Journal of Sports Science and Medicine
Journal of Sports Science and Medicine
ISSN: 1303 - 2968   
Ios-APP Journal of Sports Science and Medicine
Androit-APP Journal of Sports Science and Medicine
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©Journal of Sports Science and Medicine ( 2019 ) 18 , 438 - 447

Research article
Inertial Sensors in Swimming: Detection of Stroke Phases through 3D Wrist Trajectory
Matteo Cortesi1, , Andrea Giovanardi2, Giorgio Gatta1, Anna L. Mangia3, Sandro Bartolomei4, Silvia Fantozzi5
Author Information
1 Department for Life Quality Studies, University of Bologna, Bologna, Italy
2 School of Pharmacy, Biotechnology and Sport Science, University of Bologna, Bologna, Italy
3 Health Sciences and Technologies, Interdepartmental Centre for Industrial Research, University of Bologna, Bologna, Italy
4 Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
5 Department of Electrical, Electronic and Information Engineering, University of Bologna, Bologna, Italy

Matteo Cortesi
✉ Department for Life Quality Studies, Rimini, University of Bologna, Bologna, Italy
Email: m.cortesi@unibo.it
Publish Date
Received: 12-06-2018
Accepted: 02-05-2019
Published (online): 01-08-2019
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ABSTRACT

Monitoring the upper arm propulsion is a crucial task for swimmer performance. The swimmer indeed can produce displacement of the body by modulating the upper limb kinematics. The present study proposes an approach for automatically recognize all stroke phases through three-dimensional (3D) wrist’s trajectory estimated using inertial devices. Inertial data of 14 national-level male swimmer were collected while they performed 25 m front-crawl trial at intensity range from 75% to 100% of their 25 m maximal velocity. The 3D coordinates of the wrist were computed using the inertial sensors orientation and considering the kinematic chain of the upper arm biomechanical model. An algorithm that automatically estimates the duration of entry, pull, push, and recovery phases result from the 3D wrist’s trajectory was tested using the bi-dimensional (2D) video-based systems as temporal reference system. A very large correlation (r = 0.87), low bias (0.8%), and reasonable Root Mean Square error (2.9%) for the stroke phases duration were observed using inertial devices versus 2D video-based system methods. The 95% limits of agreement (LoA) for each stroke phase duration were always lower than 7.7% of cycle duration. The mean values of entry, pull, push and recovery phases duration in percentage of the complete cycle detected using 3D wrist’s trajectory using inertial devices were 34.7 (± 6.8)%, 22.4 (± 5.8)%, 14.2 (± 4.4)%, 28.4 (± 4.5)%. The swimmer’s velocity and arm coordination model do not affect the performance of the algorithm in stroke phases detection. The 3D wrist trajectory can be used for an accurate and complete identification of the stroke phases in front crawl using inertial sensors. Results indicated the inertial sensor device technology as a viable option for swimming arm-stroke phase assessment.

Key words: Swimming propulsion, hand kinematic, underwater, swimming technique, inertial sensor


           Key Points
  • Inertial sensors technology is a viable option for swimming arm-stroke phase assessment
  • Similar but shifted wrist 3D trajectory were observed between inertial and video analysis
  • Inertial technology for wrist trajectory is independent from video analysis
  • The identification of the entry arm-stroke phase could be performed using the wrist trajectory computed through IMMUs
 
 
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