Robotic Assessment of Upper Limb Motor Function After Stroke

Abstract

Traditional assessment of a stroke subject's motor ability, carried out by a therapist who observes and rates the subject's motor behavior using ordinal measurements scales, is subjective, time consuming and lacks sensitivity. Rehabilitation robots, which have been the subject of intense inquiry over the last decade, are equipped with sensors that are used to develop objective measures of motor behaviors in a semiautomated way during therapy. This article reviews the current contributions of robot-assisted motor assessment of the upper limb. It summarizes the various measures related to movement performance, the models of motor recovery in stroke subjects and the relationship of robotic measures to standard clinical measures. It analyses the possibilities offered by current robotic assessment techniques and the aspects to address to make robotic assessment a mainstream motor assessment method.

Randomized Trial on the Effects of Attentional Focus on Motor Training of the Upper Extremity Using Robotics With Individuals After Chronic Stroke

“…EF external focus FMA Fugl-Meyer Assessment IF internal focus WMFT Wolf Motor Function Test parameter assessed by a circle drawing task on the InMotion ARM, provides precise objective data with a resolution of 0.1mm for position 20,21 and is predictive of upper extremity clinical measures such the FMA. 21 It measures the joint angle correlation between !2 joints and indicates the degree of coordination between multiple joints.…”

Quantitative assessment based on kinematic measures of functional impairments during upper extremity movements: A review

“…In a recent study, Balasubramanian exposed several properties that a smoothness measure must accomplish with the aim of this measure may be useful (Balasubramanian et al, 2012b), but these properties could be applied to all kinematic metrics found in literature: (i) monotonic response: an increase in the metrics must always have associated a change in the movement characteristic that represent in the same direction, positive or negative. This author exposed that a decrease in smoothness is accompanied by an increase in submovement number and the time interval between them (Balasubramanian et al, 2012b); (ii) robustness: metrics must have consistency between repeated measures, because this metrics must be robust against noise and other environmental factors; (iii) sensitive to change: metrics must detect changes in the upper extremity motor performance and (iv) dimensionless: the authors exposed that, concretely, a smoothness measure must be dimensionless because the smoothness depends on the wave form of the velocity or acceleration profile and not on the amplitude and duration of the curve (Balasubramanian et al, 2012b).…”

“…This author exposed that a decrease in smoothness is accompanied by an increase in submovement number and the time interval between them (Balasubramanian et al, 2012b); (ii) robustness: metrics must have consistency between repeated measures, because this metrics must be robust against noise and other environmental factors; (iii) sensitive to change: metrics must detect changes in the upper extremity motor performance and (iv) dimensionless: the authors exposed that, concretely, a smoothness measure must be dimensionless because the smoothness depends on the wave form of the velocity or acceleration profile and not on the amplitude and duration of the curve (Balasubramanian et al, 2012b).…”

“…2a). As smooth movements are composed of low frequency components and a non-smooth movement is composed of higher frequency components, the use of Fourier Transform is adequate for the analysis of movement smoothness (Balasubramanian et al, 2012b). To our knowledge, this metric has been proposed only for an author that proposes the spectral arc-length metric as a measure and it's computed from the amplitude and Fourier magnitude spectrum from the velocity profile of the hand movement (Balasubramanian et al, 2012b) as the metrics related to smoothness previously described.…”

A Gamified Approach for Hand Rehabilitation Device

“…The use of augmented feedback has been shown to enhance rehabilitation for the two aforementioned cases [4,5]. Furthermore, the use of devices that enable automatic recording and objective measurement of the patients' capabilities has been of growing interest, as most current rehabilitation practices are based on subjective progress evaluation [6,7].…”