Segmentation of human upper body movement using multiple IMU sensors

Takashi Aoki; Jonathan Feng Shun Lin; Dana Kulic; Gentiane Venture

doi:10.1109/EMBC.2016.7591400

Segmentation of human upper body movement using multiple IMU sensors

Takashi Aoki
, Jonathan Feng Shun Lin
, Dana Kulic
, Gentiane Venture

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

14 Citations (Scopus)

Abstract

This paper proposes an approach for the segmentation of human body movements measured by inertial measurement unit sensors. Using the angular velocity and linear acceleration measurements directly, without converting to joint angles, we perform segmentation by formulating the problem as a classification problem, and training a classifier to differentiate between motion end-point and within-motion points. The proposed approach is validated with experiments measuring the upper body movement during reaching tasks, demonstrating classification accuracy of over 85.8%.

Original language	English
Title of host publication	2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016)
Editors	Jose Principe, Jose Carmena, Justin Sanchez
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	3163-3166
Number of pages	4
ISBN (Electronic)	9781457702204
ISBN (Print)	9781457702198
DOIs	https://doi.org/10.1109/EMBC.2016.7591400
Publication status	Published - 2016
Externally published	Yes
Event	International Conference of the IEEE Engineering in Medicine and Biology Society 2016 - Walt Disney World Resort, Orlando, United States of America Duration: 16 Aug 2016 → 20 Aug 2016 Conference number: 38th https://embc.embs.org/2016/ https://ieeexplore.ieee.org/xpl/conhome/7580725/proceeding (Proceedings)

Conference

Conference	International Conference of the IEEE Engineering in Medicine and Biology Society 2016
Abbreviated title	EMBC 2016
Country/Territory	United States of America
City	Orlando
Period	16/08/16 → 20/08/16
Internet address	https://embc.embs.org/2016/ https://ieeexplore.ieee.org/xpl/conhome/7580725/proceeding (Proceedings)

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10.1109/EMBC.2016.7591400

Cite this

Aoki, T., Lin, J. F. S., Kulic, D., & Venture, G. (2016). Segmentation of human upper body movement using multiple IMU sensors. In J. Principe, J. Carmena, & J. Sanchez (Eds.), 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016) (pp. 3163-3166). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EMBC.2016.7591400

Aoki, Takashi ; Lin, Jonathan Feng Shun ; Kulic, Dana et al. / Segmentation of human upper body movement using multiple IMU sensors. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016) . editor / Jose Principe ; Jose Carmena ; Justin Sanchez. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2016. pp. 3163-3166

@inproceedings{4a0cd5f890b648e8bbe1d6f46773963c,

title = "Segmentation of human upper body movement using multiple IMU sensors",

abstract = "This paper proposes an approach for the segmentation of human body movements measured by inertial measurement unit sensors. Using the angular velocity and linear acceleration measurements directly, without converting to joint angles, we perform segmentation by formulating the problem as a classification problem, and training a classifier to differentiate between motion end-point and within-motion points. The proposed approach is validated with experiments measuring the upper body movement during reaching tasks, demonstrating classification accuracy of over 85.8\%.",

author = "Takashi Aoki and Lin, \{Jonathan Feng Shun\} and Dana Kulic and Gentiane Venture",

year = "2016",

doi = "10.1109/EMBC.2016.7591400",

language = "English",

isbn = "9781457702198",

pages = "3163--3166",

editor = "Jose Principe and Jose Carmena and Justin Sanchez",

booktitle = "2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016)",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "International Conference of the IEEE Engineering in Medicine and Biology Society 2016, EMBC 2016 ; Conference date: 16-08-2016 Through 20-08-2016",

url = "https://embc.embs.org/2016/, https://ieeexplore.ieee.org/xpl/conhome/7580725/proceeding",

}

Aoki, T, Lin, JFS, Kulic, D & Venture, G 2016, Segmentation of human upper body movement using multiple IMU sensors. in J Principe, J Carmena & J Sanchez (eds), 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016) . IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 3163-3166, International Conference of the IEEE Engineering in Medicine and Biology Society 2016, Orlando, Florida, United States of America, 16/08/16. https://doi.org/10.1109/EMBC.2016.7591400

Segmentation of human upper body movement using multiple IMU sensors. / Aoki, Takashi; Lin, Jonathan Feng Shun; Kulic, Dana et al.
2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016) . ed. / Jose Principe; Jose Carmena; Justin Sanchez. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2016. p. 3163-3166.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

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AU - Aoki, Takashi

AU - Lin, Jonathan Feng Shun

AU - Kulic, Dana

AU - Venture, Gentiane

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PY - 2016

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N2 - This paper proposes an approach for the segmentation of human body movements measured by inertial measurement unit sensors. Using the angular velocity and linear acceleration measurements directly, without converting to joint angles, we perform segmentation by formulating the problem as a classification problem, and training a classifier to differentiate between motion end-point and within-motion points. The proposed approach is validated with experiments measuring the upper body movement during reaching tasks, demonstrating classification accuracy of over 85.8%.

AB - This paper proposes an approach for the segmentation of human body movements measured by inertial measurement unit sensors. Using the angular velocity and linear acceleration measurements directly, without converting to joint angles, we perform segmentation by formulating the problem as a classification problem, and training a classifier to differentiate between motion end-point and within-motion points. The proposed approach is validated with experiments measuring the upper body movement during reaching tasks, demonstrating classification accuracy of over 85.8%.

UR - https://www.scopus.com/pages/publications/85009070683

U2 - 10.1109/EMBC.2016.7591400

DO - 10.1109/EMBC.2016.7591400

M3 - Conference Paper

C2 - 28268979

AN - SCOPUS:85009070683

SN - 9781457702198

SP - 3163

EP - 3166

BT - 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016)

A2 - Principe, Jose

A2 - Carmena, Jose

A2 - Sanchez, Justin

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

T2 - International Conference of the IEEE Engineering in Medicine and Biology Society 2016

Y2 - 16 August 2016 through 20 August 2016

ER -

Aoki T, Lin JFS, Kulic D, Venture G. Segmentation of human upper body movement using multiple IMU sensors. In Principe J, Carmena J, Sanchez J, editors, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016) . Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2016. p. 3163-3166 doi: 10.1109/EMBC.2016.7591400

Segmentation of human upper body movement using multiple IMU sensors

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