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Related Experiment Video

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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
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Assessing real-world movements using consumer-grade wearable devices: Measuring segment orientations and movement

T Alexander Swain1,2, Melitta A McNarry1, Samuel Manzano-Carrasco3

  • 1Applied Sports, Technology, Exercise and Medicine Research Centre (A-STEM), Swansea University, Swansea, UK.

Wearable Technologies
|November 26, 2025
PubMed
Summary

Consumer wearables show promise for assessing human movement quality outside labs. Chest-mounted sensors offer the best accuracy for evaluating movement, though optimal placement and calibration are key.

Keywords:
IMUexercisemotion capturemotor skillsphysical activitywearable technology

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Area of Science:

  • Biomechanics
  • Wearable technology
  • Human movement analysis

Background:

  • Assessing human movement quality is crucial for health but challenging outside clinical settings.
  • Consumer-grade wearables offer a potential solution for accessible movement analysis.

Purpose of the Study:

  • To evaluate the accuracy of consumer-grade wearables for movement quality assessment.
  • To identify optimal sensor locations for wearable-based movement analysis.

Main Methods:

  • Twenty-two participants wore magnetic, angular rate, and gravity (MARG) sensors on multiple body locations.
  • The Madgwick sensor-fusion algorithm processed sensor data for 3D orientation.
  • Concurrent validity was assessed against optical motion capture using root-mean-square-error (RMSE).

Main Results:

  • Chest-mounted sensors achieved the highest accuracy (mean RMSE < 9.0°).
  • Wrist, ankle, and thigh sensors showed variable and mixed results.
  • Yaw angles had higher discrepancies than pitch and roll angles.

Conclusions:

  • Consumer MARG sensors have potential for real-world biomechanical analysis.
  • Strategic sensor placement and refined processing methods are essential for accuracy.