Biofeedback for Post-stroke Gait Retraining: A Review of Current Evidence and Future Research Directions in the Context of Emerging Technologies

Effectiveness of sensor-based interventions in improving gait and balance performance in older adults: systematic review and meta-analysis of randomized controlled trials

BACKGROUND

Sensor-based interventions (SI) have been suggested as an alternative rehabilitation treatment to improve older adults' functional performance. However, the effectiveness of different sensor technologies in improving gait and balance remains unclear and requires further investigation.

METHODS

Ten databases (Academic Search Premier; Cumulative Index to Nursing and Allied Health Literature, Complete; Cochrane Central Register of Controlled Trials; MEDLINE; PubMed; Web of Science; OpenDissertations; Open grey; ProQuest; and Grey literature report) were searched for relevant articles published up to December 20, 2022. Conventional functional assessments, including the Timed Up and Go (TUG) test, normal gait speed, Berg Balance Scale (BBS), 6-Minute Walk Test (6MWT), and Falling Efficacy Scale-International (FES-I), were used as the evaluation outcomes reflecting gait and balance performance. We first meta-analyzed the effectiveness of SI, which included optical sensors (OPTS), perception sensors (PCPS), and wearable sensors (WS), compared with control groups, which included non-treatment intervention (NTI) and traditional physical exercise intervention (TPEI). We further conducted sub-group analysis to compare the effectiveness of SI (OPTS, PCPS, and WS) with TPEI groups and compared each SI subtype with control (NTI and TPEI) and TPEI groups.

RESULTS

We scanned 6255 articles and performed meta-analyses of 58 selected trials (sample size = 2713). The results showed that SI groups were significantly more effective than control or TPEI groups (p < 0.000) in improving gait and balance performance. The subgroup meta-analyses between OPTS groups and TPEI groups revealed clear statistically significant differences in effectiveness for TUG test (mean difference (MD) = - 0.681 s; p < 0.000), normal gait speed (MD = 4.244 cm/s; p < 0.000), BBS (MD = 2.325; p = 0.001), 6MWT (MD = 25.166 m; p < 0.000), and FES-I scores (MD = - 2.036; p = 0.036). PCPS groups also presented statistically significant differences with TPEI groups in gait and balance assessments for normal gait speed (MD = 4.382 cm/s; p = 0.034), BBS (MD = 1.874; p < 0.000), 6MWT (MD = 21.904 m; p < 0.000), and FES-I scores (MD = - 1.161; p < 0.000), except for the TUG test (MD = - 0.226 s; p = 0.106). There were no statistically significant differences in TUG test (MD = - 1.255 s; p = 0.101) or normal gait speed (MD = 6.682 cm/s; p = 0.109) between WS groups and control groups.

CONCLUSIONS

SI with biofeedback has a positive effect on gait and balance improvement among a mixed population of older adults. Specifically, OPTS and PCPS groups were statistically better than TPEI groups at improving gait and balance performance, whereas only the group comparison in BBS and 6MWT can reach the minimal clinically important difference. Moreover, WS groups showed no statistically or clinically significant positive effect on gait and balance improvement compared with control groups. More studies are recommended to verify the effectiveness of specific SI. Research registration PROSPERO platform: CRD42022362817. Registered on 7/10/2022.

Efficacy of a Single-Bout of Auditory Feedback Training on Gait Performance and Kinematics in Healthy Young Adults

This study investigated the immediate effects of auditory feedback training on gait performance and kinematics in 19 healthy young adults, focusing on bilateral changes, despite unilateral training. Baseline and post-training kinematic measurements, as well as the feedback training were performed on a treadmill with a constant velocity. Significant improvements were seen in step length (trained: 590.7 mm to 611.1 mm, 95%CI [7.609, 24.373]; untrained: 591.1 mm to 628.7 mm, 95%CI [10.698, 30.835]), toe clearance (trained: 13.9 mm to 16.5 mm, 95%CI [1.284, 3.503]; untrained: 11.8 mm to 13.7 mm, 95%CI [1.763, 3.612]), ankle dorsiflexion angle at terminal stance (trained: 8.3 deg to 10.5 deg, 95%CI [1.092, 3.319]; untrained: 9.2 deg to 12.0 deg, 95%CI [1.676, 3.573]), hip flexion angular velocity, (trained: -126.5 deg/s to -131.0 deg/s, 95%CI [-9.054, -2.623]; untrained: -130.2 deg/s to -135.3 deg/s, 95%CI [-10.536, -1.675]), ankle angular velocity at terminal stance (trained: -344.7 deg/s to -359.1 deg/s, 95%CI [-47.540, -14.924]; untrained: -340.3 deg/s to -376.9 deg/s, 95%CI [-37.280, -13.166s]), and gastrocnemius EMG activity (trained: 0.60 to 0.66, 95%CI [0.014, 0.258]; untrained: 0.55 to 0.65, 95%CI [0.049, 0.214]). These findings demonstrate the efficacy of auditory feedback training in enhancing key gait parameters, highlighting the bilateral benefits from unilateral training.

Motor Learning Following Stroke: Mechanisms of Learning and Techniques to Augment Neuroplasticity

Sensorimotor impairments are common after stroke requiring stroke survivors to relearn lost motor skills or acquire new ones in order to engage in daily activities. Thus, motor skill learning is a cornerstone of stroke rehabilitation. This article provides an overview of motor control and learning theories that inform stroke rehabilitation interventions, discusses principles of neuroplasticity, and provides a summary of practice conditions and techniques that can be used to augment motor learning and neuroplasticity in stroke rehabilitation.

Real-Time Visual Kinematic Feedback During Overground Walking Improves Gait Biomechanics in Individuals Post-Stroke

Treadmill-based gait rehabilitation protocols have shown that real-time visual biofeedback can promote learning of improved gait biomechanics, but previous feedback work has largely involved treadmill walking and not overground gait. The objective of this study was to determine the short-term response to hip extension visual biofeedback, with individuals post-stroke, during unconstrained overground walking. Individuals post-stroke typically have a decreased paretic propulsion and walking speed, but increasing hip extension angle may enable the paretic leg to better translate force anteriorly during push-off. Fourteen individuals post-stroke completed overground walking, one 6-min control bout without feedback, and three 6-min training bouts with real-time feedback. Data were recorded before and after the control bout, before and after the first training bout, and after the third training bout to assess the effects of training. Visual biofeedback consisted of a display attached to eyeglasses that showed one horizontal bar indicating the user's current hip angle and another symbolizing the target hip extension to be reached during training. On average, paretic hip extension angle (p = 0.014), trailing limb angle (p = 0.025), and propulsion (p = 0.011) were significantly higher after training. Walking speed increased but was not significantly higher after training (p = 0.089). Individuals demonstrated a greater increase in their hip extension angle (p = 0.035) and propulsion (p = 0.030) after the walking bout with feedback compared to the control bout, but changes in walking speed did not significantly differ (p = 0.583) between a control walking bout and a feedback bout. Our results show the feasibility of overground visual gait feedback and suggest that feedback regarding paretic hip extension angle enabled many individuals post-stroke to improve parameters important for their walking function.

Effect of Anterioposterior Weight-Shift Training with Visual Biofeedback in Patients with Step Length Asymmetry after Subacute Stroke

Step length asymmetry is a characteristic feature of gait in post-stroke patients. A novel anterioposterior weight-shift training method with visual biofeedback (AP training) was developed to improve the forward progression of the trunk. This study aimed to investigate the effect of AP training on gait asymmetries, patterns, and gait-related function in subacute stroke patients. Forty-six subacute stroke patients were randomly assigned to the AP training group or the control group. The AP training group received conventional gait training and AP training five times per week for 4 weeks. The control group received the same intensity of conventional gait training with patient education for self-anterior weight shifting. Plantar pressure analysis, gait analysis, energy consumption, and gait-related behavioral parameters were assessed before and after training. The AP training group showed significant improvement in step length asymmetry, forefoot contact area and pressure, Berg balance scale score, and Fugl-Meyer assessment scale of lower extremity score compared to the control group (p < 0.05). However, there was no significant between-group difference with respect to energy cost and kinetic and kinematic gait parameters. In conclusion, AP training may help improve the asymmetric step length in stroke patients, and also improve anterior weight shifting, balance, and motor function in subacute stroke survivors.

Technologies in Home-Based Digital Rehabilitation: Scoping Review

BACKGROUND

Due to growing pressure on the health care system, a shift in rehabilitation to home settings is essential. However, efficient support for home-based rehabilitation is lacking. The COVID-19 pandemic has further exacerbated these challenges and has affected individuals and health care professionals during rehabilitation. Digital rehabilitation (DR) could support home-based rehabilitation. To develop and implement DR solutions that meet clients' needs and ease the growing pressure on the health care system, it is necessary to provide an overview of existing, relevant, and future solutions shaping the constantly evolving market of technologies for home-based DR.

OBJECTIVE

In this scoping review, we aimed to identify digital technologies for home-based DR, predict new or emerging DR trends, and report on the influences of the COVID-19 pandemic on DR.

METHODS

The scoping review followed the framework of Arksey and O'Malley, with improvements made by Levac et al. A literature search was performed in PubMed, Embase, CINAHL, PsycINFO, and the Cochrane Library. The search spanned January 2015 to January 2022. A bibliometric analysis was performed to provide an overview of the included references, and a co-occurrence analysis identified the technologies for home-based DR. A full-text analysis of all included reviews filtered the trends for home-based DR. A gray literature search supplemented the results of the review analysis and revealed the influences of the COVID-19 pandemic on the development of DR.

RESULTS

A total of 2437 records were included in the bibliometric analysis and 95 in the full-text analysis, and 40 records were included as a result of the gray literature search. Sensors, robotic devices, gamification, virtual and augmented reality, and digital and mobile apps are already used in home-based DR; however, artificial intelligence and machine learning, exoskeletons, and digital and mobile apps represent new and emerging trends. Advantages and disadvantages were displayed for all technologies. The COVID-19 pandemic has led to an increased use of digital technologies as remote approaches but has not led to the development of new technologies.

CONCLUSIONS

Multiple tools are available and implemented for home-based DR; however, some technologies face limitations in the application of home-based rehabilitation. However, artificial intelligence and machine learning could be instrumental in redesigning rehabilitation and addressing future challenges of the health care system, and the rehabilitation sector in particular. The results show the need for feasible and effective approaches to implement DR that meet clients' needs and adhere to framework conditions, regardless of exceptional situations such as the COVID-19 pandemic.

Gait speed and individual characteristics are related to specific gait metrics in neurotypical adults

Gait biofeedback is a well-studied strategy to reduce gait impairments such as propulsion deficits or asymmetric step lengths. With biofeedback, participants alter their walking to reach the desired magnitude of a specific parameter (the biofeedback target) with each step. Biofeedback of anterior ground reaction force and step length is commonly used in post-stroke gait training as these variables are associated with self-selected gait speed, fall risk, and the energy cost of walking. However, biofeedback targets are often set as a function of an individual's baseline walking pattern, which may not reflect the ideal magnitude of that gait parameter. Here we developed prediction models based on speed, leg length, mass, sex, and age to predict anterior ground reaction force and step length of neurotypical adults as a possible method for personalized biofeedback. Prediction of these values on an independent dataset demonstrated strong agreement with actual values, indicating that neurotypical anterior ground reaction forces can be estimated from an individual's leg length, mass, and gait speed, and step lengths can be estimated from individual's leg length, mass, age, sex, and gait speed. Unlike approaches that rely on an individual's baseline gait, this approach provides a standardized method to personalize gait biofeedback targets based on the walking patterns exhibited by neurotypical individuals with similar characteristics walking at similar speeds without the risk of over- or underestimating the ideal values that could limit feedback-mediated reductions in gait impairments.

Motor control complexity can be dynamically simplified during gait pattern exploration using motor control-based biofeedback

Understanding how the central nervous system coordinates diverse motor outputs has been a topic of extensive investigation. Although it is generally accepted that a small set of synergies underlies many common activities, such as walking, whether synergies are equally robust across a broader array of gait patterns or can be flexibly modified remains unclear. Here, we evaluated the extent to which synergies changed as nondisabled adults (n = 14) explored gait patterns using custom biofeedback. Secondarily, we used Bayesian additive regression trees to identify factors that were associated with synergy modulation. Participants explored 41.1 ± 8.0 gait patterns using biofeedback, during which synergy recruitment changed depending on the type and magnitude of gait pattern modification. Specifically, a consistent set of synergies was recruited to accommodate small deviations from baseline, but additional synergies emerged for larger gait changes. Synergy complexity was similarly modulated; complexity decreased for 82.6% of the attempted gait patterns, but distal gait mechanics were strongly associated with these changes. In particular, greater ankle dorsiflexion moments and knee flexion through stance, as well as greater knee extension moments at initial contact, corresponded to a reduction in synergy complexity. Taken together, these results suggest that the central nervous system preferentially adopts a low-dimensional, largely invariant control strategy but can modify that strategy to produce diverse gait patterns. Beyond improving understanding of how synergies are recruited during gait, study outcomes may also help identify parameters that can be targeted with interventions to alter synergies and improve motor control after neurological injury.NEW & NOTEWORTHY We used a motor control-based biofeedback system and machine learning to characterize the extent to which nondisabled adults can modulate synergies during gait pattern exploration. Results revealed that a small library of synergies underlies an array of gait patterns but that recruitment from this library changes as a function of the imposed biomechanical constraints. Our findings enhance understanding of the neural control of gait and may inform biofeedback strategies to improve synergy recruitment after neurological injury.

A portable visual biofeedback device can accurately measure and improve hip extension angle in individuals post-stroke

BACKGROUND

Visual biofeedback has shown success in improving gait mechanics in individuals post-stroke but has typically been restricted to use on a treadmill or a short walkway. Using real-time visual biofeedback during overground walking could increase the ease of clinical translation of this method. The objective was to investigate the reliability of a real-time hip extension feedback device during unconstrained, overground walking. We hypothesized that the peak hip extension angle outcome of our device would be comparable to peak hip extension angle measured from a common motion capture system. In addition, we hypothesized that individuals post-stroke would increase their hip extension angle after a single walking bout with visual biofeedback of their hip extension angle.

METHODS

Fourteen individuals with chronic stroke walked for one six-minute walking bout with the visual biofeedback device. Before (pre-training) and after (post-training) the feedback walking bout, participants walked in a straight line at their self-selected speed for at least five steps per foot.

FINDINGS

Our device was reliable in measuring peak hip extension angle when compared to 3D motion capture equipment (R2 = 0.99). Individuals increased their hip extension angle after one session with the visual biofeedback (+2.886 ± 2.189 deg) compared to a control walking bout (+1.550 ± 1.629 deg) (Z = -2.103, p = 0.035).

INTERPRETATION

Our novel and inexpensive biofeedback method may provide benefit for individuals post-stroke and expand the possibilities for feedback in rehabilitation.

Designing Ecological Auditory Feedback on Lower Limb Kinematics for Hemiparetic Gait Training

Auditory feedback has earlier been explored as a tool to enhance patient awareness of gait kinematics during rehabilitation. In this study, we devised and tested a novel set of concurrent feedback paradigms on swing phase kinematics in hemiparetic gait training. We adopted a user-centered design approach, where kinematic data recorded from 15 hemiparetic patients was used to design three feedback algorithms (wading sounds, abstract, musical) based on filtered gyroscopic data from four inexpensive wireless inertial units. The algorithms were tested (hands-on) by a focus group of five physiotherapists. They recommended that the abstract and musical algorithms be discarded due to sound quality and informational ambiguity. After modifying the wading algorithm (as per their feedback), we conducted a feasibility test involving nine hemiparetic patients and seven physiotherapists, where variants of the algorithm were applied to a conventional overground training session. Most patients found the feedback meaningful, enjoyable to use, natural-sounding, and tolerable for the typical training duration. Three patients exhibited immediate improvements in gait quality when the feedback was applied. However, minor gait asymmetries were found to be difficult to perceive in the feedback, and there was variability in receptiveness and motor change among the patients. We believe that our findings can advance current research in inertial sensor-based auditory feedback for motor learning enhancement during neurorehabilitation.

A Clinical Perspective on Bespoke Sensing Mechanisms for Remote Monitoring and Rehabilitation of Neurological Diseases: Scoping Review

Neurological diseases including stroke and neurodegenerative disorders cause a hefty burden on the healthcare system. Survivors experience significant impairment in mobility and daily activities, which requires extensive rehabilitative interventions to assist them to regain lost skills and restore independence. The advent of remote rehabilitation architecture and enabling technology mandates the elaboration of sensing mechanisms tailored to individual clinical needs. This study aims to review current trends in the application of sensing mechanisms in remote monitoring and rehabilitation in neurological diseases, and to provide clinical insights to develop bespoke sensing mechanisms. A systematic search was performed using the PubMED database to identify 16 papers published for the period between 2018 to 2022. Teleceptive sensors (56%) were utilized more often than wearable proximate sensors (50%). The most commonly used modality was infrared (38%) and acceleration force (38%), followed by RGB color, EMG, light and temperature, and radio signal. The strategy adopted to improve the sensing mechanism included a multimodal sensor, the application of multiple sensors, sensor fusion, and machine learning. Most of the stroke studies utilized biofeedback control systems (78%) while the majority of studies for neurodegenerative disorders used sensors for remote monitoring (57%). Functional assessment tools that the sensing mechanism may emulate to produce clinically valid information were proposed and factors affecting user adoption were described. Lastly, the limitations and directions for further development were discussed.

Effect of Treadmill Training with Visual Biofeedback on Selected Gait Parameters in Subacute Hemiparetic Stroke Patients

BACKGROUND

Functional limitations after a stroke are unique to each person and often include impaired independent mobility. A reduction in existing gait deficits after a stroke is often one of the main goals of rehabilitation. Gait re-education after stroke is a complex process, which consists of the effects of many therapeutic interventions.

OBJECTIVE

The study aimed to analyze the effects of using a treadmill with visual feedback in gait re-education in the sub-acute stroke period and assess the impact of biofeedback treadmill training on selected gait parameters, improving static balance and reducing the need for orthopedic aids.

METHODS

The study included 92 patients (F: 45, M: 47) aged 63 ± 12 years, with post-ischemic sub-acute (within six months onset) stroke hemiparesis, treated at a neurological rehabilitation ward. All patients participated in a specific rehabilitation program, and in addition, patients in the study group (n = 62) have a further 10 min of treadmill training with visual feedback. Patients in the control group (n = 30) participated in additional conventional gait training under the direct supervision of a physiotherapist. The evaluation of static balance was assessed with the Romberg Test. A Biodex Gait Trainer 3 treadmill with biofeedback function was used to evaluate selected gait parameters (walking speed, step length, % limb loading, and traveled distance). The use of an orthopedic aid (walker or a crutch) was noted.

RESULTS

After four weeks of rehabilitation, step length, walking speed, traveled distance, and static balance were significantly improved for the study and control group (p < 0.05). Treadmill gait training yielded significantly better results than a conventional rehabilitation program. Only the study group observed a corrected walking base (p < 0.001). All participants showed a reduction in the use of walking aids (p = 0.006). There was no asymmetry in the % of limb loading for either group prior to or following rehabilitation.

CONCLUSIONS

The treadmill with visual biofeedback as conventional gait training has resulted in a significant improvement in parameters such as step length, walking speed, static balance, and a reduction in the use of locomotion aids. However, the achieved improvement in gait parameters is still not in line with the physiological norm.

Walk the Talk: Current Evidence for Walking Recovery After Stroke, Future Pathways and a Mission for Research and Clinical Practice

Achieving safe, independent, and efficient walking is a top priority for stroke survivors to enable quality of life and future health. This narrative review explores the state of the science in walking recovery after stroke and potential for development. The importance of targeting walking capacity and performance is explored in relation to individual stroke survivor gait recovery, applying a common language, measurement, classification, prediction, current and future intervention development, and health care delivery. Findings are summarized in a model of current and future stroke walking recovery research and a mission statement is set for researchers and clinicians to drive the field forward to improve the lives of stroke survivors and their carers.

Robotic Biofeedback for Post-Stroke Gait Rehabilitation: A Scoping Review

This review aims to recommend directions for future research on robotic biofeedback towards prompt post-stroke gait rehabilitation by investigating the technical and clinical specifications of biofeedback systems (BSs), including the complementary use with assistive devices and/or physiotherapist-oriented cues. A literature search was conducted from January 2019 to September 2022 on Cochrane, Embase, PubMed, PEDro, Scopus, and Web of Science databases. Data regarding technical (sensors, biofeedback parameters, actuators, control strategies, assistive devices, physiotherapist-oriented cues) and clinical (participants' characteristics, protocols, outcome measures, BSs' effects) specifications of BSs were extracted from the relevant studies. A total of 31 studies were reviewed, which included 660 stroke survivors. Most studies reported visual biofeedback driven according to the comparison between real-time kinetic or spatiotemporal data from wearable sensors and a threshold. Most studies achieved statistically significant improvements on sensor-based and clinical outcomes between at least two evaluation time points. Future research should study the effectiveness of using multiple wearable sensors and actuators to provide personalized biofeedback to users with multiple sensorimotor deficits. There is space to explore BSs complementing different assistive devices and physiotherapist-oriented cues according to their needs. There is a lack of randomized-controlled studies to explore post-stroke stage, mental and sensory effects of BSs.

Targeting CNS Neural Mechanisms of Gait in Stroke Neurorehabilitation

The central nervous system (CNS) control of human gait is complex, including descending cortical control, affective ascending neural pathways, interhemispheric communication, whole brain networks of functional connectivity, and neural interactions between the brain and spinal cord. Many important studies were conducted in the past, which administered gait training using externally targeted methods such as treadmill, weight support, over-ground gait coordination training, functional electrical stimulation, bracing, and walking aids. Though the phenomenon of CNS activity-dependent plasticity has served as a basis for more recently developed gait training methods, neurorehabilitation gait training has yet to be precisely focused and quantified according to the CNS source of gait control. Therefore, we offer the following hypotheses to the field: Hypothesis 1. Gait neurorehabilitation after stroke will move forward in important ways if research studies include brain structural and functional characteristics as measures of response to treatment. Hypothesis 2. Individuals with persistent gait dyscoordination after stroke will achieve greater recovery in response to interventions that incorporate the current and emerging knowledge of CNS function by directly engaging CNS plasticity and pairing it with peripherally directed, plasticity-based motor learning interventions. These hypotheses are justified by the increase in the study of neural control of motor function, with emerging research beginning to elucidate neural factors that drive recovery. Some are developing new measures of brain function. A number of groups have developed and are sharing sophisticated, curated databases containing brain images and brain signal data, as well as other types of measures and signal processing methods for data analysis. It will be to the great advantage of stroke survivors if the results of the current state-of-the-art and emerging neural function research can be applied to the development of new gait training interventions.

After 55 Years of Neurorehabilitation, What Is the Plan?

Neurological disorders often cause severe long-term disabilities with substantial activity limitations and participation restrictions such as community integration, family functioning, employment, social interaction and participation. Increasing understanding of brain functioning has opened new perspectives for more integrative interventions, boosting the intrinsic central nervous system neuroplastic capabilities in order to achieve efficient behavioral restitution. Neurorehabilitation must take into account the many aspects of the individual through a comprehensive analysis of actual and potential cognitive, behavioral, emotional and physical skills, while increasing awareness and understanding of the new self of the person being dealt with. The exclusive adoption by the rehabilitator of objective functional measures often overlooks the values and goals of the disabled person. Indeed, each individual has their own rhythm, unique life history and personality construct. In this challenging context, it is essential to deepen the assessment through subjective measures, which more adequately reflect the patient’s perspective in order to shape genuinely tailored instead of standardized neurorehabilitation approaches. In this overly complex panorama, where confounding and prognostic factors also strongly influence potential functional recovery, the healthcare community needs to rethink neurorehabilitation formats.

Evidence for efficacy of commercially available wearable biofeedback gait devices: a consumer-centered review (Preprint)

BACKGROUND

The number of wearable technological devices or sensors that are commercially available for gait training is increasing. These devices can fill a gap by extending therapy outside the clinical setting. This was shown to be important during the COVID-19 pandemic when people could not access one-on-one treatment. These devices vary widely in terms of mechanisms of therapeutic effect, as well as targeted gait parameters, availability, and strength of the evidence supporting the claims.

OBJECTIVE

This study aimed to create an inventory of devices targeting improvement in gait pattern and walking behavior and identify the strength of the evidence underlying the claims of effectiveness for devices that are commercially available to the public.

METHODS

As there is no systematic or reproducible way to identify gait training technologies available to the public, we used a pragmatic, iterative approach using both the gray and published literature. Four approaches were used: simple words, including some suggested by laypersons; devices endorsed by condition-specific organizations or charities; impairment-specific search terms; and systematic reviews. A findable list of technological devices targeting walking was extracted separately by 3 authors. For each device identified, the evidence for efficacy was extracted from material displayed on the websites, and full-text articles were obtained from the scientific databases PubMed, Ovid MEDLINE, Scopus, or Google Scholar. Additional information on the target population, mechanism of feedback, evidence for efficacy or effectiveness, and commercial availability was obtained from the published material or websites. A level of evidence was assigned to each study involving the device using the Oxford Centre for Evidence-Based Medicine classification. We also proposed reporting guidelines for the clinical appraisal of devices targeting movement and mobility.

RESULTS

The search strategy for this consumer-centered review yielded 17 biofeedback devices that claim to target gait quality improvement through various sensory feedback mechanisms. Of these 17 devices, 11 (65%) are commercially available, and 6 (35%) are at various stages of research and development. Of the 11 commercially available devices, 4 (36%) had findable evidence for efficacy potential supporting the claims. Most of these devices were targeted to people living with Parkinson disease. The reporting of key information about the devices was inconsistent; in addition, there was no summary of research findings in layperson's language.

CONCLUSIONS

The amount of information that is currently available to the general public to help them make an informed choice is insufficient, and, at times, the information presented is misleading. The evidence supporting the effectiveness does not cover all aspects of technology uptake. Commercially available technologies help to provide continuity of therapy outside the clinical setting, but there is a need to demonstrate effectiveness to support claims made by the technologies.

Biomechanical Correlates of Falls Risk in Gait Impaired Stroke Survivors

Increased falls risk is prevalent among stroke survivors with gait impairments. Tripping is the leading cause of falls and it is highly associated with mid-swing Minimum Foot Clearance (MFC), when the foot’s vertical margin from the walking surface is minimal. The current study investigated MFC characteristics of post-stroke individuals (n = 40) and healthy senior controls (n = 21) during preferred speed treadmill walking, using an Optotrak 3D motion capture system to record foot-ground clearance. In addition to MFC, bi-lateral spatio-temporal gait parameters, including step length, step width and double support time, were obtained for the post-stroke group’s Unaffected and Affected limb and the control group’s Dominant and Non-dominant limbs. Statistical analysis of MFC included central tendency (mean, median), step-to-step variability (standard deviation and interquartile range) and distribution (skewness and kurtosis). In addition, the first percentile, that is the lowest 1% of MFC values (MFC 1%) were computed to identify very high-risk foot trajectory control. Spatio-temporal parameters were described using the mean and standard deviation with a 2 × 2 (Group × Limb) Multivariate Analysis of Variance applied to determine significant Group and Limb effects. Pearson’s correlations were used to reveal any interdependence between gait variables and MFC control. The main finding of the current research was that post-stroke group’s affected limb demonstrated lower MFC 1% with higher variability and lower kurtosis. Post-stroke gait was also characterised by shorter step length, larger step width and increased double support time. Gait retraining methods, such as using real-time biofeedback, would, therefore, be recommended for post-stroke individuals, allowing them to acquire optimum swing foot control and reduce their tripping risk by elevating the swing foot and improving step-to-step consistency in gait control.

Targeted walking training of patients in the early recovery period of cerebral stroke (preliminary research)

Background: Currently, training of the gait function for patients with cerebral stroke using the biofeedback technology is an independent, effective, and promising method. The most common training and exposure parameters are the gait speed, cycle length, and cadence. However, the application of basic and more complex types of selective training using wearable sensor technology is rare due to the technological complexity of their use for biofeedback. Aims: To study the possibility of using the biofeedback training technology with a targeted effect on one of the basic parameters characterizing the symmetry of walking, the duration of the support period, in patients in the early recovery period of cerebral stroke. Methods: We examined 12 patients who underwent a course of biofeedback training to harmonize the period of support during the early recovery period of hemispheric cerebral stroke in the middle cerebral artery basin. The biomechanics of voluntary walking was investigated before and after the training. The spatio-temporal parameters of walking, kinematics of movements in the hip, knee, and ankle joints, and the maximum EMG amplitudes of the main muscle groups responsible for walking were recorded. The classical clinical scales were also used. The biofeedback training on a treadmill consisted of 10 sessions; the duration of the support period was the training parameter. Results. As a result of the treatment, a significant improvement was noted according to the UpGo clinical scale and Hausers walking index. The differences in the trained support phase after the treatment are not significant and demonstrate positive changes. The kinematics of movements in the joints also demonstrates relatively small, but significant changes for the knee joint. For the hip joint, no dynamics in the parameters values is observed; the joint function does not change significantly, and the amplitude asymmetry remains unchanged. For the knee joint, the greatest dynamics is observed for the main swing amplitude and its phase. Conclusion: The study has shown that the purposeful biofeedback training of the gait function using the support period to reduce the functional asymmetry in this parameter, and also has a positive effect on other gait parameters.

A Study of Biofeedback Gait Training in Cerebral Stroke Patients in the Early Recovery Phase with Stance Phase as Target Parameter

Walking function disorders are typical for patients after cerebral stroke. Biofeedback technology (BFB) is currently considered effective and promising for training walking function, including in patients after cerebral stroke. Most studies recognize that BFB training is a promising tool for improving walking function; however, the data on the use of highly selective walking parameters for BFB training are very limited. The aim of our study was to investigate the feasibility of using BFB training targeting one of the basic parameters of gait symmetry—stance phase duration—in cerebral stroke patients in the early recovery period. The study included 20 hemiparetic patients in the early recovery period after the first hemispheric ischemic stroke. The control group included 20 healthy subjects. The BFB training and biomechanical analysis of walking (before and after all BFB sessions) were done using an inertial system. The mean number of BFB sessions was nine (from 8 to 11) during the three weeks in clinic. There was not a single negative response to BFB training among the study patients, either during the sessions or later. The spatiotemporal parameters of walking showed the whole syndrome complex of slow walking and typical asymmetry of temporal walking parameters, and did not change significantly as a result of the study therapy. The changes were more significant for the functioning of hip and knee joints. The contralateral hip amplitude returned to the normal range. For the knee joint, the amplitude of the first flexion increased and the value of the amplitude of hyperextension decreased in the middle of the stance phase. Concerning muscle function, the observed significant decrease in the function of m. Gastrocnemius and the hamstring muscles on the paretic side remained without change at the end of the treatment course. We obtained positive dynamics of the biomechanical parameters of walking in patients after the BFB training course. The feasibility and efficacy of their use for targeted correction need further research.

Repurposing an EMG Biofeedback Device for Gait Rehabilitation: Development, Validity and Reliability

Gait impairment often limits physical activity and negatively impacts quality of life. EMG-Biofeedback (EMG-BFB), one of the more effective interventions for improving gait impairment, has been limited to laboratory use due to system costs and technical requirements, and has therefore not been tested on a larger scale. In our research, we aimed to develop and validate a cost-effective, commercially available EMG-BFB device for home- and community-based use. We began by repurposing mTrigger® (mTrigger LLC, Newark, DE, USA), a cost-effective, portable EMG-BFB device, for gait application. This included developing features in the cellphone app such as step feedback, success rate, muscle activity calibration, and cloud integration. Next, we tested the validity and reliability of the mTrigger device in healthy adults by comparing it to a laboratory-grade EMG system. While wearing both devices, 32 adults walked overground and on a treadmill at four speeds (0.3, 0.6, 0.9, and 1.2 m/s). Statistical analysis revealed good to excellent test-retest reliability (r > 0.89) and good to excellent agreement in the detection of steps (ICC > 0.85) at all speeds between two systems for treadmill walking. Our results indicated that mTrigger compared favorably to a laboratory-grade EMG system in the ability to assess muscular activity and to provide biofeedback during walking in healthy adults.