Construction of Kinect-Based   Measuring and Monitoring System for the Degree of Employee’s Fatigue

Jinhua She; Hitoshi Nakamura; Junya Imani; Yasuhiro Ohyama

doi:10.20965/jaciii.2014.p0056

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JACIII Vol.18 No.1 pp. 56-61

doi: 10.20965/jaciii.2014.p0056

(2014)

Paper:

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Construction of Kinect-Based Measuring and Monitoring System for the Degree of Employee’s Fatigue

Jinhua She^*, Hitoshi Nakamura^**, Junya Imani^,
and Yasuhiro Ohyama^

^*School of Computer Science, Tokyo University of Technology, 1404-1 Katakura, Hachioji, Tokyo 192-0982, Japan

^**Graduate School of Bionics, Computer and Media Sciences, Tokyo University of Technology, 1404-1 Katakura, Hachioji, Tokyo 192-0982, Japan

Received:

May 22, 2013

Accepted:

November 25, 2013

Published:

January 20, 2014

Keywords:

ergometer, exercise intensity, fatigue measurement, fatigue monitoring, kinect

Abstract

In this study, we developed a new system for measuring and monitoring the degree of an employee’s fatigue. The system is comprised of an ergometer, a pulsometer, a Kinect sensor, and a computer. It records the heart rate and the 3D motion of a subject during a pedaling exercise. This system is simple, inexpensive, and easy to use. This paper explains the construction of the system, and reports the results of verification experiments with a special focus on the use of the Kinect sensor. The results show that the Kinect sensor is a useful tool for recording body movement and that the system may be used to measure and monitor the degree of fatigue.

Cite this article as:

J. She, H. Nakamura, J. Imani, and Y. Ohyama, “Construction of Kinect-Based Measuring and Monitoring System for the Degree of Employee’s Fatigue,” J. Adv. Comput. Intell. Intell. Inform., Vol.18 No.1, pp. 56-61, 2014.

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References

[1] Ministry of Health, Labour and Welfare, “The mental health policy for workplaces,”
Available at: http://www.mhlw.go.jp/english/wp/wp-hw4/dl/working_conditions_labour_relations/2011071910.pdf
[2] K. Russell, “Chapter 9: Fatigue,” in Interactive Textbook on Clinical Symptom Research, B. M. Mitchell and L. Joanne Ed.,
Available at: http://painconsortium.nih.gov/symptomresearch/tablecontents.htm
[3] Y. Watanabe, “Molecular and neural mechanisms of fatigue and fatigue sensation – For better recovery and better avoidance from exhaustion,”
Available at: http://www.hirou.jp//english/eim.html
[4] W. Ament and G. J. Verkerke, “Exercise and Fatigue,” Sports Med., Vol.39, No.5, pp. 389-422, 2009.
[5] Microsoft Corporation, KINECT for Windows,
Available at: http://www.microsoft.com/en-us/kinectforwindows/
[6] Y.-J. Chang, S.-F. Chen, and J.-D. Huang, “A Kinect-based system for physical rehabilitation: A pilot study for young adults with motor disabilities,” Research in Developmental Disabilities, Vol.32, No.6, pp. 2566-2570, Nov.-Dec., 2011.
[7] E. A. Suma, D. M. Krum, B. Lange, S. Koenig, A. Rizzo, and M. Bolas, “Adapting user interfaces for gestural interaction with the flexible action and articulated skeleton toolkit,” Computer & Graphics, Vol.37, No.3, pp. 193-201, May, 2013.
[8] J. Fabian, T. Young, J. C. P. Jones, and G. M. Clayton, “Integrating the Microsoft Kinect With Simulink: Real-Time Object Tracking Example,” IEEE/ASME Trans. Mechatronics, DOI: 10.1109/TMECH.2012.2228010, 2013.
[9] J. She, H. Nakamura, K. Makino, Y. Ohyama, H. Hashimoto, and M. Wu, “Experimental Selection and Verification of Maximum-Heart-Rate Formulas for Use with Karvonen Formula,” the 10th Int. Conf. on Informatics in Control, Automation and Robotics (ICINCO 2013), pp. 536-541, July, 2013.
[10] G. Borg, “Borg’s perceived exertion and pain scales,” Human Kinetics, Champaigne, 1998.
[11] M. J. Karvonen, E. Kentala, and O.Mustala, “The effects of training on heart rate: a longitudinal study,” Ann. Med. Exp. Biol. Fenn, Vol.35, No.3, pp. 307-315, 1957.
[12] B. R. Londeree and M. L. Moeschberger, “Effect of age and other factors on maximal heart rate,” Research Quarterly for Exercise and Sport, Vol.53, No.4, pp. 297-304, 1982.
[13] R. A. Robert and R. Landwehr, “The surprising history of the “HRmax=220-age” Equation,” J. of Exercise Physiology, Vol.5, No.2, pp. 1-10, 2002.
[14] H. Tanaka, K. D. Monahan, and D. R. Seals, “Age-predicted maximal heart rate revisited,” J. of the American College of Cardiology, Vol.37, No.1, pp. 153-156, 2001.
[15] Microsoft Corporation, “Kinect for Windows Programming Guide,”
Available at: http://msdn.microsoft.com/en-us/library/hh855348.aspx

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] Ministry of Health, Labour and Welfare, “The mental health policy for workplaces,”
Available at: http://www.mhlw.go.jp/english/wp/wp-hw4/dl/working_conditions_labour_relations/2011071910.pdf

[2] [2] K. Russell, “Chapter 9: Fatigue,” in Interactive Textbook on Clinical Symptom Research, B. M. Mitchell and L. Joanne Ed.,
Available at: http://painconsortium.nih.gov/symptomresearch/tablecontents.htm

[3] [3] Y. Watanabe, “Molecular and neural mechanisms of fatigue and fatigue sensation – For better recovery and better avoidance from exhaustion,”
Available at: http://www.hirou.jp//english/eim.html

[4] [4] W. Ament and G. J. Verkerke, “Exercise and Fatigue,” Sports Med., Vol.39, No.5, pp. 389-422, 2009.

[5] [5] Microsoft Corporation, KINECT for Windows,
Available at: http://www.microsoft.com/en-us/kinectforwindows/

[6] [6] Y.-J. Chang, S.-F. Chen, and J.-D. Huang, “A Kinect-based system for physical rehabilitation: A pilot study for young adults with motor disabilities,” Research in Developmental Disabilities, Vol.32, No.6, pp. 2566-2570, Nov.-Dec., 2011.

[7] [7] E. A. Suma, D. M. Krum, B. Lange, S. Koenig, A. Rizzo, and M. Bolas, “Adapting user interfaces for gestural interaction with the flexible action and articulated skeleton toolkit,” Computer & Graphics, Vol.37, No.3, pp. 193-201, May, 2013.

[8] [8] J. Fabian, T. Young, J. C. P. Jones, and G. M. Clayton, “Integrating the Microsoft Kinect With Simulink: Real-Time Object Tracking Example,” IEEE/ASME Trans. Mechatronics, DOI: 10.1109/TMECH.2012.2228010, 2013.

[9] [9] J. She, H. Nakamura, K. Makino, Y. Ohyama, H. Hashimoto, and M. Wu, “Experimental Selection and Verification of Maximum-Heart-Rate Formulas for Use with Karvonen Formula,” the 10th Int. Conf. on Informatics in Control, Automation and Robotics (ICINCO 2013), pp. 536-541, July, 2013.

[10] [10] G. Borg, “Borg’s perceived exertion and pain scales,” Human Kinetics, Champaigne, 1998.

[11] [11] M. J. Karvonen, E. Kentala, and O.Mustala, “The effects of training on heart rate: a longitudinal study,” Ann. Med. Exp. Biol. Fenn, Vol.35, No.3, pp. 307-315, 1957.

[12] [12] B. R. Londeree and M. L. Moeschberger, “Effect of age and other factors on maximal heart rate,” Research Quarterly for Exercise and Sport, Vol.53, No.4, pp. 297-304, 1982.

[13] [13] R. A. Robert and R. Landwehr, “The surprising history of the “HRmax=220-age” Equation,” J. of Exercise Physiology, Vol.5, No.2, pp. 1-10, 2002.

[14] [14] H. Tanaka, K. D. Monahan, and D. R. Seals, “Age-predicted maximal heart rate revisited,” J. of the American College of Cardiology, Vol.37, No.1, pp. 153-156, 2001.

[15] [15] Microsoft Corporation, “Kinect for Windows Programming Guide,”
Available at: http://msdn.microsoft.com/en-us/library/hh855348.aspx

Construction of Kinect-Based Measuring and Monitoring System for the Degree of Employee’s Fatigue

Jinhua She*, Hitoshi Nakamura**, Junya Imani*, and Yasuhiro Ohyama*

Jinhua She^*, Hitoshi Nakamura^**, Junya Imani^,
and Yasuhiro Ohyama^