Real-time biofeedback device for gait rehabilitation of post-stroke patients

Artificial intelligence in stroke rehabilitation: From acute care to long-term recovery

Stroke is a leading cause of disability worldwide, driving the need for advanced rehabilitation strategies. The integration of Artificial Intelligence (AI) into stroke rehabilitation presents significant advancements across the continuum of care, from acute diagnosis to long-term recovery. This review explores AI's role in stroke rehabilitation, highlighting its impact on early diagnosis, motor recovery, and cognitive rehabilitation. AI-driven imaging techniques, such as deep learning applied to CT and MRI scans, improve early diagnosis and identify ischemic penumbra, enabling timely, personalized interventions. AI-assisted decision support systems optimize acute stroke treatment, including thrombolysis and endovascular therapy. In motor rehabilitation, AI-powered robotics and exoskeletons provide precise, adaptive assistance, while AI-augmented Virtual and Augmented Reality environments offer immersive, tailored recovery experiences. Brain-Computer Interfaces utilize AI for neurorehabilitation through neural signal processing, supporting motor recovery. Machine learning models predict functional recovery outcomes and dynamically adjust therapy intensities. Wearable technologies equipped with AI enable continuous monitoring and real-time feedback, facilitating home-based rehabilitation. AI-driven tele-rehabilitation platforms overcome geographic barriers by enabling remote assessment and intervention. The review also addresses the ethical, legal, and regulatory challenges associated with AI implementation, including data privacy and technical integration. Future research directions emphasize the transformative potential of AI in stroke rehabilitation, with case studies and clinical trials illustrating the practical benefits and efficacy of AI technologies in improving patient recovery.

Instant gait classification for hip osteoarthritis patients: a non-wearable sensor approach utilizing Pearson correlation, SMAPE, and GMM

This study aims to establish a methodology for classifying gait patterns in patients with hip osteoarthritis without the use of wearable sensors. Although patients with the same pathological condition may exhibit significantly different gait patterns, an accurate and efficient classification system is needed: one that reduces the effort and preparation time for both patients and clinicians, allowing gait analysis and classification without the need for cumbersome sensors like EMG or camera-based systems. The proposed methodology follows three key steps. First, ground reaction forces are measured in three directions-anterior-posterior, medial-lateral, and vertical-using a force plate during gait analysis. These force data are then evaluated through two approaches: trend similarity is assessed using the Pearson correlation coefficient, while scale similarity is measured with the Symmetric Mean Absolute Percentage Error (SMAPE), comparing results with healthy controls. Finally, Gaussian Mixture Models (GMM) are applied to cluster both healthy controls and patients, grouping the patients into distinct categories based on six quantified metrics derived from the correlation and SMAPE. Using the proposed methodology, 16 patients with hip osteoarthritis were successfully categorized into two distinct gait groups (Group 1 and Group 2). The gait patterns of these groups were further analyzed by comparing joint moments and angles in the lower limbs among healthy individuals and the classified patient groups. This study demonstrates that gait pattern classification can be reliably achieved using only force-plate data, offering a practical tool for personalized rehabilitation in hip osteoarthritis patients. By incorporating quantitative variables that capture both gait trends and scale, the methodology efficiently classifies patients with just 2-3 ms of natural walking. This minimizes the burden on patients while delivering a more accurate and realistic assessment. The proposed approach maintains a level of accuracy comparable to more complex methods, while being easier to implement and more accessible in clinical settings.

A scoping review on recent trends in wearable sensors to analyze gait in people with stroke: From sensor placement to validation against gold-standard equipment

The purpose of the review is to evaluate wearable sensor placement, their impact and validation of wearable sensors on analyzing gait, primarily the postural instability in people with stroke. Databases, namely PubMed, Cochrane, SpringerLink, and IEEE Xplore were searched to identify related articles published since January 2005. The authors have selected the articles by considering patient characteristics, intervention details, and outcome measurements by following the priorly set inclusion and exclusion criteria. From a total of 1077 articles, 142 were included in this study and classified into functional fields, namely postural stability (PS) assessments, physical activity monitoring (PA), gait pattern classification (GPC), and foot drop correction (FDC). The review covers the types of wearable sensors, their placement, and their performance in terms of reliability and validity. When employing a single wearable sensor, the pelvis and foot were the most used locations for detecting gait asymmetry and kinetic parameters, respectively. Multiple Inertial Measurement Units placed at different body parts were effectively used to estimate postural stability and gait pattern. This review article has compared results of placement of sensors at different locations helping researchers and clinicians to identify the best possible placement for sensors to measure specific kinematic and kinetic parameters in persons with stroke.

Effects of trunk stabilization exercises using laser pointer visual feedback in patients with chronic stroke: A randomized controlled study

BACKGROUND

Many previous studies have cited the importance of trunk stabilization exercises in patients with stroke. However, the evidence for optimal trunk stabilization exercises for patients with stroke is still lacking.

OBJECTIVE

To investigate the effects of laser pointer visual feedback in trunk stabilization exercises that are important for improving trunk dysfunction in patients with stroke.

METHODS

In total, 30 patients with chronic stroke were randomly assigned to experimental and control groups. The experimental group underwent a traditional stroke rehabilitation program and trunk stabilization exercises using laser pointer visual feedback. The control group underwent a traditional stroke rehabilitation program and trunk stabilization exercises without visual feedback. Pre- and postintervention results after 6 weeks were evaluated using the Berg Balance Scale, static and dynamic plantar pressure, 10-m walk test, and the Korean version of the Fall Efficacy Scale. The results were analyzed using a general linear repeated measurement model.

RESULTS

Both groups showed significant improvements in BBS scores, static plantar pressure, dynamic plantar pressure, 10 MWT, and K-FES scores after 6 weeks of intervention (P< 0.05). Compared to the control group, significant improvements were observed in the experimental group in the Berg Balance Scale scores, dynamic paretic posterior plantar pressure, 10-m walk test, and Korean version of the Fall Efficacy Scale scores (P< 0.025).

CONCLUSION

Our results demonstrated the effectiveness of visual feedback during trunk stabilization exercises for resolving trunk dysfunction in patients with stroke. Trunk stabilization exercises using laser pointer visual feedback have been found to be more effective in balance, walking, and fall efficacy in patients with stroke.

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.

Electrotactile Perception Properties and Its Applications: A Review

With the increased demands of human-machine interaction, haptic feedback is becoming increasingly critical. However, the high cost, large size and low efficiency of current haptic systems severely hinder further development. As a portable and efficient technology, cutaneous electrotactile stimulation has shown promising potential for these issues. This paper presents a review on and insight into cutaneous electrotactile perception and its applications. Research results on perceptual properties and evaluation methods have been summarized and discussed to understand the effects of electrotactile stimulation on humans. Electrotactile applications are presented in categories to understand the methods and progress in various fields such as prostheses control, sensory substitution, sensory restoration and sensorimotor restoration. State of the art has demonstrated the superiority of electrotactile feedback, its efficiency and its flexibility. However, the complex factors and the limitations of evaluation methods made it challenging for precise electrotactile control. Groundbreaking innovation in electrotactile theory is expected to overcome challenges such as precise perception control, information capacity increasing, comprehension burden reducing and implementation costs.

Design of multi-pad electrotactile system envisioned as a feedback channel for supernumerary robotic limbs

BACKGROUND

Providing real-time haptic feedback is an important, but still not sufficiently explored aspect of use of supernumerary robotic limbs (SRLs). We present a multi-pad electrode for conveying multi-modal proprioceptive and sensory information from SRL to the user's thigh and propose a method for stimuli calibration.

METHODS

Within two pilot tests we investigated return electrode configuration and active electrode discrimination in three healthy subjects to select the appropriate electrode pad topology. Based on the obtained results and anthropometric data from literature, the electrode was designed to have three branches of 10 pads and two additional pads that can be displaced over/under the electrode branches. The electrode was designed to be connected to the stimulator that allows full multiplexing so that specific branches can serve as common return electrode. To define the procedure for application of this system, the sensation, localization and discomfort thresholds applicable for the novel electrode were determined and analysed in ten subjects.

RESULTS

The results showed no overlaps between the three thresholds for individual pads, with significantly different average values, suggesting that the selected electrode positioning and design provide good active range of useful current amplitude. The results of the subsequent analysis suggested that the stimuli intensity level of 200% of sensation threshold is the most probable value of the localization threshold. Furthermore, this level ensures low chance (i.e. 0.7%) of reaching the discomfort.

CONCLUSIONS

We believe that envisioned electrotactile system could serve as a high bandwidth feedback channel that can be easily setup to provide proprioceptive and sensory feedback from supernumerary limbs.

Review of Real-Time Biomechanical Feedback Systems in Sport and Rehabilitation

Real-time biomechanical feedback (BMF) is a relatively new area of research. The potential of using advanced technology to improve motion skills in sport and accelerate physical rehabilitation has been demonstrated in a number of studies. This paper provides a literature review of BMF systems in sports and rehabilitation. Our motivation was to examine the history of the field to capture its evolution over time, particularly how technologies are used and implemented in BMF systems, and to identify the most recent studies showing novel solutions and remarkable implementations. We searched for papers in three research databases: Scopus, Web of Science, and PubMed. The initial search yielded 1167 unique papers. After a rigorous and challenging exclusion process, 144 papers were eventually included in this report. We focused on papers describing applications and systems that implement a complete real-time feedback loop, which must include the use of sensors, real-time processing, and concurrent feedback. A number of research questions were raised, and the papers were studied and evaluated accordingly. We identified different types of physical activities, sensors, modalities, actuators, communications, settings and end users. A subset of the included papers, showing the most perspectives, was reviewed in depth to highlight and present their innovative research approaches and techniques. Real-time BMF has great potential in many areas. In recent years, sensors have been the main focus of these studies, but new types of processing devices, methods, and algorithms, actuators, and communication technologies and protocols will be explored in more depth in the future. This paper presents a broad insight into the field of BMF.

The Effects of Auditory Feedback Gait Training Using Smart Insole on Stroke Patients

This study aimed to assess the effect of the auditory feedback gait training (AFGT) using smart insole on the gait variables, dynamic balance, and activities of daily living (ADL) of stroke patients. In this case, 45 chronic stroke patients who were diagnosed with a stroke before 6 months and could walk more than 10 m were included in this study. Participants were randomly allocated to the smart insole training group (n = 23), in which the AFGT system was used, or to the general gait training group (GGTG) (n = 22). Both groups completed conventional rehabilitation, including conventional physiotherapy and gait training, lasting 60 min per session, five times per week for 4 weeks. Instead of gait training, the smart insole training group received smart insole training twice per week for 4 weeks. Participants were assessed using the GAITRite for gait variables and Timed Up and Go test (TUG), Berg Balance Scale (BBS) for dynamic balance, and Modified Barthel Index (MBI) for ADL. The spatiotemporal gait parameters, symmetry of gait, TUG, BBS, and MBI in the smart insole training group were significantly improved compared to those in the GGTG (p < 0.05). The AFGT system approach is a helpful method for improving gait variables, dynamic balance, and ADL in chronic stroke patients.

Wearable Sensor-Based Real-Time Gait Detection: A Systematic Review

Gait analysis has traditionally been carried out in a laboratory environment using expensive equipment, but, recently, reliable, affordable, and wearable sensors have enabled integration into clinical applications as well as use during activities of daily living. Real-time gait analysis is key to the development of gait rehabilitation techniques and assistive devices such as neuroprostheses. This article presents a systematic review of wearable sensors and techniques used in real-time gait analysis, and their application to pathological gait. From four major scientific databases, we identified 1262 articles of which 113 were analyzed in full-text. We found that heel strike and toe off are the most sought-after gait events. Inertial measurement units (IMU) are the most widely used wearable sensors and the shank and foot are the preferred placements. Insole pressure sensors are the most common sensors for ground-truth validation for IMU-based gait detection. Rule-based techniques relying on threshold or peak detection are the most widely used gait detection method. The heterogeneity of evaluation criteria prevented quantitative performance comparison of all methods. Although most studies predicted that the proposed methods would work on pathological gait, less than one third were validated on such data. Clinical applications of gait detection algorithms were considered, and we recommend a combination of IMU and rule-based methods as an optimal solution.

Systematic review on wearable lower-limb exoskeletons for gait training in neuromuscular impairments

Gait disorders can reduce the quality of life for people with neuromuscular impairments. Therefore, walking recovery is one of the main priorities for counteracting sedentary lifestyle, reducing secondary health conditions and restoring legged mobility. At present, wearable powered lower-limb exoskeletons are emerging as a revolutionary technology for robotic gait rehabilitation. This systematic review provides a comprehensive overview on wearable lower-limb exoskeletons for people with neuromuscular impairments, addressing the following three questions: (1) what is the current technological status of wearable lower-limb exoskeletons for gait rehabilitation?, (2) what is the methodology used in the clinical validations of wearable lower-limb exoskeletons?, and (3) what are the benefits and current evidence on clinical efficacy of wearable lower-limb exoskeletons? We analyzed 87 clinical studies focusing on both device technology (e.g., actuators, sensors, structure) and clinical aspects (e.g., training protocol, outcome measures, patient impairments), and make available the database with all the compiled information. The results of the literature survey reveal that wearable exoskeletons have potential for a number of applications including early rehabilitation, promoting physical exercise, and carrying out daily living activities both at home and the community. Likewise, wearable exoskeletons may improve mobility and independence in non-ambulatory people, and may reduce secondary health conditions related to sedentariness, with all the advantages that this entails. However, the use of this technology is still limited by heavy and bulky devices, which require supervision and the use of walking aids. In addition, evidence supporting their benefits is still limited to short-intervention trials with few participants and diversity among their clinical protocols. Wearable lower-limb exoskeletons for gait rehabilitation are still in their early stages of development and randomized control trials are needed to demonstrate their clinical efficacy.

EFFECT OF PHASE-SHIFTED AUDITORY CUE ON GAIT SYMMETRY AND TRUNK DISPLACEMENT DURING TREADMILL WALKING

This study investigated changes in gait symmetry with trunk displacement during phase-shifted auditory paced treadmill walking for effective training with auditory cueing provided in conventional gait training. Eighteen able-bodied participants walked at a comfortable speed on a treadmill and the measured cadence was set at 100% (baseline). The phase-shifted auditory cue was set to both phase advance and delay of 20% at 5% intervals based on the baseline with respect to matching foot contact to the auditory cue. Trunk displacement increased with the phase-shifted auditory cue, and the largest value was found in the 120% condition compared to baseline ([Formula: see text]). Step length, step time, and swing phase time symmetry ratio gradually increased with increasing phase delay and gradually decreased with increasing phase advance on the linear model. However, single support time and stance phase time symmetry ratio showed contrasting characteristics compared to above parameters. The results indicate that the phase-shifted auditory cue significantly changes gait symmetry and trunk displacement. Particularly, the 20% phase advance and delay cues yielded about a 5% change in the step length symmetry ratio. These results could be used to induce a symmetric gait pattern when an asymmetric gait appears in hemiplegia.