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Step sequence and direction detection of four square step test

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journal contribution
posted on 2017-08-04, 08:28 authored by Weisheng Kong, Lauren Waaning, Salvatore Sessa, Massimiliano ZeccaMassimiliano Zecca, Daniele Magistro, Hikaru Takeuchi, Ryuta Kawashima, Atsuo Takanishi
Poor balance control and falls are big issues for older adults that due to aging decline have a lower postural balance and directional control in balance performance than younger age groups. The four square step test (FSST) was developed to evaluate rapid stepping that is often required when changing direction and avoiding obstacles while walking. However, previous researchers used only the total time as the assessment in the test. The aim of this letter is to objectively quantify the sequence and direction of the steps in FSST, by using two inertial sensors placed on both feet. An algorithm was developed to automatically segment the steps performed during the test, and calculate the stepping direction from the linear velocity of the foot. Experiments were conducted with 100 Japanese healthy older adults, where sensor data and video of 20 subjects were randomly subtracted for algorithm verification. The results showed that the algorithm succeeded for 71.7% trials in recognizing both the step sequence and step direction in FSST, while 90.2% of the detection failure could be excluded with an auto verification method.

Funding

This work was supported in part by the JSPS Grant-in-Aid for Young Scientists (Wakate B) [25750259] and [15K21437], in part by the Program for Leading Graduate Schools, “Graduate Program for Embodiment Informatics” of the Ministry of Education, Culture, Sports, Science and Technology, and in part by the UK-HEFCE Catalyst grant and by the LU-EESE startup grant.

History

School

  • Sport, Exercise and Health Sciences

Published in

IEEE Robotics and Automation Letters

Volume

2

Issue

4

Pages

2194-2200

Citation

KONG, W. ... et al, 2017. Step sequence and direction detection of four square step test. IEEE Robotics and Automation Letters, 2 (4), pp. 2194-2200.

Publisher

© IEEE

Version

  • AM (Accepted Manuscript)

Acceptance date

2017-06-19

Publication date

2017-07-06

Copyright date

2017

Notes

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

ISSN

2377-3766

Language

  • en