Human Activity Recognition of Individuals with Lower Limb Amputation in Free-Living Conditions: A Pilot Study.

ABSTRACT: This pilot study aimed to investigate the implementation of supervised classifiers and a neural network for the recognition of activities carried out by Individuals with Lower Limb Amputation (ILLAs), as well as individuals without gait impairment, in free living conditions. Eight individuals with no gait impairments and four ILLAs wore a thigh-based accelerometer and walked on an improvised route in the vicinity of their homes across a variety of terrains. Various machine learning classifiers were trained and tested for recognition of walking activities. Additional investigations were made regarding the detail of the activity label versus classifier accuracy and whether the classifiers were capable of being trained exclusively on non-impaired individuals' data and could recognize physical

SUBMITTER: Jamieson A 

PROVIDER: S-EPMC8704297 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature