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Title: Anatomical calibration through post-processing of standard motion tests data
Authors: Kong, Weisheng
Sessa, Salvatore
Zecca, Massimiliano
Takanishi, Atsuo
Keywords: Anatomical calibration
Sensor-to-body alignment
Functional calibration
Inertial measurement unit
Principal component analysis
Motion test
Sagittal plane
Issue Date: 2016
Publisher: MDPI / © The Authors
Citation: KONG, W. ... et al, 2016. Anatomical calibration through post-processing of standard motion tests data. Sensors, 16 (12), s16122011.
Abstract: The inertial measurement unit is popularly used as a wearable and flexible tool for human motion tracking. Sensor-to-body alignment, or anatomical calibration (AC), is fundamental to improve accuracy and reliability. Current AC methods either require extra movements or are limited to specific joints. In this research, the authors propose a novel method to achieve AC from standard motion tests (such as walking, or sit-to-stand), and compare the results with the AC obtained from specially designed movements. The proposed method uses the limited acceleration range on medial-lateral direction, and applies principal component analysis to estimate the sagittal plane, while the vertical direction is estimated from acceleration during quiet stance. The results show a good correlation between the two sets of IMUs placed on frontal/back and lateral sides of head, trunk and lower limbs. Moreover, repeatability and convergence were verified. The AC obtained from sit-to-stand and walking achieved similar results as the movements specifically designed for upper and lower body AC, respectively, except for the feet. Therefore, the experiments without AC performed can be recovered through post-processing on the walking and sit-to-stand data. Moreover, extra movements for AC can be avoided during the experiment and instead achieved through the proposed method.
Description: This is an Open Access article published by MDPI and distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/
Sponsor: This research has been supported by the JSPS Grant-in-Aid for Young Scientists (Wakate B) [15K21437] and FY2016 Grant Program for Promotion of International Joint Research of Waseda University. The present work was also supported in part by the Program for Leading Graduate Schools, Graduate Program for Embodiment Informatics of the Ministry of Education, Culture, Sports, Science and Technology. Partial support was also obtained from the UK HEFCE Catalyst grant and from the WSMEME startup grant.
Version: Published
DOI: 10.3390/s16122011
URI: https://dspace.lboro.ac.uk/2134/23618
Publisher Link: http://dx.doi.org/10.3390/s16122011
ISSN: 1424-8220
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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