Article: Application of wearable motion tracking devices in training, monitoring, and evaluation Journal: International Journal of Data Mining and Bioinformatics (IJDMB) 2026 Vol.30 No.6 pp.71 - 91 Abstract: The current wearable motion tracking devices have significant differences in heart rate monitoring, inaccurate calorie tracking, and measurement errors in exercise speed and distance. Based on this, this paper optimises the design of wearable motion tracking devices. Firstly, this paper establishes a real-time data mining model for sports training wearable devices using fuzzy algorithms, and determines the heterogeneity of sports training data. Then, this paper constructs a feature extraction model and processes the data using thresholding and Savitzky Golay filtering. Subsequently, this paper elaborates on the calibration method of sensors in wearable motion tracking devices, and finally tests the application of the device in training monitoring and evaluation. The research results indicate that the heart rate of student 11 measured by the device in this paper is 84 beats per minute under normal conditions and 123 beats per minute under high-intensity exercise. Inderscience Publishers - linking academia, business and industry through research

Title: Application of wearable motion tracking devices in training, monitoring, and evaluation

Authors: Fangrong Wu; Shuxiang Yang; Chunli Zhang; Huarong Wu

Addresses: College of Physical Education, Hunan International Economics University, Changsha, 410205, Hunan, China ' School of Nursing and Health Management, Wuhan Donghu University, Wuhan, 430212, Hubei, China ' College of Physical Education, Hunan International Economics University, Changsha, 410076, Hunan, China ' School of Physical Education, Changsha University of Science and Technology, Changsha, 410076, Hunan, China

Abstract: The current wearable motion tracking devices have significant differences in heart rate monitoring, inaccurate calorie tracking, and measurement errors in exercise speed and distance. Based on this, this paper optimises the design of wearable motion tracking devices. Firstly, this paper establishes a real-time data mining model for sports training wearable devices using fuzzy algorithms, and determines the heterogeneity of sports training data. Then, this paper constructs a feature extraction model and processes the data using thresholding and Savitzky Golay filtering. Subsequently, this paper elaborates on the calibration method of sensors in wearable motion tracking devices, and finally tests the application of the device in training monitoring and evaluation. The research results indicate that the heart rate of student 11 measured by the device in this paper is 84 beats per minute under normal conditions and 123 beats per minute under high-intensity exercise.

Keywords: sports tracking; training monitoring; wearable devices; data processing; device calibration; physiological parameter monitoring.

DOI: 10.1504/IJDMB.2026.153896

International Journal of Data Mining and Bioinformatics, 2026 Vol.30 No.6, pp.71 - 91

Received: 17 Nov 2025
Accepted: 11 Feb 2026
Published online: 29 May 2026 *

Title: Application of wearable motion tracking devices in training, monitoring, and evaluation

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