학술논문

Activity Monitoring Through Wireless Sensor Networks Embedded Into Smart Sport Equipments: The Nordic Walking Training Utility
Document Type
Periodical
Source
IEEE Sensors Journal IEEE Sensors J. Sensors Journal, IEEE. 22(3):2744-2757 Feb, 2022
Subject
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Robotics and Control Systems
Sports
Legged locomotion
Real-time systems
Monitoring
Wireless sensor networks
Sensors
Training
Activity monitoring
data analytics
Internet of Things
smart sport equipments
wireless sensor network
Language
ISSN
1530-437X
1558-1748
2379-9153
Abstract
This paper presents the study of Nordic Walking providing objective evaluations based on real time acquisition of kinematic parameters during the sport practice. It is possible to carefully monitor the athletic gesture through the integration of conventional poles with inertial sensors, composed of a triaxial accelerometer, a triaxial gyroscope, a pressure sensor positioned on the handle, and a load cell, which constitute a Wireless Sensor Network whose nodes are appropriately synchronized. The integration of such sensors, which must be unobstructive and not change the functionality of the poles, is dictated by the ultimate goal of providing a real time biofeedback in two possible scenarios. The first is intended for Nordic Walking’s instructors, who have the opportunity to verify the proper practice execution by their trainees through the availability of real time objective data, in addition to their personal experience. The second is devoted to amateur players who can practice alone, after the training session with the instructor, and can independently correct any imperfections in real time using a software tool running on their smartphone. Using the Dynamic Time Warping algorithm, the proposed system identifies the most frequent errors in performing athletic gesture, allowing adjustment in real time of the sporting exercise, through the detection, quantification and correction of errors. The obtained results show that the developed system is able to provide an accurate analysis of the athletic gesture and the proposed algorithm allows a quantitative monitoring of the progress achieved by each subject over time.