Hand Passive Mobilization Performed with Robotic Assistance: Acute Effects on Upper Limb Perfusion and Spasticity in Stroke Survivors

Abstract

This single arm pre-post study aimed at evaluating the acute effects induced by a single session of robot-assisted passive hand mobilization on local perfusion and upper limb (UL) function in poststroke hemiparetic participants. Twenty-three patients with subacute or chronic stroke received 20 min passive mobilization of the paretic hand with robotic assistance. Near-infrared spectroscopy (NIRS) was used to detect changes in forearm tissue perfusion. Muscle tone of the paretic UL was assessed by the Modified Ashworth Scale (MAS). Symptoms concerning UL heaviness, joint stiffness, and pain were evaluated as secondary outcomes by self-reporting. Significant (p = 0.014) improvements were found in forearm perfusion when all fingers were mobilized simultaneously. After the intervention, MAS scores decreased globally, being the changes statistically significant for the wrist (from 1.6 ± 1.0 to 1.1 ± 1.0; p = 0.001) and fingers (from 1.2 ± 1.1 to 0.7 ± 0.9; p = 0.004). Subjects reported decreased UL heaviness and stiffness after treatment, especially for the hand, as well as diminished pain when present. This study supports novel evidence that hand robotic assistance promotes local UL circulation changes, may help in the management of spasticity, and acutely alleviates reported symptoms of heaviness, stiffness, and pain in subjects with poststroke hemiparesis. This opens new scenarios for the implications in everyday clinical practice. Clinical Trial Registration Number is NCT03243123.

Clasp-Knife Model of Muscle Spasticity for Simulation of Robot-Human Interaction

“…The rigidity model or also known as resistance, was defined by the increase in muscle tone feedback upon hypertonia proportional to angle of mobilization. The gain factor of rigidity is defined as the modulus of elasticity k, which contributes to the muscle tone based on the defined function of gross kinematics shown in (3). The equation presented in 3was an improvised version of equation presented by [11].…”

“…Mode selection was utilized for catch feature extraction to achieve repeatability. This is to avoid outliers caused by catch angle drifts influenced by angular velocity [13] and subsiding spasticity after continuous stretches [3], [10]. The averaged initial moment T 0 , modulus of elasticity k, and viscosity coefficient c, extracted were tested on several measures to obtain the best fitted features.…”

“…Another factor that contributes to the muscle tone sporadic pattern was temporal spasticity receding. This implication was resulted from consecutive continual stretches or intervention which may temporary recede the spasticity or stiffness [3], [10]. Subsequently, the features initially extracted may have drifts causing different proportionality in the pattern correlation gain.…”

“…The advancement of robotic rehabilitation system is promising in medical interventions, but little evidence supported its efficiency. Improvement in motor function has been observed in both long-term and short-term utilization of robotic assisted training platform [1]- [3]. However, the lack of medical integrated intervention in robotic system to accommodate subject's behavior according to their impairment level and progresses raised concerns in its efficiency in prolong rehabilitation regimen [4], [5].…”

“…Increase in muscle tone, commonly presented in subject with motor impairment, is generally rooted from muscle spasticity and rigidity upon passive mobilization [6]- [11]. Spasticity is a phenomenon that contributes to the increase in muscle tone proportional to the velocity of passive mobilization, whilst rigidity or resistance contributes to the increase in muscle tone due to hypertonia [3], [7], [9]- [11]. However, muscle tone increment does not develop linearly.…”