Assessment of movement patterns in stroke patients: a case study with the Virtual Peg Insertion Test

Abstract

Abnormal movement patterns during upper-limb reaching tasks are often observed in patients after stroke, but clinical tools are lacking to objectively evaluate and quantify them. This paper presents the implementation and evaluation of six trajectory-based metrics on the Virtual Peg Insertion Test, a technology-based assessment of upper limb function consisting of a goal-directed peg-in-hole task. A case study with four stroke patients illustrates the ability of the proposed metrics to describe motion patterns that differ from age-matched healthy subjects, and thus to objectively assess and track abnormal movement patterns.