A Comprehensive Analysis of the Validity and Reliability of the Perception Neuron Studio for Upper-Body Motion Capture

Sensors (Basel). 2022 Sep 14;22(18):6954. doi: 10.3390/s22186954.

Abstract

The Perception Neuron Studio (PNS) is a cost-effective and widely used inertial motion capture system. However, a comprehensive analysis of its upper-body motion capture accuracy is still lacking, before it is being applied to biomechanical research. Therefore, this study first evaluated the validity and reliability of this system in upper-body capturing and then quantified the system's accuracy for different task complexities and movement speeds. Seven participants performed simple (eight single-DOF upper-body movements) and complex tasks (lifting a 2.5 kg box over the shoulder) at fast and slow speeds with the PNS and OptiTrack (gold-standard optical system) collecting kinematics data simultaneously. Statistical metrics such as CMC, RMSE, Pearson's r, R2, and Bland-Altman analysis were utilized to assess the similarity between the two systems. Test-retest reliability included intra- and intersession relations, which were assessed by the intraclass correlation coefficient (ICC) as well as CMC. All upper-body kinematics were highly consistent between the two systems, with CMC values 0.73-0.99, RMSE 1.9-12.5°, Pearson's r 0.84-0.99, R2 0.75-0.99, and Bland-Altman analysis demonstrating a bias of 0.2-27.8° as well as all the points within 95% limits of agreement (LOA). The relative reliability of intra- and intersessions was good to excellent (i.e., ICC and CMC were 0.77-0.99 and 0.75-0.98, respectively). The paired t-test revealed that faster speeds resulted in greater bias, while more complex tasks led to lower consistencies. Our results showed that the PNS could provide accurate enough upper-body kinematics for further biomechanical performance analysis.

Keywords: biomechanics; inertial motion capture system; reliability; upper-body kinematics; validity.

MeSH terms

  • Biomechanical Phenomena / physiology
  • Humans
  • Motion
  • Neurons*
  • Perception*
  • Reproducibility of Results