Posts Tagged stroke rehabilitation

[ARTICLE] Automated functional electrical stimulation training system for upper-limb function recovery in poststroke patients – Full Text

Highlights

• We developed an accelerometry system to detect the motion intention of poststroke patients for triggering FES.

• A visual game module was combined with this automated FES training system.

• This system can reduce variability in compound movements produced by poststroke patients and FES.

• An optimal threshold of triggering can defined for each patient for specific tasks.

Abstract

Background

This paper describes the design and test of an automated functional electrical stimulation (FES) system for poststroke rehabilitation training. The aim of automated FES is to synchronize electrically induced movements to assist residual movements of patients.

Methods

In the design of the FES system, an accelerometry module detected movement initiation and movement performed by post-stroke patients. The desired movement was displayed in visual game module. Synergy-based FES patterns were formulated using a normal pattern of muscle synergies from a healthy subject. Experiment 1 evaluated how different levels of trigger threshold or timing affected the variability of compound movements for forward reaching (FR) and lateral reaching (LR). Experiment 2 explored the effect of FES duration on compound movements.

Results

Synchronizing FES-assisted movements with residual voluntary movements produced more consistent compound movements. Matching the duration of synergy-based FES to that of patients could assist slower movements of patients with reduced RMS errors.

Conclusions

Evidence indicated that synchronization and matching duration with residual voluntary movements of patients could improve the consistency of FES assisted movements. Automated FES training can reduce the burden of therapists to monitor the training process, which may encourage patients to complete the training.

1. Introduction

Hemiplegia is a common sequela experienced by stroke survivors; it leads to dysfunction in the upper and lower limbs. Various rehabilitation strategies have been adopted to help patients recover limb motor functions [1,2]. The methods of rehabilitation training currently adopted in clinic for poststroke patients are generally high-intensity, repetitive task-oriented paradigms that are practiced daily with outcome feedback [1]. Information on movement kinematics and muscle activation is often used to adjust the training strategy and to ensure that recovery progresses in the desired direction [3,4]. An inappropriate regimen in rehabilitation training may result in abnormal activation of muscles [4] and may lead to reduced effectiveness in motor functional recovery or even increased risk of muscle contracture and spasticity [5,6].

Functional electrical stimulation (FES) may potentially increase the effectiveness of rehabilitation training. It uses electrical stimulation to assist patients in producing physical movements [7] and to facilitate the training of patients’ voluntary muscle contraction [8]. Several studies have reported that FES improves the plasticity of the cerebral cortex and can be easily performed by therapists because it does not require extensive manual operations [9][10][11][12]. Evidence suggests that FES is a useful modality for rehabilitation training with explainable neural mechanisms.

Progress has been made in FES applications to aid the recovery of motor functions in patients poststroke [13], and novel technologies have been integrated into FES paradigms, including gaming [14] and intelligence applications [15][16][17]. However, even though many control strategies have been developed to generate electrical stimulation patterns, these control strategies have not been widely translated into routine clinical uses [18][19][20][21][22] due to the controller is too complex, or needs to be adjusted according to the patient’s condition. Notably, a recent development in neuromotor control theory focusing on the modular organization of multiple muscle activations has led to the formulation of synergy-based FES strategies [23][24][25]. This approach provides a feasible solution for multi-channel FES control using residual muscle activities from the patient [23,[25][26][27][28]]; and it leverages the idea that normal movement kinematics can be generated out of muscle synergies [23].

We have evaluated the synergy-based FES training paradigm in a short-term clinical intervention study. A five day of intervention using synergy-based FES was carried out in poststroke patients. The outcome of the short-term intervention was measured by changes in Fugl-Meyer scores and movement kinematics. Results of evaluations prior to and post intervention showed improvements in both Fugl-Meyer scores and movement kinematics [25]. In a subsequent analysis, synergy-based FES training demonstrated evidence in reorganizing neural circuits in the brain, which led to repairing of impaired muscle activation pattern towards the normal pattern [29].

In this study, we present a design and verification of an autotriggered FES system with a synergy-based stimulation strategy and used RMS errors to analyze the movement process of the patients for each trial by using acceleration. This automated FES training system is designed to continuously integrate with FES clinical protocol therapeutic intervention in stroke rehabilitation [30].

The automated FES training system with a gaming interface and accelerometer triggered generation of multiple channels of electrical stimulations to a group of targeted muscles. In this automated FES training system, we anticipated improved consistency of patient movements during rehabilitative training. If successful, the study will provide a training protocol that induces smaller RMS errors across movement trials.

2. Methods and materials

2.1. Design of the automated FES system

Fig. 1 presents a schematic of the components and experimental environment of the automated trigger FES system. The system was composed of a gaming device, an elbow cast including a radiofrequency identification (RFID) reader and an accelerometer, a multichannel FES system, and a computer. The software for the development of the training game (named Picking Apples) was created using Unity (version 2018.1.3f1, Unity Technologies Inc., CA, USA). For ease of operation, the RFID device and the Li-ion battery were mounted in the elbow cast. The RFID information and accelerometer data were transmitted wirelessly by Bluetooth (Fig. 1A).

Fig 1
Fig. 1. Illustration of the FES system. (A) The automated trigger FES system operation. (B) The experimental setup with the automated trigger FES system. The experiment was performed using the affected upper limb of the subject, which was fixed in a golden yellow plastic elbow cast. Stimulation electrodes were placed on the seven target muscles. A pair of electrodes (4 cm × 4  cm) was placed on each muscle: the red electrode represented the positive pole and the black the negative. The initial and target points are circles with a diameter of 2.5 cm.

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Continue —-> https://www.sciencedirect.com/science/article/pii/S135045332030134X

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[Abstract] Functional electrical stimulation of the peroneal nerve improves post-stroke gait speed when combined with physiotherapy. A systematic review and meta-analysis

Abstract

Background: Functional electrical stimulation (FES) applied to the paretic peroneal nerve has positive clinical effects on foot drop secondary to stroke.

Objective: To evaluate the effectiveness of FES applied to the paretic peroneal nerve on gait speed, active ankle dorsiflexion mobility, balance, and functional mobility.

Methods: Electronic databases were searched for articles published from inception to January 2020. We included randomized controlled trials or crossover trials focused on determining the effects of FES combined or not with other therapies in individuals with foot drop after stroke. Characteristics of studies, participants, comparison groups, interventions, and outcomes were extracted. Statistical heterogeneity was assessed with the I2 statistic.

Results: We included 14 studies providing data for 1115 participants. FES did not enhance gait speed as compared with conventional treatments (i.e., supervised/unsupervised exercises and regular activities at home). FES combined with supervised exercises (i.e., physiotherapy) was better than supervised exercises alone for improving gait speed. We found no effect of FES combined with unsupervised exercises and inconclusive effects when FES was combined with regular activities at home. When FES was compared with conventional treatments, it improved ankle dorsiflexion, balance and functional mobility, albeit with high heterogeneity for these last 2 outcomes.

Conclusions: This meta-analysis revealed low quality of evidence for positive effects of FES on gait speed when combined with physiotherapy. FES can improve ankle dorsiflexion, balance, and functional mobility. However, considering the low quality of evidence and the high heterogeneity, these results must be interpreted carefully.

Source: https://pubmed.ncbi.nlm.nih.gov/32376404/

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[Abstract] Changes in electroencephalography complexity and functional magnetic resonance imaging connectivity following robotic hand training in chronic stroke

ABSTRACT

Introduction

In recent years, robotic training has been utilized for recovery of motor control in patients with motor deficits. Along with clinical assessment, electrical patterns in the brain have emerged as a marker for studying changes in the brain associated with brain injury and rehabilitation. These changes mainly involve an imbalance between the two hemispheres. We aimed to study the effect of brain computer interface (BCI)-based robotic hand training on stroke subjects using clinical assessment, electroencephalographic (EEG) complexity analysis, and functional magnetic resonance imaging (fMRI) connectivity analysis. 

Method: Resting-state simultaneous EEG-fMRI was conducted on 14 stroke subjects before and after training who underwent 20 sessions robot hand training. Fractal dimension (FD) analysis was used to assess neuronal impairment and functional recovery using the EEG data, and fMRI connectivity analysis was performed to assess changes in the connectivity of brain networks. 

Results: FD results indicated a significant asymmetric difference between the ipsilesional and contralesional hemispheres before training, which was reduced after robotic hand training. Moreover, a positive correlation between interhemispheric asymmetry change for central brain region and change in Fugl Meyer Assessment (FMA) scores for upper limb was observed. Connectivity results showed a significant difference between pre-training interhemispheric connectivity and post-training interhemispheric connectivity. Moreover, the change in connectivity correlated with the change in FMA scores. Results also indicated a correlation between the increase in connectivity for motor regions and decrease in FD interhemispheric asymmetry for central brain region covering the motor area. 

Conclusion: In conclusion, robotic hand training significantly facilitated stroke motor recovery, and FD, along with connectivity analysis can detect neuroplasticity changes

Source : https://www.tandfonline.com/doi/full/10.1080/10749357.2020.1803584?scroll=top&needAccess=true

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[Abstract] Impact of mHealth technology on adherence to healthy PA after stroke: a randomized study

ABSTRACT

Background

Physical activity (PA) is a key health behavior in people with stroke including risk reduction of recurrent stroke. Despite the beneficial effects of PA, many community-dwelling stroke survivors are physically inactive. Information and communication technologies are emerging as a possible method to promote adherence to PA.

Objective

The aim of this study is to investigate the effectiveness of a mobile-health (mHealth) App in improving levels of PA.

Methods

Forty-one chronic stroke survivors were randomized into an intervention group (IG) n=24 and a control group (CG) n=17. Participants in the IG were engaged in the Multimodal Rehabilitation Program (MMRP) that consisted on supervising adherence to PA through a mHealth app, participating in an 8-week rehabilitation program that included: aerobic, task-oriented, balance and stretching exercises. Participants also performed an ambulation program at home. The CG received a conventional rehabilitation program. Outcome variables were: adherence to PA, (walking and sitting time/day), walking speed (10MWT); walking endurance (6MWT); risk of falling (TUG); ADLs (Barthel); QoL (Eq-5D5L) and participant’s satisfaction.

Results

At the end of the intervention, community ambulation increased more in IG (38.95 min; SD: 20.37) than in the CG (9.47 min; SD: 12.11) (p≤.05). Sitting time was reduced by 2.96 (SD 2.0) hours/day in the IG and by 0.53 (SD 0.24) hours in the CG (p≤.05).

Conclusions

The results suggest that mHealth technology provides a novel way to promote adherence to home exercise programs post stroke. However, frequent support and guidance of caregiver is required to ensure the use of mobile devices.

Source: https://www.tandfonline.com/doi/full/10.1080/10749357.2019.1691816?scroll=top&needAccess=true

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[Abstract + References] A Feasibility Study on the Application of Virtual Reality Technology for the Rehabilitation of Upper Limbs After Stroke – Conference paper

Abstract

The purpose of this study was to explore the clinical feasibility of virtual reality (VR) for the rehabilitation of upper limbs of stroke. In this study, it was found and suggested that future research should focus on the content design and application of VR rehabilitation games. While using VR to increase the interestingness of rehabilitation, one can also integrate VR and other technologies to achieve complementary benefits. In addition, in terms of the design of VR rehabilitation games, it was suggested that VR rehabilitation game researchers investigate the needs of the target users and design VR games that meet the needs of the target users in future work. Finally, this study demonstrates the clinical feasibility of applying VR technology for the rehabilitation of upper limbs after stroke, as well as highlights the aspects that still need to be addressed by researchers. These aspects are important targets of designing a VR system suitable for stroke upper limb rehabilitation.

References

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via A Feasibility Study on the Application of Virtual Reality Technology for the Rehabilitation of Upper Limbs After Stroke | SpringerLink

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[Abstract] Comparison of the effects of and usability of active and active-assistive rehabilitation robots for the upper extremity function among patients with stroke: a single-blinded randomized controlled pilot study – Full Text PDF

Abstract

Background: Robotic rehabilitation of stroke survivors with upper extremity dysfunction yields different outcomes depending on the robot type. Considering that excessive dependence on assistive force provided by robots may interfere with the patient’s active learning and participation, we hypothesized that the use of an active-assistive robot does not lead to a more meaningful difference with respect to upper extremity rehabilitation than the use of an active robot. Accordingly, we aimed to evaluate the differences in the clinical and kinematic outcomes between active and active-assistive robotic rehabilitation among stroke survivors.

Methods: In this single-blinded randomized controlled trial, we assigned 20 stroke survivors with upper extremity dysfunction (Medical Research Council scale score, 3 or 4) to the active (ACT) and active-assistive (ACAS) robotic rehabilitation groups in a 1:1 ratio and administered 20 sessions of 30-minute robotic intervention (5 days/week, 4 weeks). The primary (Wolf Motor Function Test [WMFT]-score and -time: measures activity), and secondary (Fugl-Meyer Assessment [FMA] and Stroke Impact Scale [SIS] scores: measure impairment and participation, respectively; kinematic outcomes) outcome measures were determined at baseline, after 2 and 4 weeks of the intervention, and 4 weeks after the end of the intervention. Furthermore, we evaluated the usability of the robotic devices by conducting interviews with the patients, therapists, and physiatrists.

Results: In both the groups, the WMFT-score and -time improved over the course of the intervention. Time had a significant effect on the WMFT-score and -time, FMA-UE, FMA-prox, and SIS-strength; group × time interaction had a significant effect on SIS-function and SIS-social participation (all, p <0.05). The ACT group showed better improvement in participation and smoothness than the ACAS group. In contrast, the ACAS group exhibited better improvement in mean speed.

Conclusions: There were no differences between the two groups regarding the impairment and activity domains. However, the ACT robots were more beneficial than ACAS robots regarding participation and smoothness. Considering the high cost and complexity of ACAS robots, ACT robots may be more suitable for robotic rehabilitation in stroke survivors who can perform voluntary movement.

Source: https://www.researchsquare.com/article/rs-24709/v2?utm_source=researcher_app&utm_medium=referral&utm_campaign=RESR_MRKT_Researcher_inbound


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[Abstract] The Use of Virtual Reality Applications in Stroke Rehabilitation for Older Adults : Technology Enhanced Relearning

Abstract

After stroke rehabilitation is a long-term relearning process that can be divided into cognitive relearning, speech relearning and motoric relearning. Today with an aging population it it interesting to look at technology enhanced and game-based solutions that can facilitate independent living for older adults. The aim of the study was to identify and categorise recently conducted research in the field of virtual reality applications for older adults’ relearning after stroke. This study was conducted as a systematic literature review with results categorised in a pre-defined framework. Findings indicate that virtual reality-based stroke rehabilitation is an emerging field that can renew after stroke rehabilitation. Most found studies were on stroke patients’ motoric and game-based relearning, and with less studies on speech rehabilitation. The conclusion is that virtual reality systems should not replace the existing stroke rehabilitation, but rather to have the idea of combining and extending the traditional relearning process where human-to-human interaction is essential. Finally, there are no virtual reality applications that can fit all stroke patients’ needs, but a thoughtful selection of exercises that matches each individual user would have a potential to enhance the current relearning therapy for older adults after stroke.

via The Use of Virtual Reality Applications in Stroke Rehabilitation for Older Adults : Technology Enhanced Relearning

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[ARTICLE] Self-Support Biofeedback Training for Recovery From Motor Impairment After Stroke – Full Text

Abstract

Unilateral arm paralysis is a common symptom of stroke. In stroke patients, we observed that self-guided biomechanical support by the nonparetic arm unexpectedly triggered electromyographic activity with normal muscle synergies in the paretic arm. The muscle activities on the paretic arm became similar to the muscle activities on the nonparetic arm with self-supported exercises that were quantified by the similarity index (SI). Electromyogram (EMG) signals and functional near-infrared spectroscopy (fNIRS) of the patients (n=54) showed that self-supported exercise can have an immediate effect of improving the muscle activities by 40–80% according to SI quantification, and the muscle activities became much more similar to the muscle activities of the age-matched healthy subjects. Using this self-supported exercise, we investigated whether the recruitment of a patient’s contralesional nervous system could reactivate their ipsilesional neural circuits and stimulate functional recovery. We proposed biofeedback training with self-supported exercise where the muscle activities were visualized to encourage the appropriate neural pathways for activating the muscles of the paretic arm. We developed the biofeedback system and tested the recovery speed with the patients (n=27) for 2 months. The clinical tests showed that self-support-based biofeedback training improved SI approximately by 40%, Stroke Impairment Assessment Set (SIAS) by 35%, and Functional Independence Measure (FIM) by 20%.

Introduction

Stroke is the leading cause of long-term disability worldwide. Of more than 750,000 stroke victims in the United States each year [1], approximately two-thirds survive and require immediate rehabilitation to recover lost brain functions [2]. These stroke rehabilitation programs, of which direct and indirect costs were estimated to be 73.7 billion dollars in 2010 [3], aim to help survivors gain physical independence and better quality of life.

Stroke damage typically interrupts blood flow within one brain hemisphere, resulting in unilateral motor deficits, sensory deficits, or both. The preservation of long-term neural and synaptic plasticity is essential for the functional reorganization and recovery of neural pathways disrupted by stroke [4]–[5][6]. Stroke survivors typically require long-term, intensive rehabilitation training due to the length of time required for these recovery processes [7], [8]. The typical time course for partial recovery of arm movement after mild to moderate unilateral stroke damage is 2 to 6 months, depending on the severity of tissue damage and the latency of treatment initiation [9], [10]; however, patients with severe damage require additional months to years of rehabilitation. Given the economic burden on patients’ families and the medical system, novel rehabilitation methods that promote rapid and complete functional recovery are needed, along with a better understanding of the functional mechanisms and neural circuits that can participate in potential therapeutic processes. The identification of rehabilitation methods that can more effectively recover brain functions in the damaged hemisphere by re-engaging dormant motor functions should be a major global objective, from both economic and societal perspectives. Such an objective would require the interface of biology, medical research, and clinical practice [4].

Recently, candidate brain areas that become activated during stroke recovery have been identified in patients and animal models [7]. Brain imaging studies during stroke recovery suggest that the extent of functional motor recovery is associated with an increase in neuronal activity in the sensorimotor cortex of the ipsilesional hemisphere [10]–[11][12]. Other work has suggested that repetitive sensorimotor tasks may promote cortical reorganization and functional recovery in the ipsilesional area by increasing bilateral cortical activity to enhance neuroplasticity [13]. Activation in the contralesional hemisphere is also observed in the early stages of post-stroke patients. This activation has been explained by the emergence of communication in corticospinal projections that are silent in the healthy state [11], and it may also contribute to movement-related neural activity on the ipsilesional limb [14], [15]. Functional brain imaging studies show that activity of the contralesional hemisphere is increased early after stroke and gradually declines as recovery progresses [16]. The functional relevance of contralesional recruitment remains unclear [17], [18]. Some reported studies have linked high abnormal activity to a high inhibitory signaling drive onto the ipsilesional cortex [19], which may be a major contributor to motor impairment [6], [20]. Recent studies have also investigated the benefits of activating the contralesional and/or ipsilesional hemispheres in functional motor recovery using brain-computer interface (BCI) and transcranial magnetic stimulation (TMS) therapies [21], [22].

Current stroke rehabilitation approaches have largely focused on paretic limb rehabilitation interventions such as muscle strengthening and endurance training [23], forced-use therapy [24], constraint-induced exercise [25], robot therapy with biofeedback [26], nonparetic limb interventions (e.g., mirror-therapy [27], [28]), or bilateral/bimanual training [29], [30]. However, to date, none have clearly investigated how the use of a patient’s unaffected neural circuits in the healthy cortical hemisphere, or in the local peripheral circuit, affect the impaired limb in terms of functional rehabilitation of the bilateral cortical sensorimotor network [31].

In this study, we investigated a motor recovery approach for post-stroke unilateral arm impairment that combined sensory feedback, motor control, and motor intention. While observing a patient cohort with unilateral stroke damage and arm movement impairment, we found that a specific self-guided motion, which we termed self-supported exercise, surprisingly reactivated a healthy muscles pattern in the paretic arm. The key of the self-supported exercise is use of the nonparetic arm as a support to help move the paretic arm. First, we will show the observation of appropriate muscle recruitment and reduction of abnormal muscle synergies for post-stroke patients during the self-supported exercise, which are a common problem in stroke recovery [32]. Then, we conduct the experiments of functional imaging and electromyography recordings and characterized the neurobiology and physiology of this self-supported exercise. Based on this mechanism, we designed a rehabilitation program involving biofeedback-aided self-supported exercises that employ a patients’ self-initiated motor intention. The results of the comparative experiments between the feedback training cohorts and the control cohorts show that this method results in efficient recovery from post-stroke motion paralysis. Finally, we discuss the significance of our findings for the design of biologically-based stroke rehabilitation.[…]

via Self-Support Biofeedback Training for Recovery From Motor Impairment After Stroke – IEEE Journals & Magazine

FIGURE 2. - The four types of exercises.

FIGURE 2.The four types of exercises.

 

 

 

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[Abstract] Developments and clinical evaluations of robotic exoskeleton technology for human upper-limb rehabilitation

The development of upper limb and lower extremity robotic exoskeletons has emerged as a way to improve the quality of life as well as act as a primary rehabilitation device for individuals suffering from stroke or spinal cord injury. This paper contains extractions from the database of robotic exoskeleton for human upper limb rehabilitation and prime factors behind the burden of stroke. Various studies on stroke-induced deficiency from different countries were included in the review. The data were extracted from both clinical tests and surveys. Though there have been splendid advancements in this field, they still present enormous challenges. This paper provides the current developments, progress and research challenges in exoskeleton technology along with future research directions associated with the field of exoskeletons and orthosis. Robot-assisted training (RT) was found to be more effective than conventional training (CT) sessions. The present research articles in this field have many weaknesses as they do not cover the systematic review including the clinical studies and various surveys that lay a foundation for the requirement of robotic assistive devices. This review paper also discusses various exoskeleton devices that have been clinically evaluated.

 

via Developments and clinical evaluations of robotic exoskeleton technology for human upper-limb rehabilitation: Advanced Robotics: Vol 0, No 0

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[Abstract] FUNCTIONAL NEAR-INFRARED SPECTROSCOPY-BASED UPPER EXTREMITY FUNCTION REHABILITATION FOR STROKE SURVIVOR: A REVIEW

Recently, the functional near-infrared spectroscopy (600–900nm electromagnetic wave) (ff-NIRS)-based rehabilitation researches have been studied for understanding the human brain. Although ff-NIRS can successfully measure the relative blood concentration changes of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) as an assessment tool to identify significant clinical intervention during pre- and post-rehabilitation therapy for stroke survivors, there is insufficient information particularly on the use of ff-NIRS as a clinical translation in upper extremity function rehabilitation. In order to widely utilize the ff-NIRS for upper extremity rehabilitation, device information, experiment design, measurement procedure, and analyzing method are described for clinician aspect in this study. In addition, further research trend was introduced from previous studies for stroke survivor rehabilitation. The authors believed that the information provided in this study can be a useful guideline to encourage future researchers to focus on upper extremity function rehabilitation of stroke survivors.

 

 

via FUNCTIONAL NEAR-INFRARED SPECTROSCOPY-BASED UPPER EXTREMITY FUNCTION REHABILITATION FOR STROKE SURVIVOR: A REVIEW | Journal of Mechanics in Medicine and Biology

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