Generic placeholder image

Recent Patents on Engineering

Author(s): Zhang Su*

DOI: 10.2174/1872212113666190911115748

DownloadDownload PDF Flyer Cite As
A Multi-parameter Joint Warning Mechanism for Physical Condition Monitoring System in Physical Education

Page: [113 - 119] Pages: 7

  • * (Excluding Mailing and Handling)

Explore Articles
About Journal
For Authors
For Editors
For Reviewers

Abstract

Background: In recent years, sudden deaths of primary and secondary school students caused by sports activities have drawn great attention in education and medical circles. It is necessary for schools to monitor the physical condition of the students in order to reasonably set the duration of their physical activity. At present, the physical condition monitoring instruments used in various hospitals are expensive, bulky, and difficult to operate, and the detection process is complicated. Therefore, existing approaches cannot meet the needs of physical education teachers on campus for detecting the physical condition of students.

Methods: This study designs a portable human-physiological-state monitoring and analysis system. Real-time communication between a wearable measurement device and a monitoring device can be ensured by real-time detection of the environment and power control of the transmitted signal.

Results: From a theoretical point of view, the larger the number of segments M, the more significantly the reduction of false alarm probability. The simulation results also show this fact. Compared with the conventional early warning mechanism, the probability of a false alarm for the proposed system is lower, and the greater the number of segments, the faster its reaction speed.

Conclusion: The portable monitoring system of student physical condition for use in physical education of primary and middle school students proposed in this paper ensures real-time monitoring of the members within the system in an open environment, and further proposes an early warning mechanism for combining multiple vital sign parameters. In addition, the proposed system functions faster; the average early warning time required is only one-quarter of that of the conventional system.

Keywords: Physical condition monitoring system, multi-parameter joint early warning mechanism, early warning probability, warning mechanism, monitoring device, human-physiological-state.

Graphical Abstract

[1]
J.L. Duan, Y. Sun, and X.N. Chen, "Comparison of heart rate between aerobic exercise and anaerobic exercise in some primary and middle school students in Beijing", Chinese J. School Health., vol. 36, pp. 1294-1296, 2015.
[2]
C. Zhang, Theoretical construction of Internet + wearable physical exercise monitoring service system., Jilin University, 2016.
[3]
K. Akai, "Monitoring physical condition of a patient by telemetry. EP0880936, 30 Oct 1997",
[4]
D. Mol, M. Rudolfus, and A. Keen, A system and a method for monitoring the physical condition of a head of livestock US Patent 6405672, 2000.
[5]
L. Wang, Z. Wang, Z. He, and X. Gao, "Research of physical condition monitoring system for the elderly based on Zigbee wireless network technology In", International Conference on E-Health Networking Digital Ecosystems and Technologies (EDT) Shenzhen,, 2010pp. 32-35
[http://dx.doi.org/10.1109/EDT.2010.5496570]
[6]
K.A. Mamun, A. Sharma, A.S.M. Hoque, and T. Szecsi, "Remote patient physical condition monitoring service module for iWARD hospital robots", Asia-Pacific World Congress on Computer Science and Engineering, Nadi, 2014pp. 1-8
[http://dx.doi.org/10.1109/APWCCSE.2014.7053854]
[7]
M. Nii, K. Nakai, Y. Takahashi, K. Maenaka, and K. Higuchi, "Human action classification for a small size physical condition monitoring system World Automation Congress 2012, Puerto Vallarta, Mexico, 2012, pp. 1-6",
[8]
M. Nii, Y. Kakiuchi, and T. Tanaka, "Implementation of a intelligent system into a small physical condition monitoring device for healthcare", IEEE International Conference on Systems, 2012
[http://dx.doi.org/10.1109/ICSMC.2012.6378041]
[9]
L. Wang, and Z.L. Wang, "Design of Physical Condition Monitoring System for the Elderly Based on ZigBee Technology", J. Chinese Comput. Syst., vol. 32, pp. 1841-1844, 2011.
[10]
S. Ji, W. Xu., M. Yang, and K. Yu, "3D Convolutional Neural Networks for Human Action Recognition. ", in IEEE Transactions on Pattern Analysis and. Machine. Intelligence., vol. 35, no. 1, pp. 221-231, Jan 2013.
[11]
L. Sha, L. Lin, Q. Zhang, F. Shi, and J. Xing, A self-adaptive speed control device for treadmill CN200720032627.0..
[12]
W. Wu, " Eyeglasses for health monitoring. CN201610586062.4",
[13]
J. Groschke, J.P. Spengler, M. Bender, and H. Riedel, " Methods and devices for monitoring bodily functions and/or physical attributes. CN20180056502.X",
[http://dx.doi.org/10.1109/TPAMI.2012.59] [PMID: 22392705]
[14]
Y. Song, J. Tang, and F. Liu, "Body surface context: a new robust feature for action recognition from depth videos", IEEE Trans. Circ. Syst. Video Tech., vol. 24, pp. 952-964, 2014.
[http://dx.doi.org/10.1109/TCSVT.2014.2302558]
[15]
A. Aboukhalil, L. Nielsen, M. Saeed, R.G. Mark, and G.D. Clifford, "Reducing false alarm rates for critical arrhythmias using the arterial blood pressure waveform", J. Biomed. Inform., vol. 41, no. 3, pp. 442-451, 2008.
[http://dx.doi.org/10.1016/j.jbi.2008.03.003] [PMID: 18440873]
[16]
S. Chawla, J. Hartline, and D Malec, Sequential posted pricing and multi-parameter mechanism design Discussion Papers, vol. 2009, no. 1486, 2010..
[17]
J. Duan, Y. Sun, and X. Chen, Heart Rate Comparison of Aerobic Exercise and Anaerobic Exercise among Some Primary and Middle School Students in Beijing Chinese Health School, vol. 36, no. 9, 2015..
[18]
Ministry of Health of the People’s Republic of China, WS/T 101-1998 Health Standards for Physical Exercises of Primary and Secondary School Students. Beijing, China Standard Press, 1998.
[19]
C. Li, and T. Gao, "Teach students to use breathing methods correctly in sports", J. Jiamusi Inst. Educ., vol. 2, pp. 89-89, 2002.