International Journal of Advanced Culture Technology

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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Analysis of instrument exercise using IMU about symmetry

  • Yohan Song (School of Mechanical and Control Engineering, Handong Global University) ;
  • Hyun-Bin Zi (School of Mechanical and Control Engineering, Handong Global University) ;
  • Jihyeon Kim (HIsoLution) ;
  • Hyangshin Ryu (HIsoLution) ;
  • Jaehyo Kim (School of Mechanical and Control Engineering, Handong Global University)
  • Received : 2023.01.31
  • Accepted : 2023.03.13
  • Published : 2023.03.31
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Abstract

The purpose of this study is to measure and compare the balance of motion between the left and right using a wearable sensor during upper limb exercise using an exercise equipment. Eight participants were asked to perform upper limb exercise using exercise equipment, and exercise data were measured through IMU sensors attached to both wrists. As a result of the PCA test, Euler Yaw(Left: 0.65, Right: 0.75), Roll(Left: 0.72, Right: 0.58), and Gyro X(Left: 0.64, Right: 0.63) were identified as the main components in the Butterfly exercise, and Euler Pitch(Left: 0.70, Right 0.70) and Gyro Z(Left: 0.70, Right: 0.71) were identified as the main components in the Lat pull down exercise. As a result of the Paired-T test of the Euler value, Yaw's Peak to Peak at Butterfly exercise and Roll's Mean, Yaw's Mean and Period at Lat pull down exercise were smaller than the significance level of 0.05, proving meaningful difference was found. In the Symmetry Index and Symmetry Ratio analysis, 89% of the subjects showed a tendency of dominant limb maintaining relatively higher angular movement performance then non-dominant limb as the Butterfly exercise proceeds. 62.5% of the subjects showed the same tendency during the Lat pull down exercise. These experimental results indicate that meaningful difference at balance of motion was found according to an increase in number of exercise trials.

Keywords

Acknowledgement

This study was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education (2020R1I1A3A04038203).

References

  1. Wang, J. "Motion recognition based on deep learning and human joint points." Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/1826951
  2. Chen, Weiya, et al. "A survey on hand pose estimation with wearable sensors and computer-vision-based methods." Sensors, Vol. 20, Issue. 4, No. 1074, 2020. https://doi.org/10.3390/s20041074
  3. Chudecka, Monika, and Lubkowska. "The use of thermal imaging in the evaluation of the symmetry of muscle activity in various types of exercises (symmetrical and asymmetrical)." Journal of human kinetics, Vol. 49, Issue. 1, pp. 141-147, December 2015. https://doi.org/10.1515/hukin-2015-0116
  4. Soro, Andrea, et al. "Recognition and repetition counting for complex physical exercises with deep learning." Sensors, Vol. 19, Issue. 3, No. 714, 2019. https://doi.org/10.3390/s19030714
  5. Vutan, Ana-Maria, and Lovasz, E.C, "Evaluation of Symmetrical Exercises in Scoliosis by Using Thermal Scanning." Applied Sciences, Vol. 12(2), pp. 5-8, January 2022. https://doi.org/10.3390/app12020721
  6. Prochazka, Ales, et al. "Motion symmetry evaluation using accelerometers and energy distribution." Symmetry, Vol. 11(7), pp. 1-12, 2019. https://doi.org/10.3390/sym11070871
  7. Patterson, Kara K., et al. "Evaluation of gait symmetry after stroke: a comparison of current methods and recommendations for standardization." Gait & posture, Vol. 31, Issue. 2, pp. 241-246, February 2010. https://doi.org/10.1016/j.gaitpost.2009.10.014
  8. Siebers, Hannah Lena, et al. "Comparison of different symmetry indices for the quantification of dynamic joint angles." BMC Sports Science, Medicine and Rehabilitation, Vol. 13, No. 130, pp. 1-11, October 2021. https://doi.org/10.1186/s13102-021-00355-4
  9. Gurchiek, Reed D., et al. "Remote gait analysis using wearable sensors detects asymmetric gait patterns in patients recovering from ACL reconstruction." 2019 IEEE 16th International Conference on Wearable and Implantable Body Sensor Networks (BSN). IEEE, 2019. https://doi.org/10.1109/BSN.2019.8771038
  10. Horbacz, A., Majherova, M., & Perecinska, K., "Posture and muscle imbalance in young tennis players", Scientific Review of Physical Culture, Vol.3, No.4, pp. 33~38. 2013
  11. Blazkiewicz, Michalina, Ida Wiszomirska, and Andrzej Wit. "Comparison of four methods of calculating the symmetry of spatial-temporal parameters of gait." Acta of bioengineering and biomechanics, Vol. 16 No. 1, 2014. http://dx.doi.org/10.5277/abb140104
  12. Bakhshi, Saba, Mohammad H. Mahoor, and Bradley S. Davidson. "Development of a body joint angle measurement system using IMU sensors." 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2011. https://doi.org/10.1109/IEMBS.2011.6091743
  13. Baechle, T. R., R. W. Earle, and Thomas R. Baechle. NSCA's essentials of personal training. Human Kinetics, 2004.
  14. Amirhamzeh, M. M. R., Chant, H. J., and Campbell, W. B. "A comparative study of treadmill tests and heel raising exercise for peripheral arterial disease" European journal of vascular and endovascular surgery, Vol. 13, Issue. 3, pp. 301-305, March 1997. https://doi.org/10.1016/S1078-5884(97)80102-5
  15. Rasti, E., Rojhani-Shirazi, Z., and Sobhan, M. R. "Effects of whole body vibration with exercise therapy versus exercise therapy alone on flexibility, vertical jump height, agility and pain in athletes with patellofemoral pain: a randomized clinical trial". BMC Musculoskeletal Disorders, Vol. 21, No. 705, pp. 1-9, October 2020. https://doi.org/10.1186/s12891-020-03732-1