Hidden Markov model-based similarity measure (HMM-SM) for gait quality assessment of lower-limb prosthetic users using inertial sensor signals.
Journal:
Journal of neuroengineering and rehabilitation
Published Date:
May 12, 2025
Abstract
BACKGROUND: Gait quality indices, such as the Gillette Gait Index or Gait Profile Score (GPS), can provide clinicians with objective, straightforward measures to quantify gait pathology and monitor changes over time. However, these methods often require motion capture or stationary gait analysis systems, limiting their accessibility. Inertial sensors offer a portable, cost-effective alternative for gait analysis. This study aimed to evaluate a novel hidden Markov model-based similarity measure (HMM-SM) for assessing gait quality directly from gyroscope and accelerometer data captured by inertial sensors.
