Postural control and gait quality in individuals in the chronic phase of stroke undergoing mobile robotic-assisted training: a pilot randomized clinical trial

 Since this didn't work, ask your competent? doctor WHAT EXACT PROTOCOLS WILL RECOVER YOUR GAIT AND PROVIDE POSTURAL CONTROL! Oh darn, HAS NOTHING; So completely fucking incompetent!

And your board of directors is so incompetent they can't recognize incompetence in their hospital!

Postural control and gait quality in individuals in the chronic phase of stroke undergoing mobile robotic-assisted training: a pilot randomized clinical trial

Kamila Niewolak

¹

,

 

Joanna Antkiewicz

¹

,

 

Laura Jadwiga Piejko

^{2, 3}

,

 

Julia Duda

³

,

 

Bogna Szołtys-Brzezowska

^{3, 4}

,

 

Agnieszka Nawrat-Szołtysik

^{4, 5}

,

 

Cezary Kucio

^{4, 5}

,

 

Anna Polak

^{3, 4}

1. Medical and Rehabilitation Center, “Solanki”, Poland
2. Clinical Department of Physiotherapy in Psychiatry, Faculty of Physical Therapy, Academy of Physical Education in Katowice, Katowice, Poland
3. Department of Clinical Physiotherapy, Academy of Physical Education in Katowice, Institute of Physiotherapy and Health Sciences, Katowice, Poland
4. Institute of Physiotherapy and Health Sciences, Academy of Physical Education in Katowice, Katowice, Poland
5. Department of Physiotherapy in Internal Diseases, Academy of Physical Education in Katowice, Katowice

Research, Physiotherapy Review, 2026, 30(1), 62-81

DOI: https://doi.org/10.5114/phr.2026.160363

Online publish date: 2026/03/26

Article file

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Abstract 

Background: 

Stroke is the second leading cause of death world wide, after ischemic heart disease. The consequences of stroke can be reduced through systematic rehabilitation of patients, including various types of therapeutic exercises that mitigate neurological deficits and stimulate brain plasticity. Among the most common consequences of stroke are disturbances in body balance and gait. In stroke patients, rehabilitation robots may contribute to improvements in motor function, increased muscle strength, and enhanced gait quality. There is therefore a need for further research to determine which rehabilitation robots are most effective at different stages after stroke and for various types of motor deficits. Aims: The aim of this pilot study was to obtain preliminary evidence on whether and how exercises performed using a mobile rehabilitation robot improve body balance and gait quality in individuals in the chronic phase after stroke. 

Material and methods: 

The study included chronic post-stroke patients (n = 23) randomly divided into two groups. In the experimental group (EG), participants performed gait exercises using a mobile rehabilitation robot for 20–40 minutes once daily, 6 days per week, for 3 weeks (a total of 18 training sessions). In the control group (CG), participants performed traditional ground-based gait exercises for 10–20 minutes once daily, 6 days per week, for 3 weeks. Patients in both groups also underwent conventional post-stroke rehabilitation for 2.5 hours per day, 6 days per week, based on best clinical practice principles. 

Results: 

Eighteen training sessions performed either on a mobile robot in the EG or as ground based gait training in the CG did not significantly improve patients’ body balance or gait quality in the chronic phase after stroke. 

Conclusions: 

There is no basis to conclude that ground-based gait training has a statistically significantly greater effect on body balance than training using a mobile robot in individuals in the chronic phase after stroke. Further studies are needed to provide a clear answer as to whether and to what extent mobile robot training can im prove body balance and gait quality in individuals in the chronic phase after stroke. Future clinical trials should consider implementing training protocols consisting of more than 18 sessions

Therapeutic and orthotic effects of an adaptive functional electrical stimulation system on gait biomechanics in participants with stroke

 

But this isn't addressing the wrong signals causing spasticity which I consider the major failure of all eStim techniques.

The proper research on this would be a way to stop the signals causing spasticity instead of this stupid; 'Hey, let's try to overcome the spasticity, which doesn't get you recovered at all!' 'Does anyone in stroke have any brains at all?'

Therapeutic and orthotic effects of an adaptive functional electrical stimulation system on gait biomechanics in participants with stroke

• Ruxin He,
• Yiqun Dong,
• You Li,
• Manxu Zheng,
• Shenghui Peng,
• Raymond Kai-Yu Tong &
• Rong Song 

Journal of NeuroEngineering and Rehabilitation volume 22, Article number: 62 (2025) Cite this article

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Abstract

Background:

In recent years, functional electrical stimulation (FES) has become a common intervention for stroke survivors to correct foot drop and improve gait biomechanics. While the orthotic effects of adaptive FES systems were well-documented, the center of pressure (COP) symmetry has been largely neglected. Furthermore, the long-term therapeutic effects of adaptive FES systems on gait biomechanics have received less attention.

Methods 

This study applied a timing- and intensity-adaptive functional electrical stimulation system for evaluation and training tests to address these limitations. In the evaluation test, eight participants with chronic stroke walked under three FES conditions: no stimulation (NS), adaptive FES to the tibialis anterior (SA-ILC SCS), and hybrid adaptive FES to the tibialis anterior and the gastrocnemius (SA-ILC DCS). Nine healthy subjects walked under the NS condition as the control group. In the training test, two participants with stroke took part in a 21-day training session under the SA-ILC DCS condition.

Results:

The results showed that the COP symmetry of participants with stroke in the SA-ILC SCS condition tended to improve compared to the NS condition, while the SA-ILC DCS condition showed significant improvement, approaching that of healthy subjects. After the 21-day treatment period, there was a tendency for improvement in the knee-ankle angle, anterior ground reaction force, and COP symmetry of both participants with stroke without assistance.

Conclusion:

The observed improvements can be attributed to the hybrid adaptive FES targeting the tibialis anterior and gastrocnemius muscles. This study demonstrates that the adaptive FES system offers promising walking assistance capabilities and significant clinical therapeutic potential.

Trial registration

Ethics Committee of Zhujiang Hospital, Southern Medical University, 2022-KY-149-01. Registered 29 September 2022.

Background

Stroke is an acute cerebrovascular disease with a high mortality and disability rate, which poses a severe threat to human life and health [1]. Hemiplegic gait is a common sequela characterized by weakness or spasticity in the affected limb and a loss of muscle control [2]. At the ankle level, the most common manifestations of the injury are lack of foot clearance during the swing and reduced forward propulsion during late stance [3]. Furthermore, the damage to the ankle muscles can result in compensatory actions involving other parts of the body [4]. For instance, individuals may lean on the unaffected limb to maintain balance and facilitate forward movement [5]. These disturbances can decrease walking speed and stability, induce asymmetric gait, and elevate the risk of falls [6, 7]. Consequently, identifying appropriate intervention methods to correct and treat hemiplegic gait is vital.

Functional Electrical Stimulation (FES) is a common intervention technique to correct hemiplegic gait, which transmits control signals from external devices to the neuromuscular system to activate muscles [8]. In 1961, Liberson et al. first applied FES to increase dorsiflexion angle during the swing phase in participants with stroke [9]. Since then, numerous FES systems have been developed to assist participants with stroke by correcting foot drop [10], enhancing push-off at the terminal stance phase [11], and improving knee [12] or hip control [13]. To address the highly nonlinear and time-varying nature of the stimulated muscle, researchers have developed several closed-loop control strategies, including finite state machines [14], artificial neural networks [15], fuzzy logic [16], and Iterative Learning Control (ILC) [10]. Among these, ILC has gained widespread application due to its ability to improve system performance through repeated trials by learning from previous iterations [17]. In ILC, control inputs are updated based on the error between the actual output and the desired output from the previous iteration, enabling the system to progressively reduce errors with each cycle. Building on this iterative learning process, ILC offers fast convergence, stable tracking performance, and robustness to external disturbances, making it particularly effective for optimizing neuromuscular control. However, most of these studies concentrate on the immediate orthotic effects of FES, neglecting the neuromuscular system’s capacity for enduring adaptation. Long-term use of FES can result in physiological changes, which may also affect motor performance in the absence of FES usage, and this carry-over effect is frequently termed the therapeutic effect [18]. Some studies recruited groups of participants with chronic stroke for more than four weeks of FES training, consistently observing improvements in gait performance [19,20,21]. FES has also been found to be an effective alternative to ankle foot orthosis for treating foot drop after stroke in other studies [22, 23]. Nonetheless, these studies often used basic open-loop FES systems with preset and fixed stimulus parameters, including pulse frequency, width, and current amplitude. These parameters cannot be dynamically adjusted to accommodate the physiological changes in participants with stroke after daily training, thus hindering the attainment of the optimal therapeutic effect. This makes the exploration of long-term training under closed-loop FES a worthwhile endeavor.

The effectiveness of FES systems in a clinical context can be assessed by analyzing various gait parameters. Regarding orthotic effects, researchers found that FES helped increase walking speed [24], reduce energy expenditure [25], increase knee-ankle angle [26], and change spatiotemporal characteristics [27]. In terms of therapeutic effects, many studies have demonstrated the effectiveness of FES in improving gait speed [20, 28]. FES also exhibited a positive therapeutic effect on additional activity-related parameters, including walking independence [19], walking distance [22], physiological cost index [20], and other variables. In addition to the above gait functions, after six weeks of FES training, Kesar et al. [21] found an improvement in gait biomechanics, including paretic propulsion and swing phase knee flexion. However, most of these studies focused on rehabilitating the affected limb to match the capabilities of non-disabled individuals, overlooking gait asymmetry caused by limb compensation. Center of pressure (COP) represents the cumulative neuromuscular response that controls the movement of the center of mass and is often utilized to evaluate balance control, gait deficits, and orthotic effect [29,30,31]. During the stance phase, the anteroposterior (AP) COP trajectory provides specific information that governs the forward progression of the center of mass. The medial-lateral (ML) COP movement mainly reflects the control process for regulating lateral stability during the single stance phase and the ability to shift weight between limbs during the double stance phase [29]. Nolan et al. [31] and Francis et al. [32] found that stimulating muscles like the tibialis anterior (TA) and gastrocnemius (GAS) could promote the anteroposterior movement of the center of pressure. Bamber et al. observed that stimulation of the peroneus longus muscle improved the lateral center of pressure during the stance phase [33]. Although applying functional electrical stimulation to ankle joint muscles can improve the center of pressure in previous studies, few of them considered the changes in symmetry after FES intervention.

In the previous research, we developed a hybrid adaptive functional electrical stimulation system [11]. Building upon this foundation, this study conducted extended evaluations. The orthotic effect of FES on COP symmetry, which is important for maintaining balance control while walking, was examined. Moreover, the therapeutic effect of the adaptive FES was studied by assessing improvements in gait biomechanics. We hypothesize that activating specific muscles in participants with stroke can facilitate the movement of the center of pressure on the hemiplegic side, improving gait symmetry. Furthermore, prolonged FES training might induce muscle strength and nerve excitability alterations, ultimately achieving therapeutic benefits.

Immediate improvements in post-stroke gait biomechanics are induced with both real-time limb position and propulsive force biofeedback

I see nothing here that suggests they are solving the spasticity problem in walking.

Since 30% of survivors that have spasticity, they are screwed in walking recovery.

 Right now I have zero propulsion, the whole leg is swung from the hip

Immediate improvements in post-stroke gait biomechanics are induced with both real-time limb position and propulsive force biofeedback

• Vincent Santucci,
• Zahin Alam,
• Justin Liu,
• Jacob Spencer,
• Alec Faust,
• Aijalon Cobb,
• Joshua Konantz,
• Steven Eicholtz,
• Steven Wolf &
• Trisha M. Kesar 

Journal of NeuroEngineering and Rehabilitation volume 20, Article number: 37 (2023) Cite this article

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Abstract

Background

Paretic propulsion [measured as anteriorly-directed ground reaction forces (AGRF)] and trailing limb angle (TLA) show robust inter-relationships, and represent two key modifiable post-stroke gait variables that have biomechanical and clinical relevance. Our recent work demonstrated that real-time biofeedback is a feasible paradigm for modulating AGRF and TLA in able-bodied participants. However, the effects of TLA biofeedback on gait biomechanics of post-stroke individuals are poorly understood. Thus, our objective was to investigate the effects of unilateral, real-time, audiovisual TLA versus AGRF biofeedback on gait biomechanics in post-stroke individuals.

Methods

Nine post-stroke individuals (6 males, age 63 ± 9.8 years, 44.9 months post-stroke) participated in a single session of gait analysis comprised of three types of walking trials: no biofeedback, AGRF biofeedback, and TLA biofeedback. Biofeedback unilaterally targeted deficits on the paretic limb. Dependent variables included peak AGRF, TLA, and ankle plantarflexor moment. One-way repeated measures ANOVA with Bonferroni-corrected post-hoc comparisons were conducted to detect the effect of biofeedback on gait biomechanics variables.

Results

Compared to no-biofeedback, both AGRF and TLA biofeedback induced unilateral increases in paretic AGRF. TLA biofeedback induced significantly larger increases in paretic TLA than AGRF biofeedback. AGRF biofeedback increased ankle moment, and both feedback conditions increased non-paretic step length. Both types of biofeedback specifically targeted the paretic limb without inducing changes in the non-paretic limb.

Conclusions

By showing comparable increases in paretic limb gait biomechanics in response to both TLA and AGRF biofeedback, our novel findings provide the rationale and feasibility of paretic TLA as a gait biofeedback target for post-stroke individuals. Additionally, our results provide preliminary insights into divergent biomechanical mechanisms underlying improvements in post-stroke gait induced by these two biofeedback targets. We lay the groundwork for future investigations incorporating greater dosages and longer-term therapeutic effects of TLA biofeedback as a stroke gait rehabilitation strategy.

Trial registration NCT03466372

Introduction

Hemiparesis following stroke causes unilateral deficits in gait kinematics and kinetics, contributing to slowed gait speed, gait asymmetries, and increased fall risk [1,2,3]. While increasing gait speed is a major goal of stroke rehabilitation [4, 5], improvements in speed can be achieved either through restoration of paretic limb function or compensatory strategies [6]. Measurement of kinematic and kinetic gait biomechanics variables can parse out restoration versus compensation as sources of gait recovery or training-induced improvements [7]. Reduced paretic propulsion, measured as the anterior component of the ground reaction force (AGRF) generated during late stance, is an important biomechanical deficit closely associated with gait speed and walking function post-stroke [8,9,10,11]. Importantly, individuals post-stroke demonstrate a paretic propulsive reserve [12] that can be exploited using gait training interventions [13, 14], with improvements in propulsion correlating to improvements in gait speed [8]. Thus, propulsion has emerged as a key modifiable post-stroke gait variable that is biomechanically and clinically relevant.

Previous studies have demonstrated two major biomechanical gait variables that contribute to overall propulsion, ankle plantarflexor moment, and trailing limb angle [15]. Ankle plantarflexors generate most of the force required to facilitate a smooth stance-to-swing transition [16]. Trailing limb angle (TLA), a measure of the overall limb angle or position with respect to the center of mass, places the leg in a better orientation to direct ground reaction forces more anteriorly [17]. Individuals post-stroke demonstrate deficits in both paretic plantarflexor moment and TLA [15], yet increases in paretic propulsion appear to originate mainly from improvements in paretic TLA [12, 18]. Post-stroke AGRF and TLA show robust inter-relationships, indicating that TLA can be used as a surrogate for paretic AGRF measurements [19]. Taken together, these studies suggest that targeting post-stroke TLA deficits may be a feasible and effective way of improving paretic propulsion.

Real-time biofeedback has emerged as a promising post-stroke gait training strategy that can target specific gait deficits on the paretic limb [20,21,22,23]. Previously, unilateral biofeedback targeting paretic propulsion was shown to induce significant increases in paretic limb propulsion without concomitant compensatory changes in the non-paretic limb [20]. However, translation of propulsion biofeedback from laboratory to clinic remains difficult because laboratory-based instrumented walkways or treadmills needed to measure AGRF may not be clinically accessible. The use of portable and wearable AGRF sensors for gait assessment is under study and not yet clinically available [24]. Moreover, estimation of propulsion through observational gait analysis is challenging even for movement experts with considerable clinical experience [25]. In contrast, measurements of TLA do not require the use of force platforms, and can be more easily subjectively estimated by clinicians based on the relationship of the forefoot to the pelvis or greater trochanter during observational gait analysis [19]. Recently, we demonstrated that able-bodied individuals are able to modulate TLA and AGRF unilaterally in response to real-time unilateral TLA biofeedback [26]. Thus, TLA biofeedback holds promise as a clinically applicable intervention that could preferentially increase paretic AGRF and reduce post-stroke propulsion deficits. While AGRF and TLA have been studied together as outcome variables in previous research, to our knowledge, biofeedback for these 2 biomechanical targets has not been directly compared in people post-stroke. Thus, an initial assessment of the feasibility and immediate biomechanical effects of TLA biofeedback on post-stroke individuals is needed.

Here, we studied the effects of TLA biofeedback on post-stroke gait biomechanics. Moreover, to assess its use as a suitable and clinically applicable alternative to AGRF biofeedback, we compared the immediate biomechanical effects of TLA biofeedback to AGRF biofeedback. We hypothesized that a biofeedback paradigm targeting paretic TLA would elicit favorable improvements in paretic propulsion and other post-stroke gait biomechanics impairments that are comparable in magnitude to AGRF biofeedback.

More at link.

5-Link model based gait trajectory adaption control strategies of the gait rehabilitation exoskeleton for post-stroke patients

 What does your doctor think of this? Does your doctor think of research at all?

5-Link model based gait trajectory adaption control strategies of the gait rehabilitation exoskeleton for post-stroke patients

Article history:

Received 2 August 2009Accepted 7 February 2010 

Zhang Jia-fan a,*, 

Dong Yi-ming a

Yang Can-jun a,

Geng Yu b, + 2 Chen Ying a,

Yang Yin a
a State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, Zhejiang 310027, China
b Sir Run Run Shaw Hospital, Affiliated with School of Medicine, Zhejiang University, Hangzhou 310027, China

abstract

Many 4-DOF exoskeleton type robot devices have been widely developed for the gait rehabilitation of post-stroke patients. However, most systems run with purely position control not allowing voluntary active movements of the subject. The lack of intelligent control strategies for variable gait patterns has been a clinical concern of such kind exoskeleton man–machine systems. In this work, we establish a 5-link model for the usual 4-DOF gait rehabilitation exoskeleton type man–machine system and propose  agait trajectory adaption control strategy. A 4 DOF gait rehabilitation exoskeleton prototype is developed as  a platform for the evaluation of design concepts and control strategies in the view of improved physical human–robot interaction. The experimental results with eight healthy volunteers and three stroke patients are encouraging.

Improved walking function in laboratory does not guarantee increased community walking in stroke survivors: Potential role of gait biomechanics

I couldn't understand a thing here, so useless for survivors. 

Improved walking function in laboratory does not guarantee increased community walking in stroke survivors: Potential role of gait biomechanics

 Journal of Biomechanics , Volume 91 , Pgs. 151-159.

NARIC Accession Number: J84187.  What's this?
ISSN: 0021-9290.
Author(s): Ardestani, Marzieh M. ; Henderson, Christopher E. ; Hornby, T. George.
Project Number: H133B031127, 90RT5027 (formerly H133B140012).
Publication Year: 2019.
Number of Pages: 9.

Abstract: 

Study investigated the relationships between clinical and biomechanical walking measures that may contribute to changes in daily stepping activity following physical interventions provided to participants with subacute stroke. The primary outcomes were short- and long-term changes in daily stepping activity, evaluated following up to 40 training sessions (POST) and at 2 to 6 months follow-up (F/U). Thirty-nine participants were categorized into three groups: (1) responders/retainers who increased daily stepping >500 steps per day at POST without decreases in stepping at F/U, (2) responders/non-retainers who increased stepping at POST but declined >500 steps per day at F/U, and (3) non-responders who did not change daily stepping from baseline testing (BSL). Gait kinematics and kinetics were evaluated during graded treadmill assessments at BSL and POST. Clinical measures of gait speed, timed walking distance, balance, and balance confidence were measured at BSL, POST and F/U. Between-group comparisons and regression analyses were conducted to predict stepping activity from BSL and POST measurements. Baseline and changes in clinical measures of walking demonstrated selective associations with stepping, although kinematic measures appeared to better discriminate responders. Specific measures suggest greater paretic versus non-paretic kinematic changes in responders with training, although greater non-paretic changes predicted greater gains (i.e., smaller declines) in stepping in retainers at F/U. No kinetic variables were primary predictors of changes in stepping activity at POST or F/U. The combined findings indicate that specific biomechanical assessments may help differentiate changes in daily stepping activity post-stroke.
Descriptor Terms: AMBULATION, BIOENGINEERING, MEASUREMENTS, OUTCOMES, PHYSICAL THERAPY, STROKE.


Can this document be ordered through NARIC's document delivery service*?: Y.

Citation: Ardestani, Marzieh M. , Henderson, Christopher E. , Hornby, T. George. (2019). Improved walking function in laboratory does not guarantee increased community walking in stroke survivors: Potential role of gait biomechanics.  Journal of Biomechanics , 91, Pgs. 151-159. Retrieved 8/18/2020, from REHABDATA database.

Effects of virtual reality training on gait biomechanics of individuals post-stroke

Useless.  A  complete demonstration of the tyranny of low expectations, potential for recovery/evaluate.  No discussion of how many got fully recovered. I would fire the mentors and senior researchers that allowed such crapola research.

Effects of virtual reality training on gait biomechanics of individuals post-stroke

 Anat Mirelman
a,b,c,
*, Benjamin L. Patritti
c
, Paolo Bonato
c,d
, Judith E. Deutsch
b
a
Gait and Neurodynamics Laboratory, Tel Aviv Sourasky Medical Center, Israel
b
RiVERS Lab, Doctoral Program in Physical Therapy, Department of Rehabilitation and Movement Science, University of Medicine and Dentistry of New Jersey, United States
c
Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital, United States
d
The Harvard-MIT Division of Health Sciences and Technology, United States

ABSTRACT

Objective:
 To evaluate gait biomechanics after training with a virtual reality(VR) system and to elucidate underlying mechanisms that contributed to the observed functional improvement in gait speed and distance.
Design:
 A single blind randomized control study.
Setting:
 Gait analysis laboratory in a rehabilitation hospital and the community.
Participants:
 Fifteen men and three women with hemiparesis caused by stroke.
Interventions:
 Subjects trained on a six-degree of freedom force-feedback robot interfaced with a VR simulation.Subjects were randomized to either aVRgroup(n = 9)or non-VRgroup(NVR,n =9). Training was performed three times a week for 4 weeks for approximately 1 h each visit.
Main outcome measures:
 Kinematic and kinetic gait parameters.
Results:
 Subjects in the VR group demonstrated a significantly larger increase in ankle power generation at push-off as a result of training ( p = 0.036). The VR group had greater change in ankle ROM post-training(19.5%)as compared to the NVR group(3.3%). Significant differences were found in knee ROM on the affected side during stance and swing, with greater change in the VR group. No significant changes were observed in kinematics or kinetics of the hip post-training.
Conclusions:
 These findings are encouraging because they support the potential for recovery of force and power of the lower extremity for individuals with chronic hemiparesis. It is likely that the effects of training included improved motor control at the ankle, which enabled the cascade of changes that produced the functional improvements seen after training.

 2010 Elsevier B.V. All rights reserved.

Automatic identification of gait events using an instrumented sock

And maybe we could put estim in there also to prevent
inversion. 

Automatic identification of gait events using an instrumented sock

Abstract (provisional)
Background
Textile-based transducers are an emerging technology in
which piezo-resistive properties of materials are used to
measure an applied strain. By incorporating these sensors
into a sock, this technology offers the potential to detect
critical events during the stance phase of the gait cycle.
This could prove useful in several applications, such as
functional electrical stimulation (FES) systems to assist
gait.
Methods
We investigated the output of a knitted resistive strain
sensor during walking and sought to determine the degree of
similarity between the sensor output and the ankle angle in
the sagittal plane. In addition, we investigated whether it
would be possible to predict three key gait events, heel
strike, heel lift and toe off, with a relatively straight-
forward algorithm. This worked by predicting gait events to
occur at fixed time offsets from specific peaks in the
sensor signal.
Results
Our results showed that, for all subjects, the sensor output
exhibited the same general characteristics as the ankle
joint angle. However, there were large between-subjects
differences in the degree of similarity between the two
curves. Despite this variability, it was possible to
accurately predict gait events using a simple algorithm.
This algorithm displayed high levels of trial-to-trial
repeatability.
Conclusions
This study demonstrates the potential of using textile-based
transducers in future devices that provide active gait
assistance