Rehabilitation of motor impairments in patients after cerebral stroke in the early recovery period using a treadmill with biofeedback

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INTRODUCTION

One of the most challenging problems for a patient is the rehabilitation after a cerebral stroke. An acute cerebrovascular accident results in the death of some neurons, and some functions cease, including the motor function. As a result, the patients develop paresis or paralysis, increased muscle tone, sensitivity disorders, all complicating the restoration of movement after the stroke and making the rehabilitation process a lengthy one.

It is known from practice that every case of stroke is unique: it is a heterogeneous disease, and the patients demonstrate different models of rehabilitation. Therefore, it is vitally important to start the rehabilitation in time and to personalize the rehabilitation program considering the individual specifics of patients [1].

Post-stroke walking disorders have a negative effect on daily independence, quality of life, professional and social integration, and increase risk of falling in adults [2, 3]. The key to restoration of walking ability after the stroke is rehabilitation. Brain is stimulated by afferent stimuli when physical exercises are performed [4, 5], including therapeutic exercise to restore gait [9-6]. The degree of neurological deficit may be reduced both as a result of spontaneous natural restoration of the nervous system and as a result of training delivered by specialists focusing specifically on restoration of the ability to perform daily activities [7-10].

Patients surviving stroke may restore quality of their life by the phenomenon of neuroplasticity [11-14]. One of the tools of focused influence on the mechanisms of neuroplasticity is the method of biological feedback (biofeedback, BFB) that has strong positions in the modern neurorehabilitation [15]. The method is based on the principle of external objectification of physiological processes that normally occur at a subclinical level and remain unnoticed by the patient. Biofeedback provides the patient with real-time information about parameters of their motor activity and shifts automated neuromuscular processes into the realm of conscious control.

In the post-stroke motor rehabilitation, the key biological signal is the bioelectrical activity of the muscles registered by electromyography [16]. A closed loop of sensorimotor feedback is thus formed: attempt at movement → signal registration → result visualization → correction of the motor command. The patient receives immediate information on the quality and intensity of muscle contraction and may voluntarily increase the force of or to modify the movement. The process meets the principles of motor learning based on repetition, error correction and support of a successful action [17].

From a neurophysiological perspective, BFB training activates several interrelated mechanisms: enhancement of afferent flow from the working muscles; increased cortical excitability in sensorimotor areas; formation of new functional connections bypassing damaged regions; and stabilization of newly formed neural networks through repeated activation.

The regular comparison of motor intention with the objective outcome helps reduce pathological movement patterns and gradually restore the movement schema. Unlike passive intervention methods, biofeedback actively involves the patient in the self-regulation process, which is essential for achieving a sustained neuroplastic effect [18, 19].

The optimal frequency of training sessions is determined individually, however, regular exercises (2–3 times per week 30–40 minutes each or as parts of intensive rehabilitation programs) ensure accumulation effect achieved through repeated activation of sensorimotor loops [20].

The psychological component of the method is of no lesser importance. After the stroke, the patients often encounter the phenomenon of ‘motor uncertainty’, when the attempt at movement does not come with the expected result. The visualization of even minimal muscular activity forms the feeling of control and progression. From a passive object of therapy, the patient turns into an active participant of the rehabilitation process, which increases motivation and compliance with the treatment process [21].

Biofeedback gains even greater significance in the context of variability of post-stroke rehabilitation. The character of neurological deficit, extent of damage, manifestation of spasticity, availability of sensory disorders, age and concomitant disease form the unique individual patient profile. Customization of the program requires precise evaluation not only of the physical strength and range of movement, but also of the concealed disorders: proprioceptive deficit, coordination disorders, dissociation of muscular activity [22].

Early identification of such disorders allows for a timely inclusion of elements of neural stimulation in the rehabilitation program, as well as antispasmodic measures, balance training and correction of posture control. In this context, BFB serves not only as a training method but also as a functional diagnostic tool [23].

An important stage of therapy is the system calibration process. Based on the recorded signals, individual threshold values reflecting the patient's baseline functional level are established. Adjusting the sensitivity ranges ensures the adequacy of the feedback and prevents both excessive task complexity and insufficient stimulation. Maintaining the parameters across sessions allows for monitoring of dynamics and objective documentation of progress [24, 25].

Thus, biofeedback is an integrative method combining elements of neurophysiology, motor training and digital monitoring. It ensures transition from empiric training to a managed quantitatively controlled process of neuroplastic learning making it a perspective component of modern programs of post-stroke rehabilitation [26].

AIM

To evaluate the clinical effectiveness of integrating treadmill training with a biofeedback system into an early post-stroke rehabilitation program for managing motor disorders and improving functional outcomes.

MATERIAL AND METHODS

The study involved 60 patients. Inclusion criteria: history of cerebral ischemic stroke suffered in the past 6 months confirmed by neuroimaging data and medical documentation, focal neurological symptoms manifested by motor deficit (ataxia, paresis) with a possibility of unaided walking with a speed > 0.4 m/s, muscle tone of the paretic lower limb on the Ashworth scale ≤ 1 plus, disability level 3 on the Rankin scale, lack of dementia, availability of a voluntary informed consent to participate in the study. Non-inclusion criteria: impossibility of maintaining an upright posture, unstable hemodynamic condition, diseases of peripheric vessels, cognitive disorders with results below 20 on the Mini Mental Scale Examination and other motor disorders significantly impeding the walking capability, refusal from participation in the study. Exclusion criteria: withdrawal of the voluntary informed consent, premature termination of treatment course for any reason.

Using a software randomizer, the participants were randomly distributed into two groups, the experiment and the control group. In the course of the study, 30 patients underwent a rehabilitation course using a BFB treadmill (17 men, 13 women; median age: 66 ± 7.6 years). The other 30 patients were in the control group (19 men, 11 women; median age: 68 ± 6.9 years) and underwent rehabilitation programs without the BFB. In their clinical and demographic characteristics at the stage of inclusion in the study, the patients were comparable in sex, age, type of stroke, availability of a comorbid pathology (p > 0.05). All patients underwent rehabilitation in the day patient facility of the Department of medical rehabilitation of the Clinics of Bashkir State Medical University. The duration of the rehabilitation course was 14 days. The average time elapsed from the onset of the stroke was 43.8 days.

At the time of the study, all patients presented with ataxia (both dynamic and static) and central paresis of the leg as the predominant clinical syndrome. The rehabilitation process included individual therapeutic exercise sessions with a physical therapy instructor (30 minutes), mechanotherapy (exercise on a stationary bicycle, 10 minutes), and occupational therapy (30 minutes). In addition to these interventions, the experimental group underwent BFB-assisted treadmill gait rehabilitation (20 minutes daily).

Training sessions were performed on a BFB-assisted treadmill Walker View. Its principle of work is based on the integration of the mechanical platform (modified walking frame with strain gauges) and a software and hardware complex providing visualization and quantitative analysis of the motor action. The principle of action is based on continuous real-time monitoring of several biomechanical parameters, including distribution of vertical load on upper limbs, symmetry of support reaction, length and rhythm of the step, as well as general dynamics of locomotion. The obtained data was sent to the interface as self-explanatory graphics, i.e. digital indicators, load scales or interactive animated scenarios. As a result, the patient actively controlled the movements based on the visual analysis of current values. The key therapeutic advantage of the system in the correction of ataxic disorders is the formation of an afferent flow contributing to the restoration of the physiological pattern of walking. While trying to achieve target values on the screen (e.g. maintain the balance or walk the suggested trajectory), the patient involuntarily normalized the body weight distribution, reduces the asymmetry of load on the paretic and the normal limb and trains the elements of postural control. From a neurophysiological perspective, this technique potentiates neuroplasticity mechanisms by providing intensive, repetitive, and goal-directed practice, consistent with the principles of experience-dependent learning. The brain receives a clear task and immediate feedback on the quality of its performance, which stimulates the reorganization of functional maps in the sensorimotor cortex and the formation of new compensatory neural networks. Beyond the direct effects on motor function, this technology has a significant psychological impact, enhancing the motivational component of therapy through gamification of the rehabilitation process and by visualizing objective progress.

Statistical processing of data was performed with a confidence probability of 95%. The normality of the quantitative data distribution was assessed using the Shapiro–Wilk test; the distribution did not differ significantly from normal (p > 0.05). Descriptive statistics were expressed as the arithmetic mean and standard deviation. The significance of the treadmill training outcomes in each study group was evaluated by comparing the results of pre- and post-training assessments. Improvement was defined as the change between the pre- and post-training results. Given the demonstrated normality of the data distribution, Fisher-Student’s t-test was used to examine statistical differences between the two samples. The threshold significance level was set at α < 0.05. All data were analyzed using STATISTICA version 10.0 (StatSoft, Poland).

RESULTS

To evaluate the outcomes of the rehabilitation interventions, we used the following measures and clinical scales: the Timed Up and Go test, the 10-Meter Walk Test, the Berg Balance Scale, walking speed (km/h), and step cycle length (cm).

 

Parameter		Day 1 of rehabilitation	Day 14 of rehabilitation	p-value
Timed Up and Go test		21.55±6.48	17.23±6.05	< 0.001
10-Meter Walk test		20.27±5.31	15.55±4.23	< 0.001
Berg Balance Scale		26.45±9.94	33.70±8.72	< 0.001
Walking speed (km/h)		0.86±0.79	1.04±0.92	< 0.002
Step cycle length		0.51±0.63	0.72±0.71	< 0.001

Table 1. Mean values of indicators in patients over time during rehabilitation using a biofeedback track (n=30)

Таблица 1. Усредненные значения показателей у пациентов в динамике в процессе реабилитации с применением дорожки с БОС (n=30)

 

Parameter	Day 1 of rehabilitation	Day 14 of rehabilitation	p-value
Timed Up and Go test	22.06±6.91	18.14±5.76	< 0.001
10-Meter Walk test	21.78±4.84	16.73±4.72	< 0.001
Berg Balance Scale	26.15±8.76	30.11±9.28	< 0.001
Walking speed (km/h)	0.81±0.65	0.98±0.87	< 0.002
Step cycle length	0.55±0.69	0.70±0.82	< 0.001

Table 2. Mean values of indicators in patients over time during rehabilitation without a biofeedback track (n=30)

Таблица 2. Усредненные значения показателей у пациентов в динамике в процессе реабилитации без использования дорожки с БОС (n=30)

 

A comparative analysis of the dynamics of the parameters between the groups demonstrates a clear advantage of the biofeedback-based method. Although statistically significant improvement was observed in both groups, the experimental group showed more pronounced progress across all evaluated parameters. The percentage improvement (relative to baseline) on the key functional tests was as follows.

Timed Up and Go Test: In the experimental group, the time of test performance reduced by 20%, while in the control group, by 17.8%. The 10-Meter Walking test: the time required to complete the walk reduced by 23.3% in the experimental group vs. 23.1% in the control group. Berg Balance Scale: the results of the experimental group increased by 27.4%, whereas in the control group the improvement was 15.1%. Walking speed: the speed increase in the experimental group was 20.9% vs. 21.0% in the control group. The difference between the groups was insignificant (0.1%). Длина Step cycle length: the step length in the BFB group increased by 41.2% vs. increase of 27.3% in the control group.

Thus, it can be concluded that the integration of biofeedback with treadmill training leads to a more pronounced improvement in functional capabilities in terms of balance and gait symmetry, as confirmed by the quantitative advantage most clearly observed in the dynamics of the Berg Balance Scale and step cycle length.

DISCUSSION

The effect of training on the treadmill and use of BFB methods is confirmed by many tests involving patients after a cerebral stroke. The increase in walking speed and improvement in gait quality are achieved by extending the stance time on the paretic limb. The addition of external auditory and visual information regarding correct gait and its parameters, such as speed, step length, and symmetry of gait phases, during treadmill training enables the patient not only to improve gait symmetry but also to stimulate balance, coordination, strength, and endurance of the relevant muscle groups. Besides, patient motivation to perform the exercises is enhanced by visualizing task accuracy on the screen and through acoustic biofeedback. M. Rizzo et al. (2023) [27] demonstrated that improvement of motor functions may be achieved by various means of rehabilitation including mirror therapy with visual biofeedback. Х. Ма et al. (2025) [28] report that improvement of kinesthetic imagination are related to selective inhibition in the frontal-central-temporal areas of the brain and activation in the parietal-occipital areas, as well as with the information flow between the parietal-occipital and frontal-parietal areas of the brain, and these models may be used in the development of online educational resources for motor skills and technologies of virtual modeling. M.T.A.P. Dantas et al. (2023) [29] studied the effects of training on a treadmill and analyzed the effect of training on mobility and parameters of walking capability. It was demonstrated that the use of treadmill training was justified, especially with the effect of such training being augmented by supplementary procedures (e.g., functional electrostimulation).

In our group, in which biofeedback was applied, a greater increase in step cycle length on the healthy side and in the duration of the swing phase of the healthy lower limb was observed. The superior rehabilitation outcomes in the biofeedback group were also associated with improved symmetry of the stance phase duration.

Patients in both groups demonstrated a reduction in the swing phase of both the paretic and non-paretic limbs, accompanied by a prolongation of the stance phase. In the biofeedback group, the changes in the spatiotemporal parameters of the non-paretic limb were greater than those in the non-biofeedback group; however, the difference between the groups did not reach a high level of significance. In the biofeedback group, the effect of motor training was significantly higher than in the control group, but only in the healthy limb. The fact may be explained by the brevity of the program, which might restrict the capabilities of motor training after the stroke, especially in the field of motor control of the paretic limb. Improvement of other metrics in the group receiving BFB-enhanced rehabilitation was higher than in the group without the BFB, but it was not statistically significant, both in our study and in others [30].

CONCLUSION

The obtained results do not provide a definitive answer to the question of whether biofeedback-assisted treadmill rehabilitation is more effective for restoring walking function compared to treadmill training without biofeedback. Treadmill training contributed to the normalization of spatiotemporal gait parameters in both groups, primarily in the swing phase and step length reduction. An important clinical effect of the program was the significant increase in the speed and distance of walking, as well as improved independence in walking and improved self-reliance in both groups. Visual feedback used in the training of walking helped patients focus on the exercise by providing additional information, and real-time results motivated patients to continue training. The findings of this pilot study may serve as a basis for further investigation with an expanded sample size and, potentially, with the inclusion of data from modern neuroimaging studies that allow assessment of the morphological integrity of cerebral tracts [31], along with a longer treatment period and comparison of the obtained data with earlier publications [32] on the set of prognostic factors influencing clinical outcomes in post-stroke rehabilitation.

 

ADDITIONAL INFORMATION	ДОПОЛНИТЕЛЬНАЯ ИНФОРМАЦИЯ
Ethical approval. The study was conducted in accordance with the ethical standards of the Helsinki Declaration and approved by the Local Ethics Committee of Bashkir State Medical University (Protocol No. 10 dated 23.10.2024).	Этическая экспертиза. Исследование выполнено в соответствии с этическими стандартами Хельсинкской декларации и одобрено локальным этическим комитетом ФГБОУ ВО «Башкирский государственный медицинский университет» (протокол №10 от 23.10.2024).
Consent for publication. All study participants signed a written informed consent form.	Согласие на публикацию. Все участники исследования подписывали добровольное информированное согласие.
Study funding. The work was carried out using funds from the State Assignment of the Ministry of Health of the Russian Federation, registration number 124121800005-6.	Источник финансирования. Работа выполнена за счет средств государственного задания Минздрава России (регистрационный номер 124121800005-6).
Conflict of interest. The authors declare that there are no obvious or potential conflicts of interest associated with the content of this article.	Конфликт интересов. Авторы декларируют отсутствие явных и потенциальных конфликтов интересов, связанных с содержанием настоящей статьи.
Contribution of individual authors. Akhmadeeva L.R.: overall supervision, writing of the text, Goldyrev E.O.: conducting the training, data analysis, writing of the text. Bagautdinov K.F., Blinova N.M.: participation in data analysis and discussion of results, editing of the text editing, participation in discussion of results. All authors gave their final approval of the manuscript for submission, and agreed to be accountable for all aspects of the work, implying proper study and resolution of issues related to the accuracy or integrity of any part of the work.	Участие авторов. Ахмадеева Л.Р.: общее руководство, написание текста, Голдырев Е.О.: проведение тренинга, анализ данных, написание текста. Багаутдинов К.Ф., Блинова Н.М.: участие в анализе данных и обсуждении результатов, редактирование текста. Все авторы одобрили финальную версию статьи перед публикацией, выразили согласие нести ответственность за все аспекты работы, подразумевающую надлежащее изучение и решение вопросов, связанных с точностью или добросовестностью любой части работы.
Statement of originality. No previously published material (text, images, or data) was used in this work.	Оригинальность. При создании настоящей работы авторы не использовали ранее опубликованные сведения (текст, иллюстрации, данные).
Data availability statement. The editorial policy regarding data sharing does not apply to this work.	Доступ к данным. Редакционная политика в отношении совместного использования данных к настоящей работе не применима.
Generative AI. No generative artificial intelligence technologies were used to prepare this article.	Генеративный искусственный интеллект. При создании настоящей статьи технологии генеративного искусственного интеллекта не использовали.
Provenance and peer review. This paper was submitted unsolicited and reviewed following the standard procedure. The peer review process involved 2 external reviewers.	Рассмотрение и рецензирование. Настоящая работа подана в журнал в инициативном порядке и рассмотрена по обычной процедуре. В рецензировании участвовали 2 внешних рецензента.

 

About the authors

Leila R. Akhmadeeva

Bashkir State Medical University

Email: leila_ufa@mail.ru
ORCID iD: 0000-0002-1177-6424

MD, Dr. Sci. (Medicine), Professor of the Department of Neurology.

Russian Federation, Ufa

Evgenii O. Goldyrev

Bashkir State Medical University

Email: evgenyy86@gmail.com
ORCID iD: 0009-0003-5307-3123

MD, neurologist of the Clinic of the Bashkir State Medical University.

Russian Federation, Ufa

Kamil F. Bagautdinov

Bashkir State Medical University

Email: bagautdinov-k@mail.ru
ORCID iD: 0009-0009-7165-8073

MD, assistant of the Department of Adaptive physical culture and sports medicine.

Russian Federation, Ufa

Nataliya M. Blinova

Bashkir State Medical University

Author for correspondence.
Email: natalia_ufa@bk.ru
ORCID iD: 0000-0001-7385-3299

MD, Cand. Sci. (Medicine), Associate professor of the Department of Neurosugery and medical rehabilitation.

Russian Federation, Ufa

References

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