscope signals. To test its accuracy, we compared speed estimates to known values during walking overground and on a treadmill. The speed estimation method worked well across treadmill speeds and slopes yielding a root mean square speed estimation error of only 7%. It also worked well during overground walking with a 4% error in the estimated travel distance. This accuracy is comparable to that achieved from foot-mounted sensors, providing an alternative in sensor positioning for walking speed estimation. Shank mounted sensors may be of great benefit for estimating speed in walking with abnormal foot motion and for the embedded control of knee-mounted devices such as prostheses and energy harvesters. Copyright 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20185136     DOI: 10.1016/j.jbiomech.2010.01.031

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  17 in total

1.  Inertial sensors in estimating walking speed and inclination: an evaluation of sensor error models.

Authors:  Shuozhi Yang; Annemarie Laudanski; Qingguo Li
Journal:  Med Biol Eng Comput       Date:  2012-03-15       Impact factor: 2.602

2.  Modeling the Kinematics of Human Locomotion Over Continuously Varying Speeds and Inclines.

Authors:  Kyle R Embry; Dario J Villarreal; Rebecca L Macaluso; Robert D Gregg
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2018-11-05       Impact factor: 3.802

3.  Analysis of Continuously Varying Kinematics for Prosthetic Leg Control Applications.

Authors:  Kyle R Embry; Robert D Gregg
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2021-03-01       Impact factor: 3.802

Review 4.  Gait metrics analysis utilizing single-point inertial measurement units: a systematic review.

Authors:  Ralph Jasper Mobbs; Jordan Perring; Suresh Mahendra Raj; Monish Maharaj; Nicole Kah Mun Yoong; Luke Wicent Sy; Rannulu Dineth Fonseka; Pragadesh Natarajan; Wen Jie Choy
Journal:  Mhealth       Date:  2022-01-20

5.  Activity recognition using a single accelerometer placed at the wrist or ankle.

Authors:  Andrea Mannini; Stephen S Intille; Mary Rosenberger; Angelo M Sabatini; William Haskell
Journal:  Med Sci Sports Exerc       Date:  2013-11       Impact factor: 5.411

6.  Measurement of foot placement and its variability with inertial sensors.

Authors:  John R Rebula; Lauro V Ojeda; Peter G Adamczyk; Arthur D Kuo
Journal:  Gait Posture       Date:  2013-06-26       Impact factor: 2.840

Review 7.  Inertial sensor-based methods in walking speed estimation: a systematic review.

Authors:  Shuozhi Yang; Qingguo Li
Journal:  Sensors (Basel)       Date:  2012-05-10       Impact factor: 3.576

8.  Ambulatory Assessment of Instantaneous Velocity during Walking Using Inertial Sensor Measurements.

Authors:  Angelo Maria Sabatini; Andrea Mannini
Journal:  Sensors (Basel)       Date:  2016-12-21       Impact factor: 3.576

9.  Gait Variability Using Waist- and Ankle-Worn Inertial Measurement Units in Healthy Older Adults.

Authors:  Timo Rantalainen; Laura Karavirta; Henrikki Pirkola; Taina Rantanen; Vesa Linnamo
Journal:  Sensors (Basel)       Date:  2020-05-18       Impact factor: 3.576

10.  Slope estimation during normal walking using a shank-mounted inertial sensor.

Authors:  Antonio M López; Diego Álvarez; Rafael C González; Juan C Álvarez
Journal:  Sensors (Basel)       Date:  2012-08-29       Impact factor: 3.576

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