Abstract
Background and Aims: The physical decline of college students is greatly affected by the modern lifestyle. College students sit in bad posture for a long time and use electronic products for a long time, and at the same time lack exercise, resulting in increasingly serious restrictions on the functional movement of the body. In this regard, we hope to use modern advanced technology to build an application that can guide college students with functional movement limitations to perform physical training. This paper aims; (1) To investigate the limitations of functional movements among college students. (2) To design physical exercise prescriptions for reduction of functional movement limitation. (3) To construct an application for physical exercise prescription for reduction of functional movement limitation. (4) To experience the application to compare the reduction of functional movement limitation with pre-test and post-test.
Materials and Methods: In the two flexible test movements of active straight leg raise and shoulder flexible in FMS, we added 4 and 12 observation factors by Modify Delphi. After the physical exercise prescription was investigated by the expert IOC, all the content was recognized by the expert. Based on the preliminary content, we have built the Physical Exercise Prescription Application for Reduction of Functional Movement Limitation with an exact validity value equal to 1 and reliability while conducting the Chi-Square test of the application and expert group, we found that the application and experts are consistent. For physical exercise prescriptions, we compared the application and experts to find that the Chi-Square value is between 1 to 3 and has a large consistency. The Chi-Square Value of the evaluation process is 0.087, and the consistency evaluated by the application and experts is as high as 76.8%.
Results: We used the application to conduct an 8-week experimental intervention of 35 college students. Using the physical exercise prescriptions recommended by the application, through the t-test, students' shoulder flexibility and active straight leg raise are raised significantly (P <0.05).
Conclusion: The application can solve the problem of functional movement limitation of college students. In the future, with the increase of capital investment and the expansion of data volume, the application will be able to solve the basic problems of functional movement limitation to more different levels of motion pyramids. To encourage to exanthem case more healthily.
Publisher
Dr. Ken Institute of Academic Development and Promotion
Reference60 articles.
1. Alves, V., & Silvestrini, A. P. (2020). Achieving the Right to Work in the Face of Technological Advances: Reflections on the Occasion of the ILO's Centenary. U. Bologna L. Rev., 5, 226.
2. Angermueller, C., Pärnamaa, T., Parts, L., & Stegle, O. (2016). Deep learning for computational biology. Molecular systems biology, 12(7), 878.
3. Baker, R., Coenen, P., Howie, E., Williamson, A., & Straker, L. (2018). The short-term musculoskeletal and cognitive effects of prolonged sitting during office computer work. International journal of environmental research and public health, 15(8), 1678.
4. Bottou, L. (2010). Large-scale machine learning with stochastic gradient descent. In Proceedings of COMPSTAT'2010. 19th International Conference on Computational Statistics Paris France, August 22-27, 2010 Keynote, Invited and Contributed Papers (pp. 177 - 186). Physica-Verlag HD.
5. Caruana, R., Lou, Y., Gehrke, J., Koch, P., Sturm, M., & Elhadad, N. (2015, August). Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission. In Proceedings of the 21st ACM SIGKDD international conference on knowledge discovery and data mining (pp. 1721-1730).