title: Stumble detection and classification for an intelligent transfemoral prosthesis.
abstract: This paper describes an approach for the real-time detection of stumble for use in an intelligent lower limb prosthesis, using accelerometers mounted on the prosthesis, and also describes an algorithm that classifies the stumble response as either an elevating or lowering type response. In order to validate the proposed approach, the investigators collected stumble data on 10 healthy subjects using accelerometers affixed to the subjects in a manner consistent with similar instrumentation on a transfemoral prosthesis. The proposed algorithms were shown to correctly identify stumbling and correctly classify the stumble response for all 19 stumbles and 34 control strides collected in the experiments.
authors.affiliation: Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA. brian.e.lawson@vanderbilt.edu
authors.forename: Brian E
authors.initials: BE
authors.lastname: Lawson
authors.forename: H
authors.initials: H
authors.lastname: Atakan Varol
authors.forename: Frank
authors.initials: F
authors.lastname: Sup
authors.forename: Michael
authors.initials: M
authors.lastname: Goldfarb
mesh_terms: D000054:Acceleration; D000465:Algorithms; D001185:Artificial Intelligence; D001186:Artificial Limbs; D005684:Gait / Q000502:physiology*; D006801:Humans; D018670:Monitoring, Ambulatory / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D013848:Thigh / Q000502:physiology; D016138:Walking / Q000145:classification / Q000502:physiology