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Synchronisation of multiple unconnected inertial measurement units using software correction.

Brook Galna1, Emily Wood2, Steven Griffiths3

  • 1PHysical Activity, Sport and Exercise (PHASE) Research Group, School of Allied Health (Exercise Science), Murdoch University, Western Australia, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Western Australia, Australia; Personalised Medicine Centre, Health Futures Institute, Murdoch University, Western Australia, Australia; Newcastle University Translational and Clinical Research Institute, Newcastle, UK.

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Summary

Synchronisation of unconnected inertial measurement units (IMUs) is challenging. This study found predictable desynchronisation rates in IMUs, enabling adaptable techniques for extended human movement research applications.

Keywords:
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Area of Science:

  • Biomechanics
  • Wearable Technology
  • Human Movement Analysis

Background:

  • Accurate synchronization of multiple inertial measurement units (IMUs) is crucial for capturing complex, multi-segmental human movements.
  • Unconnected IMUs, widely used in human movement studies, present synchronization challenges due to clock drift.

Purpose of the Study:

  • To evaluate the reproducibility of desynchronization rates between unconnected IMUs (Axivity, Ax6).
  • To assess the accuracy of predicted clock differences under various experimental conditions.
  • To determine the suitability of synchronization for human movement applications.

Main Methods:

  • Conducted experiments to measure desynchronization rates between pairs of unconnected IMUs.
  • Analyzed the linearity, uniqueness, and reproducibility of desynchronization over time and across sessions.
  • Validated predicted clock error corrections using data from 44 active adults during physical activity.

Main Results:

  • Desynchronization rates between IMU pairs were found to be linear, unique to each pair, and reproducible.
  • Predicted clock errors after 2 hours ranged from -10.1 to 0.3 ms in a cohort of active adults.
  • The observed level of synchronization is deemed acceptable for most human movement applications.

Conclusions:

  • Consistent and predictable desynchronization rates in commonly used unconnected IMUs offer opportunities for synchronization improvements.
  • Development of simple, movement-independent, and adaptable techniques can extend synchronization periods for human movement research.
  • Further research is needed to address fluctuations from external and internal factors for longer-duration synchronization.