Literature DB >> 23529073

A kinematic human-walking model for the normal-gait-speed estimation using tri-axial acceleration signals at waist location.

Jwu-Sheng Hu1, Kuan-Chun Sun, Chi-Yuan Cheng.   

Abstract

This study aims at estimating the human walking speed using wearable accelerometers by proposing a novel virtual inverted pendulum model. This model not only keeps the important characteristics of both the biped rolling-foot and the inverted pendulum model, but also makes the speed estimation feasible using human body acceleration. Rather than using statistical methods, the proposed kinematic walking model enables calibration of the parameters during walking using only one tri-axial accelerometer on the waist that collects the user's body acceleration. In addition, this model also includes the effect of rotation of the waist within a walking cycle, which improves the estimation accuracy. Experimental results for a group of humans show a 0.58% absolute error mean and 0.72% error deviation, which is far better than the results of other known studies with accelerometers mounted on the upper body.

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Year:  2013        PMID: 23529073     DOI: 10.1109/TBME.2013.2252345

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  6 in total

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

Authors:  Shaghayegh Zihajehzadeh; Edward J Park
Journal:  PLoS One       Date:  2016-10-20       Impact factor: 3.240

2.  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

3.  Walking-speed estimation using a single inertial measurement unit for the older adults.

Authors:  Seonjeong Byun; Hyang Jun Lee; Ji Won Han; Jun Sung Kim; Euna Choi; Ki Woong Kim
Journal:  PLoS One       Date:  2019-12-26       Impact factor: 3.240

4.  Running Speed Estimation Using Shoe-Worn Inertial Sensors: Direct Integration, Linear, and Personalized Model.

Authors:  Mathieu Falbriard; Abolfazl Soltani; Kamiar Aminian
Journal:  Front Sports Act Living       Date:  2021-03-18

5.  Development of a gait speed estimation model for healthy older adults using a single inertial measurement unit.

Authors:  Hyang Jun Lee; Ji Sun Park; Jong Bin Bae; Ji Won Han; Ki Woong Kim
Journal:  PLoS One       Date:  2022-10-06       Impact factor: 3.752

6.  Human Body Mixed Motion Pattern Recognition Method Based on Multi-Source Feature Parameter Fusion.

Authors:  Jiyuan Song; Aibin Zhu; Yao Tu; Yingxu Wang; Muhammad Affan Arif; Huang Shen; Zhitao Shen; Xiaodong Zhang; Guangzhong Cao
Journal:  Sensors (Basel)       Date:  2020-01-18       Impact factor: 3.576

  6 in total

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