Gait detection in children with and without hemiplegia using single-axis wearable gyroscopes

Abstract

In this work, we develop a novel gait phase detection algorithm based on a hidden Markov model, which uses data from foot-mounted single-axis gyroscopes as input. We explore whether the proposed gait detection algorithm can generate equivalent results as a reference signal provided by force sensitive resistors (FSRs) for typically developing children (TD) and children with hemiplegia (HC). We find that the algorithm faithfully reproduces reference results in terms of high values of sensitivity and specificity with respect to FSR signals. In addition, the algorithm distinguishes between TD and HC and is able to assess the level of gait ability in patients. Finally, we show that the algorithm can be adapted to enable real-time processing with high accuracy. Due to the small, inexpensive nature of gyroscopes utilized in this study and the ease of implementation of the developed algorithm, this work finds application in the on-going development of active orthoses designed for therapy and locomotion in children with gait pathologies.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1. Schematic of positions for IMU and FSRs.

a) An IMU is attached to the shoe and φ measures the angular position in the sagittal plane with respect to resting position and b) FSRs are placed on the sole of the foot at the heel and the first and fifth metatarsals.

Figure 2. Specificity and sensitivity of AOL-detected gait phases, with FSR reference, for typically developing children and children with hemiplegia.

The three populations are the combined legs of typically developing children (TD), the more affected legs of the children with hemiplegia (HC), and the less affected legs of the children with hemiplegia. Performance measures are given as mean ± one standard error over each population. For patients with equally affected sides, the right is taken as the more affected leg.

Figure 3. Percent time spent in each gait phase by typically developing children and children with hemiplegia.

The three populations are the combined legs of typically developing children (TD), the more affected legs of the children with hemiplegia (HC), and the less affected legs of the children with hemiplegia. Results are given as mean ± one standard error over each population, detected by AOL. For patients with equally affected sides, the right is taken as the more affected leg. Gait phases in which the three populations spend statistically significant different times are starred (ANOVA, p<0.05).

Figure 4. Specificity and sensitivity of ART-detected gait phases, with AOL reference, for typically developing children and children with hemiplegia.

The three populations are the combined legs of typically developing children (TD), the more affected legs of the children with hemiplegia (HC), and the less affected legs of the children with hemiplegia. Performance measures are given as mean ± one standard error over each population. For patients with equally affected sides, the right is taken as the more affected leg.