Influence of Arm Weight Support on a Robotic Assessment of Upper Limb Function

Abstract

Quantifying upper limb impairment post-stroke is of essential importance to monitor motor recovery or to evaluate different therapeutic approaches. Instrumented assessments of upper limb function, such as the Virtual Peg Insertion Test (VPIT), often emulate a daily life manipulation activity that requires the subject to actively lift the arm against gravity, which can be challenging for severely impaired patients with arm weakness. With the aim of making the VPIT accessible to patients with severe arm weakness, we conducted a pilot study to analyze the feasability of combining this assessment with an arm weight support (AWS) device in 16 healthy subjects. Subjects performed the VPIT protocol without AWS device and with three different levels of weight support. Usability of combining the VPIT and the AWS device was high in healthy Subjects: The VPIT could be successfully completed without collisions with the AWS device, the duration to set up the AWS device was on average 1.5min, and subjects reported high levels of comfort while experiencing AWS. Metrics representing arm function were mostly not significantly influenced by the presence of the AWS device despite a decrease of 6.2% in movement smoothness, whereas grasping control was not significantly affected at all. The AWS level did not alter motor performance, even though subjects reported a decrease in perceived arm control with an increased AWS level. The high usability of combining the VPIT with an AWS device might enable the assessment of severely impaired patients in clinical practice. However, the influence of the AWS on outcome measures of the VPIT must be taken into account to make assessment results interpretable in the context of daily life reaching and manipulation situations without AWS.