Rehabilitation Technology Research Articles

Data Processing and Machine Learning for Assistive and Rehabilitation Technologies

This Special Issue (SI), “Data Processing and Machine Learning for Assistive and Rehabilitation Technologies”, aimed to collect cutting-edge research papers that frame how data-driven approaches and machine learning techniques are advancing the field of assistive and rehabilitation technologies [...]

Satisfaction, user experiences, and initial efficacy of a technology-supported self-management intervention (iSMART) to improve post-stroke functioning: a remoted randomized controlled trial

ABSTRACT Background Self-management interventions empower individuals to manage their chronic conditions and daily life after stroke. However, traditional in-person self-management interventions often face transportation and geographical barriers. Digital interventions may offer a solution to address this gap. Objectives This pilot randomized controlled trial (RCT) aimed to examine treatment satisfaction, user experiences, and the initial effect of the interactive Self-Management Augmented by Rehabilitation Technologies (iSMART) intervention in stroke survivors to improve post-stroke functioning. Methods Participants (N = 24) with mild-to-moderate chronic stroke completed a parallel, 2-arm, nonblinded, remote RCT. They were randomly assigned to either a 12-week iSMART or a control intervention (post-stroke information). iSMART was a technology-based self-management intervention involving skill-building education, human coaching, and text messaging. Participants completed a battery measuring treatment satisfaction, use experiences, and function and participation outcomes at baseline and post-intervention. Results iSMART participants expressed greater satisfaction with their treatment (r = 0.387), healthcare environment (r = 0.454), relationships with providers (r = 0.374), and higher expectations for positive treatment outcomes (r = 0.328) than control participants, with medium effect sizes. The iSMART group rated the overall program and its coaching, skill-building, and text messaging components as helpful. iSMART participants showed a medium effect in improving overall post-stroke functioning, but control participants showed a small effect. Moreover, iSMART participants showed moderate-to-large effects in improving hand function (r = 0.699), mobility (r = 0.499), memory and thinking (r = 0.436), communication (r = 0.416), social participation (r = 0.307), community reintegration (r = 0.652), and perceived recovery (r = 0.545). Conclusions Our results provide initial evidence that iSMART supports stroke survivors in managing chronic conditions and enhancing post-stroke functioning.

Research on Interactive Control Algorithms for Lower Limb Exoskeleton Rehabilitation Robots

Lower limb exoskeleton rehabilitation robots represent an important development direction in modern rehabilitation technology. By integrating various sensors and control algorithms, these robots effectively enhance the specificity and efficiency of rehabilitation training. This paper systematically analyzes several widely used control methods, including position-based, force feedback, bioelectrical signal, and intelligent control strategies. Each strategy has its unique features and addresses different issues in the interaction between the robot and the patient, thereby improving the effectiveness and efficiency of rehabilitation training. For instance, position control provides stability and repeatability, force control ensures compliance, bioelectrical signal control offers rapid responsiveness, and intelligent control exhibits adaptability. Future research will focus on combining the advantages of different strategies to develop composite control methods that enable more efficient and personalized rehabilitation training, enhancing patient recovery outcomes and experiences

Novel AIRTrode-based wearable electrode supports long-term, online brain–computer interface operations

Non-invasive electroencephalograms (EEG)-based brain-computer interfaces (BCIs) play a crucial role in a diverse range of applications, including motor rehabilitation, assistive and communication technologies, benefiting users across various clinical spectrums. Effective integration of these applications into daily life requires systems that provide stable and reliable BCI control for extended periods. Our prior research introduced the AIRTrode, a self-adhesive (A), injectable (I), and room-temperature (RT) spontaneously-crosslinked hydrogel electrode (AIRTrode). The AIRTrode has shown lower skin-contact impedance and greater stability than dry electrodes and, unlike wet gel electrodes, does not dry out after just a few hours, enhancing its suitability for long-term application. This study aims to demonstrate the efficacy of AIRTrodes in facilitating reliable, stable and long-term online EEG-based BCI operations. In this study, four healthy participants utilized AIRTrodes in two BCI control tasks - continuous and discrete - across two sessions separated by six hours. Throughout this duration, the AIRTrodes remained attached to the participants' heads. In the continuous task, participants controlled the BCI through decoding of upper-limb motor imagery (MI). In the discrete task, the control was based on decoding of error-related potentials (ErrPs). Using AIRTrodes, participants demonstrated consistently reliable online BCI performance across both sessions and tasks. The physiological signals captured during MI and ErrPs tasks were valid and remained stable over sessions. Lastly, both the BCI performances and physiological signals captured were comparable with those from freshly applied, research-grade wet gel electrodes, the latter requiring inconvenient re-application at the start of the second session. AIRTrodes show great potential promise for integrating non-invasive BCIs into everyday settings due to their ability to support consistent BCI performances over extended periods. This technology could significantly enhance the usability of BCIs in real-world applications, facilitating continuous, all-day functionality that was previously challenging with existing electrode technologies.

Fusing CNNs and attention-mechanisms to improve real-time indoor Human Activity Recognition for classifying home-based physical rehabilitation exercises

Physical rehabilitation plays a critical role in enhancing health outcomes globally. However, the shortage of physiotherapists, particularly in developing countries where the ratio is approximately ten physiotherapists per million people, poses a significant challenge to effective rehabilitation services. The existing literature on rehabilitation often falls short in data representation and the employment of diverse modalities, limiting the potential for advanced therapeutic interventions. To address this gap, This study integrates Computer Vision and Human Activity Recognition (HAR) technologies to support home-based rehabilitation. The study mitigates this gap by exploring various modalities and proposing a framework for data representation. We introduce a novel framework that leverages both Continuous Wavelet Transform (CWT) and Mel-Frequency Cepstral Coefficients (MFCC) for skeletal data representation. CWT is particularly valuable for capturing the time-frequency characteristics of dynamic movements involved in rehabilitation exercises, enabling a comprehensive depiction of both temporal and spectral features. This dual capability is crucial for accurately modelling the complex and variable nature of rehabilitation exercises. In our analysis, we evaluate 20 CNN-based models and one Vision Transformer (ViT) model. Additionally, we propose 12 hybrid architectures that combine CNN-based models with ViT in bi-model and tri-model configurations. These models are rigorously tested on the UI-PRMD and KIMORE benchmark datasets using key evaluation metrics, including accuracy, precision, recall, and F1-score, with 5-fold cross-validation. Our evaluation also considers real-time performance, model size, and efficiency on low-power devices, emphasising practical applicability. The proposed fused tri-model architectures outperform both single-architectures and bi-model configurations, demonstrating robust performance across both datasets and making the fused models the preferred choice for rehabilitation tasks. Our proposed hybrid model, DenMobVit, consistently surpasses state-of-the-art methods, achieving accuracy improvements of 2.9% and 1.97% on the UI-PRMD and KIMORE datasets, respectively. These findings highlight the effectiveness of our approach in advancing rehabilitation technologies and bridging the gap in physiotherapy services.

Pohled ergoterapeutů, fyzioterapeutů a pacientů na aplikaci tradičních a inovativních postupů Constraint-induced movement therapy v České republice

Background: The comprehensive therapeutic program, Constraint-induced movement therapy (CIMT), focuses on functional training of the paretic upper limb and the transfer of acquired skills in daily life. Aim: The purpose of the survey was to map the current experience of therapists and patients with the therapeutic toolkit and home activity monitoring. Methods: The components of CIMT currently used, monitoring forms, barriers to provision, and motivations and subjectively perceived limitations for the use of technology in rehabilitation for activity monitoring were explored with the use of on-line surveys. Results: A total of 95 occupational therapists and physiotherapists and 91 patients participated in the survey. Czech therapists reported the most common perceived barriers that limit CIMT provision were as follows: low number of suitable patients, lack of knowledge of the method, increased administrative and time demands, or concerns about the high demands of the method for patients. The patients themselves are then limited in participating in the program due to its low accessibility or fear of the high difficulty of the exercise. As part of monitoring, patients complete a paper exercise diary (36%) or less frequently one on a computer (6.7%), but most often they do not track the results (40.4%). A total of 55% of patient respondents are motivated to share their results electronically with their therapist. Conclusions: According to the survey results, patients with spastic paresis of the upper limb after brain injury are motivated to participate in remote therapy and share results of home exercise remotely. The application of innovative approaches in CIMT and activity monitoring increases the availability of therapeutic interventions with potential cost reduction in clinical practice.

The intersection of artificial intelligence and rehabilitation sciences: promoting originality and integrity in research

Artificial Intelligence (AI) as a scientific discipline is an exciting opportunity for the development of a new direction in rehabilitation sciences and the improvement of patient care and research approaches [1]. Nevertheless, this integration brings a lot of problems to the issue of credibility and novelty around the processes of researching practices. Thus, this editorial is devoted to these questions, stressing the importance of a strong ethic compared to the standards for research in this shifting context. AI technologies have started influencing Rehabilitation sciences by offering individualized intervention, patient tracking, and optimization of the results by using big data analytics [2, 3]. For example, the machine learning approach may retrieve an avalanche of data to predict rehabilitation strategies that may be effective for patients with particular characteristics [4]. Nonetheless, as more developments are created through the utilization of artificial intelligence, the likelihood of ethical concerns and questions regarding originality in research rises as well [5]. Scientific practice requires creativity and any utilization of AI needs to hold to this regulated element of advancement. Investigators should implement specific precautions to avoid plagiarism or the unauthorized borrowing of concepts through the use of AI tools [6]. This requires policies and procedures that define how the use of AI in production can be realized without compromising the research process domain [7]. AI practice must be brought into the open through mandatory reporting obligations that compel institutions to declare the use of AI throughout research processes It is equally important in all fields especially those which have the potential to endanger the lives of patients. As noted in various studies, the principles of ethical practice like candor, accountability, and transparency are critical in developing public confidence in science [8]. That means the rehabilitation sciences community must embrace the operational and best use of AI and ensure that researchers learn the ethics of using them and the importance of following the set standards. There is a need to ensure institutional commitment to the training of consciousness on responsible conduct of research and the use of AI [7]. Key factors touched upon here include bias that exists in the AI systems they develop and the kind of data they produce [9, 10]. To this end, researchers should be compelled to specify the strategies they have applied AI in their research; the database they have utilized; the algorithm they have employed; and the reasons as to why they selected such choices [11]. This transparency is necessary to make methods reproducible and trustworthy [12]. There was a proposal that enhancing the elements of interdisciplinary interaction would increase the yield of their work [13]. There is also the concern that the ethical standards followed should not be overlooked in the peer review processes thus the procedures should be changed to allow for the review of the implementation of AI [6]. Universities and research centers need to develop strong guidelines to prevent researchers from engaging in wrongdoing; this can involve developing and providing procedures for reporting research misconduct [14-16]. AI in the domain of rehabilitation sciences has the potential to take the specialty to the next level. However, this potential has to be controlled and balanced by the goals of novelty, as well as the ethical course of the research. By keeping the emphasis on ethical behavior and core principles of the rehabilitation sciences the community can embrace the attributes of AI while at the same time preserving the integrity of science. It will increase the quality of work done while also making new technologies in rehabilitation it is useful and beneficial for society. artificial intelligence integrity rehabilitation sciences

Advanced Technology in a Real-World Rehabilitation Setting: Longitudinal Observational Study on Clinician Adoption and Implementation.

Advanced technologies are becoming increasingly accessible in rehabilitation. Current research suggests technology can increase therapy dosage, provide multisensory feedback, and reduce manual handling for clinicians. While more high-quality evidence regarding the effectiveness of rehabilitation technologies is needed, understanding of how to effectively integrate technology into clinical practice is also limited. Current implementation of rehabilitation technology is inconsistent, with low uptake among clinicians and frequent reports of technology abandonment. An Australian rehabilitation provider opened a new technology therapy center in 2022, offering a unique opportunity to generate practice-based evidence to inform future technology implementation and research. This study aimed to investigate the implementation and adoption of advanced technology within a real-world rehabilitation setting. This study was a longitudinal observational study in a rehabilitation organization with inpatient, outpatient, and community settings. Allied health clinicians (n=119) within the organization had access to advanced technologies, with patients receiving neurological, spinal cord injury, brain injury, or general rehabilitation. Interventions included 21 advanced technologies, including robotic, virtual reality (VR), sensor-based, and functional electrical stimulation devices. Clinicians received training for devices in a staged approach by external and internal trainers. Data were collected from patient electronic medical records from July 1, 2022, to June 30, 2023. Outcomes included frequency of advanced technology use, patient demographics (age, gender, and primary health condition), clinician discipline, rehabilitation service (inpatient, outpatient, or community), goals of technology therapy sessions, and therapy dosage achieved (minutes active, number of repetitions, and meters walked). Clinicians used advanced technology 4208 times with 269 patients over 12 months; specifically, physiotherapists (2716/4208, 65%), occupational therapists (1396/4208, 33%), and allied health assistants (96/4208, 2%). The majority of patients had stroke, spinal cord injury, or brain injury diagnoses (188/269, 70%). Devices were typically used to target impairment and activity limitation-related goals. Frequently used devices included gait training body-weight support (VR treadmill and overground), overground robotic exoskeletons, and upper limb robotic VR devices. Outpatient services were the dominant users of advanced technology (3940/4208, 94%). Clinicians most commonly used devices for patients with stroke (1973/4208, 47%) and the greatest variety of devices for patients with stroke and spinal cord injury. The relative use of lower limb robotic devices was greater in inpatient services (91/178, 51%, vs outpatient services, 963/2335, 41%) (χ21=6.6, P=.01) and for patients with spinal cord injury (48/95, 51%, vs all other conditions, between 24%-31%; χ25=16.8, P=.005). The type and amount of advanced technology use differed between patient populations and rehabilitation settings. To support clinician use of advanced technology, devices should match the rehabilitation context. Tailored strategies are important, such as clinician training. Further practice-based research is required to provide guidance on implementation and to establish the effectiveness of advanced technology use.

Empirical Research on the Integration of Medical and Educational Models in Cultivating Professional Abilities in Traditional Chinese Medicine Rehabilitation Techniques

This study empirically analyzes the application effect of the integration of medical and educational models in cultivating professional abilities in traditional Chinese medicine rehabilitation techniques. The research subjects are 100 students from the Traditional Chinese Medicine Rehabilitation Technology major at Y school. Through questionnaire scores, practical training results, and interview data, this study explores the outcomes of this integrated approach. The findings reveal that students in the experimental group significantly outperform those in the control group in terms of practical operation skills, professional responsibility, and communication and collaboration skills. This research confirms the notable role of the medical-educational integration model in enhancing the professional skills and accomplishments of students majoring in traditional Chinese medicine rehabilitation, providing a scientific basis for vocational education reform and the cultivation of rehabilitation technical talents.

Brain-Computer Interfaces Enhanced by AI: Applications in Rehabilitation and Assistive Technology

Brain-Computer Interfaces (BCIs) enhanced by Artificial Intelligence (AI) represent a transformative frontier in rehabilitation and assistive technology. These systems enable direct communication between the brain and external devices, empowering individuals with neurological impairments to regain lost functions and enhance their quality of life. By integrating AI, BCIs can decode complex neural signals with unprecedented accuracy, enabling applications such as motor function restoration, cognitive enhancement, and assistive communication. This research explores the current state of AI-driven BCIs, focusing on their impact on rehabilitation for stroke survivors, individuals with spinal cord injuries, and those with neurodegenerative disorders. Ethical challenges, such as data privacy, consent, and accessibility, are also examined. Through a review of case studies and emerging trends, this study highlights the potential of AI-enhanced BCIs to revolutionize neurorehabilitation and foster greater independence for individuals with disabilities.

Stepping up recovery: integrating patient reported outcome measures and wearable technology for 90-day rehabilitation following total hip arthroplasty.

There is conflicting data in the literature regarding the clinical utility of wearable devices. This study examined the association between patient reported outcome measures (PROMs) and step and stair flight counts obtained from wearable devices in postoperative total hip arthroplasty (THA) patients. Data was collected from a multicenter prospective longitudinal cohort study from October 2018 to February 2022. A smartphone-based platform with smartwatch was utilized for collection of daily step and stair flight counts. Subjects (N = 1644) completed the Hip disability and Osteoarthritis Outcome Score for Joint Replacement (HOOS JR) and numerical rating scale (NRS) pain scores preoperatively and at 1 and 3months postoperatively. Patients who reported living in a multi-level home (N = 931) were included in analysis of stair flight counts. Pearson correlation coefficients were calculated to determine correlations between step and stair flight counts with NRS pain and HOOS JR scores. Step counts demonstrated a weak negative correlation to NRS pain scores at preoperative (r = -0.15, p < 0.0001), 1-month (r = -0.15, p < 0.0001), and 3-months follow-up (r = -0.06, p = 0.05). Step counts demonstrated a weak positive correlation with HOOS JR scores at preoperative (r = 0.16, p < 0.0001), 1-month (r = 0.15, p < 0.0001), and 3-months (r = 0.13, p < 0.0001). Stair flight counts demonstrated a weak negative correlation with NRS pain preoperatively (r = -0.19, p < 0.0001) and at 1-month (r = -0.11, p = 0.003). Stair flight counts positively correlated with HOOS JR scores at preoperative (r = 0.24, p < 0.0001), 1-month (r = 0.15, p < 0.0001), and 3-months (r = 0.09, p = 0.02). The utilization of wearable technology can enhance the evaluation of patient outcomes after THA, primarily due to the observed correlation between data collected from wearables and PROMs. Our study highlights the importance of the use of objective data, in addition to subjective patient reported data, when analyzing postoperative patient progress, which propels forward the field of postoperative THA patient care.

Rehabilitation technology in assessment and treatment of arm and hand function in myotonic dystrophy type 1: A single subject experimental design study

Background: Myotonic Dystrophy type 1 (DM1) is a slowly progressive hereditary neuromuscular disorder affecting several organ systems including the musculoskeletal system. Objective: To examine the effects of rehabilitation technology on arm and hand function in the assessment and treatment of adults with DM1 with moderate to severe muscle impairment. Methods: A single subject experimental design study (SSED) with 6 participants. The assessments were done weekly through remote study assessments using the video-conference system Whereby®. Participants performed the nine-hole peg test (NHPT), active range of motion (AROM) of the shoulder and patient reported outcome measures (PROMS). Three participants also measured grip and pinch strength and performed the Nut and Bolt task. The intervention was a three-week in-patient rehabilitation stay with the use of rehabilitation technology for exercising arm and hand function. Exercises were performed in AMADEO and the ArmeoSenso. The participants exercised the upper extremities for 30 min 5 times a week. Results: Improvement on the NHPT test on the dominant hand were found for five of the six participants. Three of six improved on the non-dominant hand and in AROM. Two of the three participants that measured pinch and grip strength improved, and all three improved on the Nut and Bolt task. Self- reported function, myotonia and fatigue remained stable. All participants were able to participate in video assessments. Conclusions: Impairment in arm- and hand function affects independence in people with DM1.Our findings suggest that exercising arm- and hand using rehabilitation technology may have a positive effect on function measured by dexterity, strength, and movement in DM1. There is a need to study the effect of exercise on arm- and hand function in DM1 in larger studies. The use of video-consultations can be a supplement in assessment of people with neuromuscular conditions in research and clinical practise.

Advancing public health through technological rehabilitation: insights from a national clinician survey

IntroductionIn the evolving healthcare landscape, technology has emerged as a key component in enhancing system efficiency and offering new avenues for patient rehabilitation. Despite its growing importance, detailed information on technology's specific use, types, and applications in clinical rehabilitation settings, particularly within the Italian framework, remains unclear. This study aimed to explore the use of technology and its needs by Physical Medicine and Rehabilitation medical doctors in Italy.MethodsWe conducted a cross-sectional online survey aimed at 186 Italian clinicians affiliated with the Italian Society of Physical and Rehabilitation Medicine (SIMFER). The online questionnaire consists of 71 structured questions designed to collect demographic and geographical data of the respondents, as well as detailed insights into the prevalence and range of technologies they use, together with their specific applications in clinical settings."ResultsA broad range of technologies, predominantly commercial medical devices, has been documented. These technologies are employed for various conditions, including common neurological diseases, musculoskeletal disorders, dementia, and rheumatologic issues. The application of these technologies indicates a broadening scope beyond enhancing sensorimotor functions, addressing both physical and social aspects of patient care.DiscussionIn recent years, there's been a notable surge in using technology for rehabilitation across various disorders. The upcoming challenge is to update health policies to integrate these technologies better, aiming to extend their benefits to a wider range of disabling conditions, marking a progressive shift in public health and rehabilitation practices.

Employment outcomes among clients with stroke utilizing public vocational rehabilitation services in the United States.

To examine the correlations between individual characteristics among clients with stroke within public vocational rehabilitation (VR) and the employment outcome, as well as the utilization of VR services and their employment outcomes after VR services. Observational cohort study SETTING: Nationwide vocational rehabilitation data from the Rehabilitation Service Administration Case Service Report (RSA-911) for fiscal year 2022. Individuals with stroke as primary cause of disability MAIN OUTCOME MEASURES: employment status and VR service types RESULTS: Of those with stroke who received VR services (n = 1,793), 653 (36.4%) achieved a competitive employment outcome. African American clients were less likely to be competitively employed at closure than White clients, OR = .72, 95% CIs [0.56, 0.92]. Clients whose primary disability was auditory or communicative disabilities were more likely to be competitively employed at closure, OR = 2.25, 95% CIs [1.22, 4.17]. Regarding VR services, receiving distinct types of VR services significantly was associated with the competitive employment outcome for clients. Clients who received short-term job support services were 6.36 times more likely to be competitively employed at closure than those who did not receive the service, OR = 6.36, 95% CIs [4.28, 9.46]. Our results found that race, types of primary disability, level of education, receipt of SSI/SSDI, and the length of the VR services were associated with obtaining or regaining employment among clients with stroke who received public VR services. In terms of VR service patterns, job support services, job placement assistance, rehabilitation technology supports, maintenance services, other services, and VR counseling and guidance were associated with competitive employment outcomes among individuals with stroke.

Manual medical technologies in complex treatment and rehabilitation of patients with primary osteoarthritis (literature review)

The review discusses the pathogenetic mechanisms of primary osteoarthritis (OA) formation. The recommendations of the Association of Rheumatologists of Russia on the main principles of rehabilitation for OA are presented, including drug and non-drug methods of pain syndrome correction, improvement of motor activity and quality of life of patients. Particular attention is paid to the mechanisms of osteopathic correction for OA, which are aimed at restoring the impaired biomechanics of the patient’s body, eliminating persistent muscle hypertonicity, peripheral sensitization, and aimed at regulating antinociceptive mechanisms. An important advantage of manual treatment is the possibility of its use before, during or after other types of treatment and the ability to enhance their therapeutic potential.

Potential of plants and microorganisms for bioremediation technologies for mine rehabilitation

The mining industry is one of the priority sources of environmental pollution by potentially toxic metals. The impact on the environment remains significant even after the end of mining activities. Numerous studies report the environmental impact of abandoned mines. Therefore, cleaning of mine territories from the pollution is of priority importance. Phytoremediation and microbial remediation are some of the methods. The study of plants for their possible use in phytoremediation is of great interest. Such works are of great importance in developing modern phytoremediation technologies, as they allow us to find new hyperaccumulators for possible mine reclamation. Microorganisms possessing resistance to heavy metals, such as fungi and bacteria, as well as unicellular algae, may be used to clean up tailings contaminated with potentially toxic metals. The microbiological method of tailings treatment is based on the ability of microorganisms to transform and decompose chemical compounds. Microbial remediation and phytoremediation are attracting more and more attention due to their relatively low cost and environmental friendliness. A large number of studies related to the investigation of mine plants and microorganisms and their utilization for mine cleanup demonstrate the promise of using bioremediation. Further development of bioremediation technologies will be associated with wider implementation of the research findings in practice and the possible use of biotechnology in bioremediation. The successful practical application of mine bioremediation requires a complex interdisciplinary approach associated with biological, ecological, biotechnological, and geographic-geological areas.

The Use of Extrinsic Performance Feedback and Reward to Enhance Upper Limb Motor Behavior and Recovery Post-Stroke: A Scoping Review.

During post-stroke motor rehabilitation, patients often receive feedback from therapists or via rehabilitation technologies. Research suggests that feedback may benefit motor performance, skill acquisition, and action selection. However, there is no consensus on how extrinsic feedback should be implemented during stroke rehabilitation to best leverage specific neurobehavioral mechanisms to optimize recovery. To identify the existing evidence and research gaps regarding the effects of extrinsic feedback on upper extremity motor function in stroke survivors, and to map the evidence onto neurobehavioral concepts of motor performance, motor learning, and action selection. The MEDLINE, PsychInfo, EMBASE, and CINHAL databases were searched for relevant articles. A sequential screening process and data extraction were performed by 2 independent reviewers, and the results were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews guidelines. A total of 29 studies were identified that met the criteria for inclusion. Beneficial effects of feedback were reported for clinical outcomes of rehabilitation interventions as well as motor performance, motor learning, and action selection post-stroke. Three studies showed that the addition of rewarding elements to positive performance feedback benefited learning or recovery. Extrinsic feedback has the potential to improve outcomes of stroke rehabilitation through effects on motor performance, motor learning, or action selection. To understand how these specific neurobehavioral processes contribute to recovery, clinical trials should include more granular behavioral measures. Rewarding feedback may be particularly beneficial, but more research is needed regarding the specific implementation of feedback.

Haptic Technology: Exploring Its Underexplored Clinical Applications-A Systematic Review.

Haptic technology has transformed interactions between humans and both tangible and virtual environments. Despite its widespread adoption across various industries, the potential therapeutic applications of this technology have yet to be fully explored. A systematic review of randomized controlled trials (RCTs) and randomized crossover trials was conducted, utilizing databases such as PubMed, Embase, Cochrane Library, and Web of Science. This review included studies reporting clinical applications of haptic technology in rehabilitation, cognition, wellness, and mental health among adult subjects. This systematic review included 34 studies, of which 20 focused on clinical outcomes and 14 on learning clinical skills. The results showed that haptic devices, both robotic and non-robotic, enhance sensorimotor performance and motor function in rehabilitation settings, especially in post-stroke recovery, with reported effect sizes ranging from 0.2 to 0.7. The majority of the haptic technologies reported were integrated into robotic systems (40%). Haptic devices were also reported to improve clinical skills training by providing tactile feedback that enhances procedural performance and trainee self-efficacy. In fact, surgical simulations accounted for 79% of all the modalities used for medical training. This review underscores the potential yet underexplored applications of haptic technology in healthcare, including medical education, rehabilitation, cognition, and mental health. The key limitations of this review include heterogeneity across studies, small sample sizes, and a scarcity of comprehensive, long-term investigations. Therefore, future research should aim to validate these findings further and expand the applications of haptic technology to maximize its utility in the healthcare industry and clinical practice.

Rehabilitation Technologies by Integrating Exoskeletons, Aquatic Therapy, and Quantum Computing for Enhanced Patient Outcomes.

Recent advancements in patient rehabilitation integrate both traditional and modern techniques to enhance treatment efficacy and accessibility. Hydrotherapy, leveraging water's physical properties, is crucial for reducing joint stress, alleviating pain, and improving circulation. The rehabilitation of upper limbs benefits from technologies like virtual reality and robotics which, when combined with hydrotherapy, can accelerate recovery. Exoskeletons, which support and enhance movement, have shown promise for patients with neurological conditions or injuries. This study focused on implementing and comparing proportional-integral-derivative (PID) and fuzzy logic controllers (FLCs) in a lower limb exoskeleton. Initial PID control tests revealed instability, leading to a switch to a PI controller for better stability and the development of a fuzzy control system. A hybrid strategy was then applied, using FLC for smooth initial movements and PID for precise tracking, with optimized weighting to improve performance. The combination of PID and fuzzy controllers, with tailored weighting (70% for moderate angles and 100% for extensive movements), enhanced the exoskeleton's stability and precision. This study also explored quantum computing techniques, such as the quantum approximate optimization algorithm (QAOA) and the quantum Fourier transform (QFT), to optimize controller tuning and improve real-time control, highlighting the potential of these advanced tools in refining rehabilitation devices.

Цифровое здравоохранение в медицинской реабилитации после инсульта: менеджмент телемедицинских технологий.

The development of digital technologies leads to a digital transformation of the healthcare system. Recently, digital healthcare has been developing dynamically, including its component part – telerehabilitation after a stroke. However, the novelty of technologies, their diversity, low awareness of doctors and healthcare organizers, and other reasons, do not allow healthcare organizations to use all their tools to manage organizational, managerial and medical problems of medical rehabilitation after a stroke. The aim of the study is to systematize information on telemedicine and cross-cutting digital technologies used in organizing medical rehabilitation of patients who have suffered a stroke, as well as the development of approaches to manage of these technologies to constantly improve the quality of healthcare and increase patient satisfaction. Materials and methods. The study used methods of information retrieval, analytical and synthetic research, etc. Results. The study showed that the development of technologies leads to an increase in the use of cross-cutting digital technologies in telemedicine rehabilitation of stroke patients. The results indicate the possibility of improving the quality and accessibility of medical care using telerehabilitation and cross-cutting technologies, expanding medical coverage, and improving therapeutic results in recovery of patients’ health. The PDCA cycle can be used to manage telerehabilitation and digital technologies. Findings. The introduction of digital technologies into telemedicine practice can reduce the workload of health workers and improve manageability with respect to a patient-centric approach. The use of quality management system principles and PDCA cycle can provide the standardization of telerehabilitation management, improve the quality of healthcare and patient satisfaction, contributing to the sustainable development of healthcare organizations.