Improving the reliability of underwater gait analysis using wearable pressure and inertial sensors

PLoS One. 2024 Mar 21;19(3):e0300100. doi: 10.1371/journal.pone.0300100. eCollection 2024.

Abstract

This work addresses the lack of reliable wearable methods to assess walking gaits in underwater environments by evaluating the lateral hydrodynamic pressure exerted on lower limbs. Sixteen healthy adults were outfitted with waterproof wearable inertial and pressure sensors. Gait analysis was conducted on land in a motion analysis laboratory using an optoelectronic system as reference, and subsequently underwater in a rehabilitation swimming pool. Differences between the normalized land and underwater gaits were evaluated using temporal gait parameters, knee joint angles and the total water pressure on the lower limbs. The proposed method was validated against the optoelectronic system on land; gait events were identified with low bias (0.01s) using Bland-Altman plots for the stride time, and an acceptable error was observed when estimating the knee angle (10.96° RMSE, Bland-Altman bias -2.94°). The kinematic differences between the land and underwater environments were quantified, where it was observed that the temporal parameters increased by more than a factor of two underwater (p<0.001). The subdivision of swing and stance phases remained consistent between land and water trials. A higher variability of the knee angle was observed in water (CV = 60.75%) as compared to land (CV = 31.02%). The intra-subject variability of the hydrodynamic pressure on the foot ([Formula: see text] = 39.65%) was found to be substantially lower than that of the knee angle (CVz = 67.69%). The major finding of this work is that the hydrodynamic pressure on the lower limbs may offer a new and more reliable parameter for underwater motion analysis as it provided a reduced intra-subject variability as compared to conventional gait parameters applied in land-based studies.

MeSH terms

  • Adult
  • Biomechanical Phenomena
  • Gait
  • Gait Analysis*
  • Humans
  • Reproducibility of Results
  • Walking
  • Water
  • Wearable Electronic Devices*

Substances

  • Water

Grants and funding

This research was funded in part by the Estonian Research Council Grant PRG1243. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.