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Related Experiment Video

Updated: Jul 7, 2026

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

Surf Session Events' Profiling Using Smartphones' Embedded Sensors.

Diana Gomes1, Dinis Moreira2, João Costa2,3

  • 1Fraunhofer Portugal AICOS, 4200-135 Porto, Portugal. diana.gomes@fraunhofer.pt.

Sensors (Basel, Switzerland)
|July 20, 2019
PubMed
Summary

This study introduces a new method for accurately detecting surfing events, including waves and paddling, achieving 88.1% overall accuracy. This system offers precise wave detection, enhancing surf session analysis.

Keywords:
activity recognitiongpsinertial sensorsmonitoring systemsmartphonesports performancesurf

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Area of Science:

  • Sports Science
  • Computer Science
  • Engineering

Background:

  • The burgeoning popularity of surfing highlights the need for advanced technological solutions.
  • Current methods for analyzing surf sessions are limited by performance, availability, and validation issues.

Purpose of the Study:

  • To develop a novel, accurate method for detecting key events within a surf session.
  • To enable comprehensive profiling of surfing activities through precise event detection.

Main Methods:

  • A new algorithm was developed for detecting wave, paddle, sprint paddle, dive, lay, and sit events.
  • The system was validated for its accuracy and precision in identifying these events.

Main Results:

  • The proposed method achieved 88.1% accuracy for combined event detection.
  • Wave detection, a critical event, reached 90.3% accuracy with second-level precision.
  • Wave detection performance demonstrated 97.5% precision and 94.2% recall out of 327 annotated waves.

Conclusions:

  • The developed system provides precise and valid surf session profiling.
  • The solution is suitable for real-time implementation and shows significant market potential.