Posts Tagged Ankle Spasticity
[ARTICLE] Reinforced Feedback in Virtual Environment for Plantar Flexor Poststroke Spasticity Reduction and Gait Function Improvement – Full Text
Posted by Kostas Pantremenos in Gait Rehabilitation - Foot Drop, REHABILITATION, Spasticity, Virtual reality rehabilitation on July 4, 2020
Abstract
Background
Ankle spasticity is a frequent phenomenon that limits functionality in poststroke patients.
Objectives
Our aim was to determine if there was decreased spasticity in the ankle plantar flex (PF) muscles in the plegic lower extremity (LE) and improvement of gait function in stroke patients after traditional rehabilitation (TR) in combination with virtual reality with reinforced feedback, which is termed “reinforced feedback virtual environment” (RFVE).
Methods
The evaluation, before and after treatment, of 10 hemiparetic patients was performed using the Modified Ashworth Scale (MAS), Functional Ambulatory Category (FAC), and Functional Independence Measure (FIM). The intervention consisted of 1 hour/day of TR plus 1 hour/day of RFVE (5 days/week for 3 weeks; 15 sessions in total).
Results
The MAS and FAC reached statistical significance (P < 0.05). The changes in the FIM did not reach statistical significance (P=0.066). The analysis between the ischemic and haemorrhagic patients showed significant differences in favour of the haemorrhagic group in the FIM scale. A significant correlation between the FAC and the months after the stroke was established (P=−0.711). Indeed, patients who most increased their score on the FAC at the end of treatment were those who started the treatment earliest after stroke.
Conclusions
The combined treatment of TR and RFVE showed encouraging results regarding the reduction of spasticity and improvement of gait function. An early commencement of the treatment seems to be ideal, and future research should increase the sample size and assessment tools.
1. Introduction
Stroke patients suffer several deficits that affect (mildly to severely) the cognitive, psychological, or motor areas of the brain, at the expense of their quality of life [1]. Although rehabilitation techniques do not only act on the motor deficits [2], the effects associated with the interruptions of the corticospinal tract, as well as the subsequent adaptive changes, commonly require specific interventions. Among them, the most important changes are muscle weakness, loss of dexterity, cocontraction, and increased tone and abnormal postures [3].
Hemiparesis is the most common problem in poststroke patients, and its severity correlates with the functional capabilities of the individual [4], being that impairment of gait function is one of the most important limitations. Furthermore, weakness of the ankle muscles caused by injury to supraspinal centres and spasticity are the most frequent phenomena that limit functionality [5]. The degree of spasticity of the affected ankle plantar flex (PF) muscles primarily influences gait asymmetry [6], which is, in addition to depression, another independent factor for predicting falls in ambulatory stroke patients [7]. Physiological changes in the paretic muscles, passive or active restraint of agonist activation, and abnormal muscle activation patterns (coactivation of the opposing lower extremity (LE)) have been shown to occur after a stroke and can lead to joint stiffness (foot deformities are present in 30% of stroke patients) [8], deficits in postural stabilization, and reduced muscle force generation [9]. To enhance this postural stability during gait, it seems that poststroke patients with impaired balance and paretic ankle muscle weakness use a compensation strategy of increased ankle muscle coactivation on the paretic side [10].
Scientific evidence shows that the use of mixed techniques with different physiotherapy approaches under very broad classifications (i.e., neurophysiological, motor learning, and orthopaedic) provides significantly better results regarding recovery of autonomy, postural control, and recovery of LE in the hemiparetic patient (HP) as compared to no treatment or the use of placebo [11]. Within the latter techniques, we may emphasize the relearning of motor-oriented tasks [12], as well as other approaches based on new technologies (e.g., treadmill [13], robotics [14–16], and functional electrical stimulation (FES) [17]), which are often used as additional treatments to traditional rehabilitation (TR). However, some of these emerging therapies, such as vibratory platforms [18], have not been shown yet to produce as positive results as the prior ones. Thus, obtaining better results with mixed and more intensive rehabilitation treatment has been demonstrated [19, 20]. Therefore, we propose to add the use of virtual reality (VR) techniques to TR to optimize results. We can use the label “VR-based therapy” because it acknowledges the VR system as the tool being used by the clinician in therapy, not as the therapy itself. It is essential to transfer the obtained gains in VR-based therapy to better functioning in the real world [21]. In this way, the intersection of a promising technological tool with the skills of confident and competent clinicians will more likely yield high-quality evidence and enhanced outcomes for physical rehabilitation patients [22].
The application of VR to motor recovery of the hemiparetic LE (HLE) has been addressed by several authors in the last decade [23–28], obtaining satisfactory results, in general terms, in the increase of walking speed [22, 24, 25], cortical reorganization, balance, and kinetic-kinematic parameters. Other authors have reported improvements in the balance of patients treated with nonimmersive VR systems based on video games, using specific software and with the guidance of a therapist [29]. A recent study showed that VR-based eccentric training using a slow velocity is effective for improving LE muscle activity to the gastrocnemius muscle and balance in stroke [30]; however, the spasticity of PF muscles was not analysed in any of these studies.
Virtual reality acts as an augmented environment where feedback can be delivered in the form of enhanced information about knowledge of results and knowledge of performance (KP) [31]. There are systems that use this KP through the representation of trajectories during the execution of the movement, as well as visualizing these once performed, to visually check the amount of deviation from the path proposed by the physiotherapist. Several studies demonstrated that this treatment enriched by reinforced feedback in a virtual environment (RFVE) may be more effective than TR to improve the motor function of the upper limb after stroke [31, 32]. In our study, the use of a VR-based system, together with a motion capture tool, allowed us to modify the artificial environment with which the patient could interact, exploiting some mechanisms of motor learning [33, 34], thus allowing greater flexibility and effective improvement in task learning. This system has been highly successful in the functional recovery of the hemiparetic upper extremity [31, 33–36], but its combined effect with TR on the LE has not yet reported conclusive data [37]. The continuous supply of feedback during voluntary movement makes it possible to continuously adjust contractile activity [38], thus mitigating increments in spasticity and cocontraction processes of the patient. These settings are of great significance in motor control, and certain variables (such as the speed of the movement) can be controlled, having a direct influence on spasticity. In this line, the aim of this study is to determine if there is a decrease in the spasticity of the PF muscles and improved gait function, following a program that includes the combination of TR and VR with reinforced feedback, which is called “reinforced feedback virtual environment” (RFVE).
Moreover, as a complementary aim, we analysed the modulatory effects of demographic and clinical factors on the recovery of patients treated with TR and VR. The analysis of the influence of these modulatory variables was focused on better highlighting what type of patients would benefit most from the combined treatment of TR and VR. Particularly, we looked into the effects of age and time elapsed from the moment the stroke occurs until the patient starts neurorehabilitation. As shown in various studies, a better outcome for treatment can be expected for younger patients and for those who start the treatment earlier [39]. Also, comparisons were made between patients with an ischemic and haemorrhagic stroke, since differences in their recovery prognostic have been reported elsewhere, with better outcomes for the latter group [40].[…]
Figure 2. Patient carrying out a task set out by the physiotherapist in front of the RFVE equipment.
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[ARTICLE] Robot-Assisted Rehabilitation of Ankle Plantar Flexors Spasticity: A Three-Month Study with Proprioceptive Neuromuscular Facilitation – Full Text
Posted by Kostas Pantremenos in Gait Rehabilitation - Foot Drop, Rehabilitation robotics, Spasticity on October 25, 2016
Abstract
In this paper, we aim to investigate the effect of Proprioceptive Neuromuscular Facilitation (PNF) based rehabilitation for ankle plantar flexors spasticity by using a Robotic Ankle-foot Rehabilitation System (RARS). A modified robot-assisted system was proposed and seven post-stroke patients with hemiplegic spastic ankles participated a three-month of robotic PNF training. Their impaired sides were used as the experimental group while their unimpaired sides as the control group. A robotic intervention for the experimental group generally started from a two minutes passive stretching to warm-up or relax the soleus and gastrocnemius muscle and also ended with the same one. Then a PNF training session included 30 trails was activated between them. The rehabilitation trainings were carried out three times a week as an addition of their regular rehabilitation exercise. Passive ankle joint range of motion, resistance torque and stiffness were measured in both ankles before and after the intervention. The changes in Achilles’ tendon length, walking speed, and lower limb function were also evaluated by the same physician or physiotherapist for each participant. Biomechanical measurements before interventions showed significant difference between the experimental group and the control group due to ankle spasticity. For the control group, there was no significant difference in the three months with no robotic intervention. But for the experimental group, passive dorsiflexion range of motion increased ($p0.05$). The robotic rehabilitation also improved the muscle strength ($p0.05$) and fast walking speed ($p<0.05$). These results indicated that PNF based robotic intervention could significantly alleviate lower limb spasticity and improve the motor function in chronic stroke participant. The robotic system could potentially be used as an effective tool in post-stroke rehabilitation training.
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