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A Wearable System for Jump Detection in Inline Figure Skating.

Antonio Panfili1, Alvise Spanò1, Agostino Cortesi1

  • 1Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca' Foscari Venezia, 30172 Venice, Italy.

Sensors (Basel, Switzerland)
|February 26, 2022
PubMed
Summary

A new wearable sensor system accurately detects jumps in inline figure skating using novel optical sensor placement. This non-invasive technology provides real-time performance data for athletes and coaches.

Keywords:
human movement analysisinline figure skatingsports biomechanicswearable sensors

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Area of Science:

  • Sports Science
  • Biomechanical Engineering
  • Wearable Technology

Background:

  • Inline figure skating performance analysis requires accurate, non-invasive monitoring.
  • Existing methods lack specificity or are constrained by training environment.
  • Developing a system for real-time jump detection is crucial for training optimization.

Purpose of the Study:

  • To design and evaluate a novel wearable sensor system for inline figure skating.
  • To accurately detect jumps and provide real-time performance metrics.
  • To offer a cost-effective and precise solution for athlete monitoring.

Main Methods:

  • Integration of distance, time-of-flight, and gyroscope sensors into a wearable system.
  • Novel vertical orientation of optical sensors under each foot to measure ground distance.
  • Placement of a gyroscope on the athlete's back for movement analysis.
  • Development of a graphical user interface for live data visualization.

Main Results:

  • The system accurately detects jumps and technical elements in inline figure skating.
  • Real-time data on jump count and height is provided.
  • Experimental evaluation by elite athletes confirmed system effectiveness.
  • The system offers a favorable precision-to-cost ratio.

Conclusions:

  • The developed wearable sensor system is effective for inline figure skating performance analysis.
  • The novel sensor orientation provides accurate jump detection without training ground constraints.
  • This system represents a significant advancement in non-invasive athlete monitoring for inline figure skating.