Functional Electrical Stimulation Research Articles

Abstract TP86: Stroke-Impaired Proprioception Limits Motor Recovery With BCI-FES Device

Introduction: Non-invasive brain-computer interface (BCI) therapy with contingent (i.e., closed-loop) functional electrical stimulation (FES) shows efficacy improving motor function. However, it is not well understood why some stroke survivors respond better to closed-looped BCI-FES intervention than others. Contingent BCI-FES intervention drives neuroplastic change toward adaptive functional connectivity in stroke-impaired sensorimotor brain areas by enriching the afferent feedback environment. The interruption of afferent-efferent feedback circuits is a neural correlate of long-term acquired disability and intactness of functional connections predicts recovery capacity. Studies suggest that proprioception is essential for motor learning and performance. Therefore, we hypothesize that proprioceptive intactness is essential for recovery of motor performance when using a BCI-FES. Methods: Participants with upper extremity motor loss resulting from stroke (n=35) completed up to 30 hours of closed-loop BCI-FES. Results: Change in ARAT scores over the course of the control period were compared to ARAT change scores over the intervention period at a one-month follow up assessment. On average, participants in the intervention realized greater change in ARAT (M = 2.11, SD = 4.68) than during the control phase (M = 0.294, SD = 3.53). An independent-samples t-test indicated this difference, 1.82, 95%CI [-4.17, 0.534], was not statistically significant, t (40.901) = -1.56, p = 0.126. Preliminary results indicate that Proprioceptive sensory loss has a greater limiting effect on recovery than cutaneous somatosensory loss. Discussion: Rehabilitating motor capacity after stroke depends on the intactness of sensorimotor neural circuits. If afference signals are missing or degraded due to stroke, motor recovery is poor. When the stroke spares afferent connectivity to the peripheral muscles, the sensorimotor cortex can leverage plasticity-based motor rehab strategies such as BCI-FES. Conclusion: Intactness of sensorimotor circuits is related to baseline severity of motor impairment as well as recovery of motor function. Efficacious prescription of BCI-FES intervention is best suited for patients with stroke-spared proprioception.

Symptomatic Treatment of Myelopathy.

This article discusses the effects of myelopathy on multiple organ systems and reviews the treatment and management of some of these effects. Recent advances in functional electrical stimulation, epidural spinal cord stimulation, robotics, and surgical techniques such as nerve transfer show promise in improving function in patients with myelopathy. Ongoing research in stem cell therapy and neurotherapeutic drugs may provide further therapeutic avenues in the future. Treatment for symptoms of spinal cord injury should be targeted toward patient goals. If nerve transfer for upper extremity function is considered, the patient should be evaluated at around 6 months from injury to assess for lower motor neuron involvement and possible time limitations of surgery. A patient with injury at or above the T6 level is at risk for autonomic dysreflexia, a life-threatening condition that presents with elevated blood pressure and can lead to emergent hypertensive crisis. Baclofen withdrawal due to baclofen pump failure or programming errors may also be life-threatening. Proper management of symptoms may help avoid complications such as autonomic dysreflexia, renal failure, heterotopic ossification, and fractures.

Efficacy of functional electrical stimulation of the lower extremities in stroke patients

Aim. To evaluate the efficacy of functional electrical stimulation of the lower extremities in stroke patients at different stages of motor rehabilitation.Materials and methods. The study involved 80 patients with motor disorders after stroke. The studied treatment methods included passive and passive-active functional electrical stimulation (FES) in combination with the THERATrainer Tigo and active FES (neuro-orthosis) WalkAide.Results. The analysis of motor status indicators, namely the Berg Balance Scale, 6-minute walk test, and dynamic walking index showed the maximum efficacy of active FES with biofeedback.Conclusion. When prescribing and selecting a method of electrical stimulation, preference in neurorehabilitation should be given to methods of passive-active and active functional stimulation.

Resource-Efficient Neural Network Architectures for Classifying Nerve Cuff Recordings on Implantable Devices.

Closed-loop functional electrical stimulation can use recorded nerve signals to create implantable systems that make decisions regarding nerve stimulation in real-time. Previous work demonstrated convolutional neural network (CNN) discrimination of activity from different neural pathways recorded by a high-density multi-contact nerve cuff electrode, achieving state-of-the-art performance but requiring too much data storage and power for a practical implementation on surgically implanted hardware. To reduce resource utilization for an implantable implementation, with minimal performance loss for CNNs that can discriminate between neural pathways in multi-contact cuff electrode recordings. Neural networks (NNs) were evaluated using rat sciatic nerve recordings previously collected using 56-channel cuff electrodes to capture spatiotemporal neural activity patterns. NNs were trained to classify individual, natural compound action potentials (nCAPs) elicited by sensory stimuli. Three architectures were explored: the previously reported ESCAPE-NET, a fully convolutional network, and a recurrent neural network. Variations of each architecture were evaluated based on F1-score, number of weights, and floating-point operations (FLOPs). NNs were identified that, when compared to ESCAPE-NET, require 1,132-1,787x fewer weights, 389-995x less memory, and 6-11,073x fewer FLOPs, while maintaining macro F1-scores of 0.70-0.71 compared to a baseline of 0.75. Memory requirements range from 22.69 KB to 58.11 KB, falling within on-chip memory sizes from published deep learning accelerators fabricated in ASIC technology. Reduced versions of ESCAPE-NET require significantly fewer resources without significant accuracy loss, thus can be more easily incorporated into a surgically implantable device that performs closed-loop responsive neural stimulation.

Novel Weft-Knitted Strain Sensors for Motion Capture.

Functional electrical stimulation (FES) aims to improve the gait pattern in cases of weak foot dorsiflexion (foot lifter weakness) and, therefore, increase the liveability of people suffering from chronic diseases of the central nervous system, e.g., multiple sclerosis. One important component of FES is the detection of the knee angle in order to enable the situational triggering of dorsiflexion in the right gait phase by electrical impulses. This paper presents an alternative approach to sensors for motion capture in the form of weft-knitted strain sensors. The use of textile-based strain sensors instead of conventional strain gauges offers the major advantage of direct integration during the knitting process and therefore a very discreet integration into garments. This in turn contributes to the fact that the FES system can be implemented in the form of functional leggings that are suitable for inconspicuous daily use without disturbing the wearer unnecessarily. Different designs of the weft-knitted strain sensor and the influence on its measurement behavior were investigated. The designs differed in terms of the integration direction of the sensor (wale- or course-wise) and the width of the sensor (number of loops) in a weft-knitted textile structure.

A Performance Evaluation of Repetitive and Iterative Learning Algorithms for Periodic Tracking Control of Functional Electrical Stimulation System

Functional electrical stimulation (FES) is a medical device that delivers electrical pulses to the muscle, allowing patients with spinal cord injuries to perform activities such as walking, cycling, and grasping. It is critical for the FES to generate stimuli with the appropriate controller so that the desired movements can be precisely tracked. By considering the repetitive nature of the movements, the learning-based control algorithms are utilized for regulating the FES. Iterative learning control (ILC) and repetitive control (RC) are two learning algorithms that can be used to accomplish accurate repetitive motions. This study investigates a variety of ILC and RC designs with distinct learning functions; this constitutes our contribution to the field. The FES model of ankle angle, which is in a class of discrete-time linear systems is considered in this study. Two learning functions, i.e., proportional, and zero-phase learning functions, are simulated for the second-order FES model running at a sampling time of 0.1 s. The results indicate the superior performance of the ILC and RC in terms of convergence rate using the zero-phase learning function. ILC and RC with a zero-phase learning function can reach a zero root-mean-square error in two iterations if the model of the plant is correct. This is faster than proportional-based ILC and RC, which takes about 40 iterations. This indicates that the zero-phase learning function requires two iterations to ensure that the patient's ankle angle precisely tracks the intended trajectory. However, the tracking performance is degraded for both control methods, especially when the model is subject to uncertainties. This specific problem can lead to future research directions.

Functional electrical stimulation to enhance reactive balance among people with hemiparetic stroke.

Individuals with stroke demonstrate a twofold higher fall incidence compared to healthy counterparts, potentially associated with deficits in reactive balance control, which is crucial for regaining balance from unpredictable perturbations to the body. Moreover, people with higher stroke-related motor impairment exhibit greater falls and cannot recover balance during higher perturbation intensities. Thus, they might need supplemental agents for fall prevention or even to be included in a perturbation-based protocol. Functional electrical stimulation is a widely used clinical modality for improving gait performance;however, it remains unknown whether it can enhance or interfere with reactive balance control. We recruited twelve ambulatory participants with hemiparetic stroke (61.48 ± 6.77years) and moderate-to-high motor impairment (Chedoke-McMaster Stroke Leg Assessment ≤ 4/7). Each participant experienced 4 unpredicted paretic gait-slips, with and without functional electrical stimulation (provided 50-500ms after perturbation) in random order. The paretic quadriceps muscle group was chosen to receive electrical stimulation, considering the role of support limb knee extensors for preventing limb-collapse. Outcomes includingprimary (laboratory falls), secondary (reactive stability, vertical limb support) and tertiary (compensatory step length, step initiation, execution time) measureswere compared between the two conditions. Participants demonstrated fewer falls, higher reactive stability, and higher vertical limb support (p < 0.05) following gait-slips with functional electrical stimulation compared to those without. This was accompanied by reduced step initiation time and a longer compensatory step (p < 0.05). The application of functional electrical stimulation to paretic quadriceps following gait-slips reduced laboratory fall incidence with enhanced reactive balance outcomes among people with higher stroke-related motor impairment. Our results lay the preliminary groundwork for understanding the instantaneous neuromodulatory effect of functional electrical stimulation in preventing gait-slip falls, future studies could test its therapeutic effect on reactive balance. Clinical registry number: NCT04957355.

Functional Electrostimulation System for a Prototype of a Human Hand Prosthesis Using Electromyography Signal Classification by Machine Learning Techniques

Functional electrical stimulation (FES) has been proven to be a reliable rehabilitation technique that increases muscle strength, reduces spasms, and enhances neuroplasticity in the long term. However, the available electrical stimulation systems on the market produce stimulation signals with no personalized voltage–current amplitudes, which could lead to muscle fatigue or incomplete enforced therapeutic motion. This work proposes an FES system aided by machine learning strategies that could adjust the stimulating signal based on electromyography (EMG) information. The regulation of the stimulated signal according to the patient’s therapeutic requirements is proposed. The EMG signals were classified using Long Short-Term Memory (LSTM) and a least-squares boosting ensemble model with an accuracy of 91.87% and 84.7%, respectively, when a set of 1200 signals from six different patients were used. The classification outcomes were used as input to a second regression machine learning algorithm that produced the adjusted electrostimulation signal required by the user according to their own electrophysiological conditions. The output of the second network served as input to a digitally processed electrostimulator that generated the necessary signal to be injected into the extremity to be treated. The results were evaluated in both simulated and robotized human hand scenarios. These evaluations demonstrated a two percent error when replicating the required movement enforced by the collected EMG information.

Machine-learning-based coordination of powered ankle-foot orthosis and functional electrical stimulation for gait control.

This study proposes a novel gait rehabilitation method that uses a hybrid system comprising a powered ankle-foot orthosis (PAFO) and FES, and presents its coordination control. The developed system provides assistance to the ankle joint in accordance with the degree of volitional participation of patients with post-stroke hemiplegia. The PAFO adopts the desired joint angle and impedance profile obtained from biomechanical simulation. The FES patterns of the tibialis anterior and soleus muscles are derived from predetermined electromyogram patterns of healthy individuals during gait and personalized stimulation parameters. The CNN-based estimation model predicts the volitional joint torque from the electromyogram of the patient, which is used to coordinate the contributions of the PAFO and FES. The effectiveness of the developed hybrid system was tested on healthy individuals during treadmill walking with and without considering the volitional muscle activity of the individual. The results showed that consideration of the volitional muscle activity significantly lowers the energy consumption by the PAFO and FES while providing adaptively assisted ankle motion depending on the volitional muscle activities of the individual. The proposed system has potential use as an assist-as-needed rehabilitation system, where it can improve the outcome of gait rehabilitation by inducing active patient participation depending on the stage of rehabilitation.

A Review of Current Perspectives on Motoric Insufficiency Rehabilitation following Pediatric Stroke.

Pediatric stroke (PS) is an injury caused by the occlusion or rupture of a blood vessel in the central nervous system (CNS) of children, before or after birth. Hemiparesis is the most common motoric deficit associated with PS in children. Therefore, it is important to emphasize that PS is a significant challenge for rehabilitation, especially since the consequences may also appear during the child's growth and development, reducing functional capacity. The plasticity of the child's CNS is an important predecessor of recovery, but disruption of the neural network, specific to an immature brain, can have harmful and potentially devastating consequences. In this review, we summarize the complexity of the consequences associated with PS and the possibilities and role of modern rehabilitation. An analysis of the current literature reveals that Constraint-Induced Movement Therapy, forced-use therapy, repetitive transcranial magnetic stimulation, functional electrical stimulation and robot-assisted therapy have demonstrated at least partial improvements in motor domains related to hemiparesis or hemiplegia caused by PS, but they are supported with different levels of evidence. Due to the lack of randomized controlled studies, the optimal rehabilitation treatment is still debatable, and therefore, most recommendations are primarily based on expert consensuses, opinions and an insufficient level of evidence.

Community mobility and participation assessment of manual wheelchair users: a review of current techniques and challenges.

According to the World Health Organization, hundreds of individuals commence wheelchair use daily, often due to an injury such as spinal cord injury or through a condition such as a stroke. However, manual wheelchair users typically experience reductions in individual community mobility and participation. In this review, articles from 2017 to 2023 were reviewed to identify means of measuring community mobility and participation of manual wheelchair users, factors that can impact these aspects, and current rehabilitation techniques for improving them. The selected articles document current best practices utilizing self-surveys, in-clinic assessments, and remote tracking through GPS and accelerometer data, which rehabilitation specialists can apply to track their patients' community mobility and participation accurately. Furthermore, rehabilitation methods such as wheelchair training programs, brain-computer interface triggered functional electric stimulation therapy, and community-based rehabilitation programs show potential to improve the community mobility and participation of manual wheelchair users. Recommendations were made to highlight potential avenues for future research.

Cycling using functional electrical stimulation therapy to improve motor function and activity in post-stroke individuals in early subacute phase: a systematic review with meta-analysis

BackgroundStroke necessitates interventions to rehabilitate individuals with disabilities, and the application of functional electrical stimulation therapy (FEST) has demonstrated potential in this regard. This study aimed to analyze the efficacy and effectiveness of cycling using FEST to improve motor function and lower limb activity in post-stroke individuals.MethodsWe performed a systematic review according to the recommendations of the PRISMA checklist, searching MEDLINE, Cochrane, EMBASE, LILACS, and PEDro databases by July 2022, without any date or language limitations. Studies were selected using the following terms: stroke, electrical stimulation therapy, cycling, and clinical trials. Randomized or quasi-randomized clinical trials that investigated the effectiveness of cycling using FEST combined with exercise programs and cycling using FEST alone for motor function and activity in subacute post-stroke individuals were included. The quality of included trials was assessed using the PEDro scores. Outcome data were extracted from eligible studies and combined in random-effects meta-analyses. The quality of evidence was determined according to the Grading of Recommendations Assessment, Development, and Evaluation system.ResultsFive randomized clinical trials involving 187 participants were included. Moderate-quality evidence indicates that cycling using FEST combined with exercise programs promotes relevant benefits in trunk control (MD 9 points, 95% CI 0.36–17.64) and walking distance (MD 94.84 m, 95% CI 39.63–150.05, I = 0%), the other outcomes had similar benefits. Cycling using FEST alone compared to exercise programs promotes similar benefits in strength, balance, walking speed, walking distance, and activities of daily living.ConclusionThis systematic review provides low- to moderate-quality evidence that cycling using FEST may be an effective strategy to consider in improving motor function and activity outcomes for post-stroke individuals in the early subacute phase.Review registration: PROSPERO (CRD42022345282).

Literature review: User interface of system functional electrical stimulation (FES) and arm robotic rehabilitation

Interface technology development for human-robot interaction (HRI) in rehabilitation systems has increased in recent years. HRI can effectively achieve specific motor goals desired in rehabilitation, such as combining human intentions and actions with robotic devices to perform the desired stroke rehabilitation movements. Rehabilitation devices are starting to be directed towards using devices that integrate functional electrical stimulation (FES) with robotic arms because they have succeeded in providing promising interventions to restore arm function by intensively activating the muscles of post-stroke patients. However, FES requires a high level of accuracy to position the limbs for the functional tasks given because excessive electrical stimulation can cause fatigue in the patient, so it is necessary to provide electrical stimulation with an amplitude that suits the patient's needs. Unfortunately, most studies have a constant voltage amplitude and do not consider the voltage that matches the patient's muscle needs; this treatment can cause fatigue in the patient. Robotic devices as rehabilitation aids have the potential to support external power and adapt electrical stimulation needs to the voltage amplitude applied to the FES. Integrating FES with a robotic arm support system into one hybrid neuroprosthesis is attractive because the mechanical device can complement muscle action and increase rehabilitation's repeatability and accuracy rate. The integration of FES and robotic arms is a promising approach in the future. This article reviews the state of the art regarding motor rehabilitation using functional electrical stimulation (FES) devices and robotic arms for the upper limbs of post-stroke patients. A narrative review was done through a literature search using the IEEE-Xplore, Scopus, and PubMed databases. Nine different rehabilitation system articles were identified. The selected systems were compared critically by considering the design and actuators, components, technological aspects, and technological challenges that could be developed in the future. This article also examines the development of HRI and emerging research trends in HRI-based rehabilitation

Resistance band training with functional electrical stimulation improves force control capabilities in older adults: a preliminary study.

Resistance band training (RBT) with functional electrical stimulation (FES) may be an effective exercise regimen for improving age-related motor impairments. This preliminary study investigated the potential effects of bimanual RBT with FES on upper limb motor functions in older adults. This study randomly assigned 22 elderly people to the bimanual RBT with FES (Bi-RBT+FES) group and the RBT without FES (Bi-RBT) group. All participants performed isometric hand-grip force control tasks in unimanual (dominant and non-dominant) and bimanual conditions before and after four weeks of exercise for each group. We quantified the mean force, force accuracy, force variability, and force regularity at two targeted force levels (i.e., 10 % and 40 % of maximum voluntary contraction; MVC) to estimate changes in force control capabilities. The results revealed that the Bi-RBT+FES group demonstrated a greater force accuracy in the dominant hand at 10 % of MVC after training. Non-dominant hands in the Bi-RBT+FES group increased force accuracy at 40 % of MVC and reduced force variability collapsed across two targeted force levels. Both groups showed a decrease in force regularity after training. These preliminary results indicate that Bi-RBT+FES may be a viable option to facilitate functional recovery of the upper limbs in older adults.

An Adaptive Hammerstein Model for FES-Induced Torque Prediction Based on Variable Forgetting Factor Recursive Least Squares Algorithm.

Modeling the muscle response to functional electrical stimulation (FES) is an important step during model-based FES control system design. The Hammerstein structure is widely used in simulating this nonlinear biomechanical response. However, a fixed relationship cannot cope well with the time-varying property of muscles and muscle fatigue. In this paper, we proposed an adaptive Hammerstein model to predict ankle joint torque induced by electrical stimulation, which used variable forgetting factor recursive least squares (VFFRLS) method to update the model parameters. To validate the proposed model, ten healthy individuals were recruited for short-duration FES experiments, ten for long-duration FES experiments, and three stroke patients for both. The isometric ankle dorsiflexion torque induced by FES was measured, and then the test performance of the fixed-parameter Hammerstein model, the adaptive Hammerstein model based on fixed forgetting factor recursive least squares (FFFRLS) and the adaptive Hammerstein model based on VFFRLS was compared. The goodness of fit, root mean square error, peak error and success rate were applied to evaluate the accuracy and stability of the model. The results indicate a significant improvement in both the accuracy and stability of the proposed adaptive model compared to the fixed-parameter model and the adaptive model based on FFFRLS. The proposed adaptive model enhances the ability of the model to cope with muscle changes.

Tremor Suppression Using Functional Electrical Stimulation.

Parkinson's disease (PD) and essential tremor are two major causes of pathological tremor among people over 60 years old. Due to the side effects and complications of traditional tremor management methods such as medication and deep brain surgery, non invasive tremor suppression methods have become more popular in recent years. Functional electrical stimulation (FES) is one of the methods used to reduce tremor in several studies. However, the effect of different FES parameters on tremor suppression and discomfort level, including amplitude, the number of pulses in each stimulation burst, frequency, and pulse width is yet to be studied for longer stimulation durations. Therefore, in this work, experiments were performed on 14 participants with PD to evaluate the effect of thirty seconds of out-of-phase electrical stimulation on wrist tremor at rest. Trials were conducted by varying the stimulation amplitude and the number of pulses while keeping the frequency and pulse width constant. Each test was repeated three times for each participant. The results showed an overall tremor suppression for 11 out of 14 participants and no average positive effects for three participants. It is concluded that despite the effectiveness of FES in tremor suppression, each set of FES parameters showed different suppression levels among participants due to the variability of tremor over time. Thus, for this method to be effective, an adaptive control system would be required to tune FES parameters in real time according to changes in tremor during extended stimulation periods.

Simulation of FES on the forearm with muscle-specific activation resolution.

Functional electrical stimulation (FES) is an established method of supporting neurological rehabilitation. However, particularly on the forearm, it still cannot elicit selective muscle activations that form the basis of complex hand movements. Current research approaches in the context of selective muscle activation often attempt to enable targeted stimulation by increasing the number of electrodes and combining them in electrode arrays. In order to determine the best stimulation positions and settings, manual or semi-automated algorithms are used. This approach is limited due to experimental limitations. The supportive use of simulation studies is well-established, but existing simulation models are not suitable for analyses of selective muscle activation due to missing or arbitrarily arranged innervation zones. This study introduces a new modeling method to design a person-specific digital twin that enables the prediction of muscle activations during FES on the forearm. The designed individual model consists of three parts: an anatomically based 3D volume conductor, a muscle-specific nerve fiber arrangement in various regions of interest (ROIs), and a standard nerve model. All processes were embedded in scripts or macros to enable automated changes to the model and the simulation setup. The experimental evaluation of simulated strength-duration diagrams showed good coincidence. The relative differences of the simulated amplitudes to the mean amplitude of the four experiments were in the same range as the inter-experimental differences, with mean values between 0.005 and 0.045. Based on these results, muscle-specific activation thresholds were determined and integrated into the simulation process. With this modification, simulated force-intensity curves showed good agreement with additionally measured curves. The results show that the model is suitable for simulating realistic muscle-specific activations. Since complex hand movements are physiologically composed of individual, selective muscle activations, it can be assumed that the model is also suitable for simulating these movements. Therefore, this study presents a new and very promising approach for developing new applications and products in the context of the rehabilitation of sensorimotor disorders.

TREINAMENTO INTERVALADO DE ALTA INTENSIDADE EM PESSOAS COM LESÃO DA MEDULA ESPINHAL: REVISÃO SISTEMÁTICA

ABSTRACT Objective: Analyze the effects of high-intensity interval training (HIIT) on cardiometabolic parameters, and cardiorespiratory fitness to compile the most used HIIT training types in adults with spinal cord injury (SCI). Methods: This is a systematic review of searches performed in the electronic databases PubMed / Medline, Science Direct, and Google Scholar. Studies included I) needed to apply HIIT training II) adults with SCI to analyze III) cardiometabolic aspects and cardiorespiratory fitness. Two independent reviewers selected the articles for inclusion, extracted their data, and assessed their methodological quality. Results: 654 studies were found. Thus, 12 studies, 11 pre- and post-intervention, and one control group (CG) with 106 participants were analyzed. Pre- and post-HIITT intervention results revealed significant improvement in cardiorespiratory fitness and cardiometabolic aspects (VO2peak, LDH, HDL, insulin resistance). In addition, GC results revealed significant improvement in cardiorespiratory fitness observed in the intervention group (HIIT) compared to the moderate-low intensity (GC) group. Seven studies used the arm ergometer as the primary exercise modality. Two studies described functional electrical stimulation (FES) performed with the arm ergometer plus electrical stimulation in the lower limbs. None reported heart rate dynamics during the study period. Conclusion: High-intensity interval training improves physical fitness and cardiometabolic health in adults with SCI. Evidence level II; Systematic Review of level II studies.

Enhancement of Functional Corticomuscular Coupling After Functional Electrical Stimulation in Healthy Young Adults

Enhancement of Functional Corticomuscular Coupling After Functional Electrical Stimulation in Healthy Young Adults

Effectiveness of physiotherapy interventions in alleviating symptoms and complications of diabetic peripheral neuropathy: A review of evidence

This review presents a comprehensive analysis of physiotherapy interventions for Diabetic Peripheral Neuropathy (DPN), summarizing key findings derived from an examination of approximately 654 studies, including randomized controlled trials, systematic reviews, meta-analyses, conducted up to September 2021. Ultimately, 19 studies met the inclusion and exclusion criteria. The findings affirm the effectiveness of physiotherapy interventions in enhancing the quality of life for individuals with DPN. Notable discoveries encompass the positive impact of various interventions, such as aerobic and resistance exercises, electrical stimulation modalities (e.g., transcutaneous electrical nerve stimulation, percutaneous electrical nerve stimulation, and functional electrical stimulation), as well as manual therapies (e.g., massage and joint mobilization). These interventions have demonstrated their ability to reduce pain, enhance balance, and improve sensory function. While acknowledging certain limitations, this review underscores the potential of evidence-based physiotherapy interventions to optimize DPN management and enhance patient outcomes.