Analyzing gait data measured by wearable cyborg hybrid assistive limb during assisted walking: gait pattern clustering.

ABSTRACT:

Introduction

The wearable cyborg Hybrid Assistive Limb (HAL) is a therapeutic exoskeletal device that provides voluntary gait assistance using kinematic/kinetic gait data and bioelectrical signals. By utilizing the gait data automatically measured by HAL, we are developing a system to analyze the wearer's gait during the intervention, unlike conventional evaluations that compare pre- and post-treatment gait test results. Despite the potential use of the gait data from the HAL's sensor information, there is still a lack of analysis using such gait data and knowledge of gait patterns during HAL use. This study aimed to cluster gait patterns into subgroups based on the gait data that the HAL automatically collected during treatment and to investigate their characteristics.

Methods<

SUBMITTER: Namikawa Y 

PROVIDER: S-EPMC11682894 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature