J Shanghai Jiaotong Univ Sci

Journal of Shanghai Jiaotong University(Science) >

2022 , Vol. 27 >Issue 2: 219 - 225

DOI: https://doi.org/10.1007/s12204-021-2367-4

Medicine-Engineering Interdisciplinary Research

Improvement of Physical Fitness Test Assessment Criteria Based on fNIRS Technology: Taking Pull-Up as an Example

Expand
  • (1. School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China; 2. Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China; 3. School of Mechanical and Electrical Engineering, Soochow University, Suzhou 215006, Jiangsu, China; 4. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

Received date: 2021-04-26

  Online published: 2022-05-02

Fold

Abstract

Pull-up, as an important physical fitness test event of the “National Student Physical Health Standard”, is known as a difficult physical fitness test event. To improve the assessment criteria of pull-ups, this paper uses the functional near-infrared spectroscopy (fNIRS) to monitor the changes and activation of oxyhemoglobin (HbO) signals in the brain motor cortex of people with different body mass indexes (BMIs) during the pullup assessment. Then the relationship between BMIs and evaluation criteria is discussed. After collecting and analyzing experimental data of 18 recruited college students, it is found that the number of pull-ups performed by people with different BMIs is different when they reach the peak state of brain activation. The results of the study indicate that different assessment criteria should be adopted for different BMI groups. It is suggested that the BMI should be introduced as one of the test indexes in the examination of pull-ups event in “National Student Physical Health Standard”.

Key words： functional near-infrared spectroscopy (fNIRS); body mass index (BMI); pull-up; brain activation

Cite this article

GONG Bin(巩斌), YU Xianghua(禹香华), FANG Yu (方宇), WANG Zheng (王正), YANG Hao (杨皓), CHEN Guodong (陈国栋), L Ü Na (吕娜) . Improvement of Physical Fitness Test Assessment Criteria Based on fNIRS Technology: Taking Pull-Up as an Example[J]. Journal of Shanghai Jiaotong University(Science), 2022 , 27(2) : 219 -225 . DOI: 10.1007/s12204-021-2367-4

References

[1] ZHANG Q F, TANG C F, YIN L Q, et al. Policy implementation and effect of National Student Physical Fitness Standard from the perspective of audience responsiveness: An empirical analysis based on 40 colleges and universities in 10 provinces [J]. China Sport Science and Technology, 2020, 56(10): 89-97 (in Chinese). [2] YANG F. Strengthen compensatory physical fitness exercises to improve the level of pull-ups [J]. China School Physical Education, 2019(8): 54-55 (in Chinese). [3] YU J, MAO Y. On the factors affecting the execution efficiency of “chin-up” in National Fitness And Health Standard Of Students [J]. Journal of Zhejiang Ocean University (Humanities Edition), 2020, 37(2): 84-88(in Chinese). [4] WANG Y, TONG J. Discussion on the quantitative model of college students’ physical health [J]. Contemporary Sports Technology, 2020, 10(34): 11-12 (in Chinese). [5] JIANG L P, ZHAO Y, XI T F. An empirical study on the effect of test implementation of “National Student Physical Health Standard”: Taking university A as an example [J]. Zhejiang Sport Science, 2020, 42(5): 46-51 (in Chinese). [6] ZENGQ,HEY, DONGS, et al.Optimal cut-off values of BMI, waist circumference and waist: Height ratio for defining obesity in Chinese adults [J]. British Journal of Nutrition, 2014, 112(10): 1735-1744. [7] MA Q Z, ZHANG Z, MU X T, et al. Effects of body mass index on left ventricular structure and function in Chinese adult men: A cardiovascular magnetic resonance imaging study [J]. Journal of Medical Imaging,2021, 31(3): 414-417 (in Chinese). [8] CHANG P H, LEE S H, GU G M, et al. The cortical activation pattern by a rehabilitation robotic hand: A functional NIRS study [J]. Frontiers in Human Neuroscience,2014, 8: 49. [9] KIMMJ, HONG J H, JANG S H. The cortical effect of clapping in the human brain: A functional MRI study [J]. NeuroRehabilitation, 2011, 28(2): 75-79. [10] MIYAI I, TANABE H C, SASE I, et al. Cortical mapping of gait in humans: A near-infrared spectroscopic topography study [J]. NeuroImage, 2001, 14(5): 1186-1192. [11] SUZUKI M, MIYAI I, ONO T, et al. Prefrontal and premotor cortices are involved in adapting walking and running speed on the treadmill: An optical imaging study [J]. NeuroImage, 2004, 23(3): 1020-1026. [12] LIN P Y, LIN S I, CHEN J J J. Functional near infrared spectroscopy study of age-related difference in cortical activation patterns during cycling with speed feedback [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2012, 20(1): 78-84. [13] BU L, HUO C, XU G, et al. Alteration in brain functional and effective connectivity in subjects with hypertension [J]. Frontiers in Physiology, 2018, 9: 669. [14] YEUNG M K. An optical window into brain function in children and adolescents: A systematic review of functional near-infrared spectroscopy studies [J]. NeuroImage,2021, 227: 117672. [15] VAN EYNDHOVEN S, DUPONT P, TOUSSEYN S,et al. Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI data [J]. NeuroImage, 2021,228: 117652. [16] PERREY S. Non-invasive NIR spectroscopy of human brain function during exercise [J]. Methods, 2008,45(4): 289-299. [17] ZHOU X S, HU Y N, LIAO P C, et al. Hazard differentiation embedded in the brain: A near-infrared spectroscopy-based study [J]. Automation in Construction,2021, 122: 103473. [18] LI C G, YANG H J, CHENG L. Fugl-Meyer hand motor imagination recognition for brain-computer interfaces using only fNIRS [J]. Complex & Intelligent Systems,2021: 1-11. [19] KAWAI N, NAKATA R, KUBO-KAWAI N. Older adults exhibit greater brain activity than young adults in a selective inhibition task by bipedal and bimanual responses: An fNIRS study [J]. NeuroReport, 2020,31(14): 1048-1053. [20] LU K, XU G C, LIWH, et al. Frequency-specific functional connectivity related to the rehabilitation task of stroke patients [J]. Medical Physics, 2019, 46(4): 1545-1560. [21] HITOMI T, GERRITS R, HARTSUIKER R J. Using functional near-infrared spectroscopy to study word production in the brain: A picture-word interference study [J]. Journal of Neurolinguistics, 2021, 57:100957. [22] LI R, LI S, ROH J, et al. Multimodal neuroimaging using concurrent EEG/fNIRS for poststroke recovery assessment: An exploratory study [J]. Neurorehabilitation and Neural Repair, 2020, 34(12): 1099-1110. [23] SCHOLKMANN F, SPICHTIG S, MUEHLEMANN T, et al. How to detect and reduce movement artifacts in near-infrared imaging using moving standard deviation and spline interpolation [J]. Physiological Measurement,2010, 31(5): 649-662. [24] HU X, ZHUANG C, WANG F, et al. fNIRS evidence for recognizably different positive emotions [J]. Frontiers in Human Neuroscience, 2019, 13: 120. [25] GENTILE E, BRUNETTI A, RICCI K, et al. Mutual interaction between motor cortex activation and pain in fibromyalgia: EEG-fNIRS study [J]. PLoS One,2020, 15(1): e0228158. [26] SMITH S M, FOX P T, MILLER K L, et al. Correspondence of the brain’s functional architecture during activation and rest [J]. PNAS, 2009, 106(31): 13040-13045.
Options
Outlines

/

〈 〉