Literature DB >> 29327655

Accuracy between optical and inertial motion capture systems for assessing trunk speed during preferred gait and transition periods.

Martin Kokholm Fleron1, Niels Christian Hauerbach Ubbesen1, Francesco Battistella1, David Leandro Dejtiar1, Anderson Souza Oliveira2.   

Abstract

Motion capture through inertial sensors is becoming popular, but its accuracy to describe kinematics during changes in walking speed is unknown. The aim of this study was to determine the accuracy of trunk speed extracted using an inertial motion system compared to a gold standard optical motion system, during steady walking and stationary periods. Eleven participants walked on pre-established paths marked on the floor. Between each lap, a 1-second stationary transition period at the initial position was included prior to the next lap. Resultant trunk speed during the walking and transition periods were extracted from an inertial (240 Hz sampling rate) and an optical system (120 Hz sampling rate) to calculate the agreement (Pearson's correlation coefficient) and relative root mean square errors between both systems. The agreement for the resultant trunk speed between the inertial system and the optical system was strong (0.67 < r ≤ 0.9) for both walking and transition periods. Moreover, relative root mean square error during the transition periods was greater in comparison to the walking periods (>40% across all paths). It was concluded that trunk speed extracted from inertial systems have fair accuracy during walking, but the accuracy was reduced in the transition periods.

Entities:  

Keywords:  Inertial sensors; biomechanics; kinematics; validation; walking

Mesh:

Year:  2018        PMID: 29327655     DOI: 10.1080/14763141.2017.1409259

Source DB:  PubMed          Journal:  Sports Biomech        ISSN: 1476-3141            Impact factor:   2.832


  5 in total

1.  Machine Learning Strategies for Low-Cost Insole-Based Prediction of Center of Gravity during Gait in Healthy Males.

Authors:  Jose Moon; Dongjun Lee; Hyunwoo Jung; Ahnryul Choi; Joung Hwan Mun
Journal:  Sensors (Basel)       Date:  2022-05-04       Impact factor: 3.847

2.  Quantitative Evaluation of Gait Changes Using APDM Inertial Sensors After the External Lumbar Drain in Patients With Idiopathic Normal Pressure Hydrocephalus.

Authors:  Mengmeng He; Zhenyu Qi; Yunxiang Shao; Hui Yao; Xuewen Zhang; Yang Zhang; Yu Shi; Qinzhi E; Chengming Liu; Hongwei Hu; Jiangang Liu; Xiaoou Sun; Zhong Wang; Yulun Huang
Journal:  Front Neurol       Date:  2021-07-08       Impact factor: 4.003

3.  Kinematic Profile of Visually Impaired Football Players During Specific Sports Actions.

Authors:  Sara Finocchietti; Monica Gori; Anderson Souza Oliveira
Journal:  Sci Rep       Date:  2019-07-23       Impact factor: 4.379

4.  Paddle Stroke Analysis for Kayakers Using Wearable Technologies.

Authors:  Long Liu; Hui-Hui Wang; Sen Qiu; Yun-Cui Zhang; Zheng-Dong Hao
Journal:  Sensors (Basel)       Date:  2021-01-29       Impact factor: 3.576

5.  Quaternion-Based Local Frame Alignment between an Inertial Measurement Unit and a Motion Capture System.

Authors:  Jung Keun Lee; Woo Chang Jung
Journal:  Sensors (Basel)       Date:  2018-11-16       Impact factor: 3.576

  5 in total

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