Volitional Control of the Paretic Hand Post-Stroke Increases Finger Stiffness and Resistance to Robot-Assisted Movement

TL;DR

This study investigates how volitional effort to move the paretic hand affects finger stiffness during robot-assisted movement after stroke. Using the MyHand wearable orthosis and EMG-controlled actuation, stiffness is quantified as the slope of the force–displacement relation at the index finger, comparing active, EMG-controlled movement to passive extension across three chronic stroke subjects. Active engagement yields higher finger stiffness than passive movement or sustained exertion, with a maximum around $0.46$ N/mm, and induces persistent changes in finger posture (e.g., claw-like configurations). These results imply that designers must anticipate elevated joint stiffness during user-driven ipsilateral control and motivate sensorized, adaptive approaches in assistive/rehabilitative devices for stroke.

Abstract

Increased effort during use of the paretic arm and hand can provoke involuntary abnormal synergy patterns and amplify stiffness effects of muscle tone for individuals after stroke, which can add difficulty for user-controlled devices to assist hand movement during functional tasks. We study how volitional effort, exerted in an attempt to open or close the hand, affects resistance to robot-assisted movement at the finger level. We perform experiments with three chronic stroke survivors to measure changes in stiffness when the user is actively exerting effort to activate ipsilateral EMG-controlled robot-assisted hand movements, compared with when the fingers are passively stretched, as well as overall effects from sustained active engagement and use. Our results suggest that active engagement of the upper extremity increases muscle tone in the finger to a much greater degree than through passive-stretch or sustained exertion over time. Potential design implications of this work suggest that developers should anticipate higher levels of finger stiffness when relying on user-driven ipsilateral control methods for assistive or rehabilitative devices for stroke.

Figures (6)

• Figure 1: Subject engaging the impaired limb to practice functional hand movements with robotic assistance. Volitional ipsilateral activation of the orthosis makes user-driven, intensive exercise possible for individuals who cannot open their own hands.
• Figure 2: Diagrams showing sensor placements on the robot and hand and the angle convention used in this paper.
• Figure 3: Graphical summary of the experimental protocol. The session is divided into four main phases: an initial passive phase (P1), a training phase (T1-T3), an active phase (A1-A2) , and a final passive phase (P2). During the passive phases (P1, P2), we use button control to open and close the participant's hand. This contrasts with the active phase (A1, A2), in which the participant has full volitional control of the orthosis via EMG. Our EMG-control is calibrated during the training phase in which the participant is actively exerting volitional effort to move their hand both without (T1-T2) and with (T3) assistance from the orthosis. Bolded outlines around an experimental phase block denote when the orthosis assists hand movement. The gradient color bar labeled "Expected Fatigue" at the bottom of the diagram qualitatively denotes our expectations of increasing fatigue (red) over the course of the session as the participant engages in activities of sustained active engagement and use of the arm.
• Figure 4: Net force versus motor displacement scatterplots and corresponding best fit linear regression lines for each experimental condition during robot-assisted hand openings across subjects. Experimental conditions are labeled by color (Blue = P1, Orange = A1, Green = A2, Red = P2).
• Figure 5: Spike plot of measured index finger stiffnesses ordered chronologically during robot-assisted hand openings. Experimental conditions are labeled by color (Blue = P1, Orange = A1, Green = A2, Red = P2). We define finger stiffness as the slopes of the best-fit lines calculated by performing linear regression on the force and motor displacement data during hand opening. EMG bars (Gray) depict the maximum EMG amplitude recorded during each hand opening. EMG amplitude values are integers given in arbitrary units (a.u.) transmitted by the commercial EMG armband. We set scale bars for EMG amplitude based on the maximum values recorded for each subject.