Search Results (17)

Upper-limb motor impairment is a major consequence of stroke and neuromuscular disorders, imposing a sustained clinical and socioeconomic burden worldwide. Quantitative assessment of limb positioning and motion accuracy is fundamental to rehabilitation, guiding therapy evaluation and robotic assistance. The evolution of upper-limb positioning systems has progressed from optical motion capture to wearable inertial measurement units (IMUs) and, more recently, to data-driven estimators integrated with rehabilitation robots. Each generation has aimed to balance spatial accuracy, portability, latency, and metrological reliability under ecological conditions. This review presents a systematic synthesis of the state of measurement uncertainty, calibration, and traceability in upper-limb rehabilitation robotics. Studies are categorised across four layers, i.e., sensing, fusion, cognitive, and metrological, according to their role in data acquisition, estimation, adaptation, and verification. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was followed to ensure transparent identification, screening, and inclusion of relevant works. Comparative evaluation highlights how modern sensor-fusion and learning-based pipelines achieve near-optical angular accuracy while maintaining clinical usability. Persistent challenges include non-standard calibration procedures, magnetometer vulnerability, limited uncertainty propagation, and absence of unified traceability frameworks. The synthesis indicates a gradual transition toward cognitive and uncertainty-aware rehabilitation robotics in which metrology, artificial intelligence, and control co-evolve. Traceable measurement chains, explainable estimators, and energy-efficient embedded deployment emerge as essential prerequisites for regulatory and clinical translation. The review concludes that future upper-limb systems must integrate calibration transparency, quantified uncertainty, and interpretable learning to enable reproducible, patient-centred rehabilitation by 2030. Full article

Recently, telerehabilitation has taken on a significant role in rehabilitation programs, with benefits in improving balance. Many neurological diseases are associated with an increased fall risk and, considering the impact of falls on quality of life, the aim of this study is to evaluate the ability of the Silver Index (via the hunova^® robotic platform) to identify the fall risk and the effect of a telerehabilitation intervention (by ARC Intellicare) on fall risk in patients with neurological disorders. This is an ancillary study of a single-center, randomized controlled trial. Ninety patients with stroke, Multiple Sclerosis (MS), and Parkinson’s Disease (PD) participated, and were randomized into an ARC Intellicare group (experimental group) and a paper-based group (control group). Each group performed home treatment for 60 min a day, 3 days a week, for 8 weeks. Fall risk was assessed with clinical scales and hunova^®. Data analysis showed a correlation between clinical scales and the Silver Index. Furthermore, only the MS patients in the experimental group showed a significant decrease in fall risk (p = 0.015). This study suggested that the Silver Index is a valid tool for assessing fall risk in neurological disorders. It also confirmed that ARC Intellicare is a useful tool for remote rehabilitation at home. Full article

Background/Objectives: Balance, postural control, and functional independence are essential components for the autonomy of people with neurological conditions. Robotic technologies such as the Lokomat^® have emerged as promising tools in rehabilitation, but their effectiveness when integrated into functional programs requires further evidence. The objective of this study was to evaluate the impact of an intensive robotic intervention on these three functional variables. Methods: A single-group, quasi-experimental pretest–posttest study was conducted with 136 participants who received a robotic rehabilitation intervention using the Lokomat^® device, and focused on functional tasks over several weeks. Balance (using the Berg scale), postural control (using the PASS), and functional independence (using the Barthel index) were assessed, comparing pre- and post-intervention results using parametric and non-parametric tests. Results: The results showed statistically significant improvements in all three variables after the intervention. The mean Berg score increased from 11.76 to 21.91 points (p < 0.001), postural control increased from 15.53 to 21.90 points (p < 0.001), and the Barthel index increased from 24.71 to 41.76 points (p < 0.001). In all cases, the effect sizes were large (d > 0.90). Conclusions: A rehabilitation program including intensive, task-oriented Lokomat^® training was associated with improvements in balance, postural control, and functional independence. Given the single-group design without a control arm, these findings reflect associations and do not establish causality. Full article

Multiple Sclerosis (MS) is a chronic neurological disorder affecting the central nervous system that significantly impairs postural control and functional abilities. Robotic-assisted gait training mitigates this functional deterioration. This preliminary study aims to investigate the effects of a four-week gait training with the ExoAtlet II exoskeleton on static balance control and functional mobility in five individuals with MS (Expanded Disability Status Scale ≤ 2.5). Before and after the training, they were assessed in quiet standing under Eyes Open (EO) and Eyes Closed (EC) conditions and with the Timed Up and Go (TUG) test. Center of Pressure (CoP) Sway Area, Antero–Posterior (AP) and Medio–Lateral (ML) CoP displacement, Stay Time, and Total Instability Duration were computed. TUG test Total Duration, sit-to-stand, stand-to-sit, and linear walking phase duration were analyzed. To establish target reference values for rehabilitation advancement, the same evaluations were performed on a matched healthy cohort. After the training, an improvement in static balance with EO was observed towards HS values (reduced Sway Area, AP and ML CoP displacement, and Total Instability Duration and increased Stay Time). Enhancements under EC condition were less marked. TUG test performance improved, particularly in the stand-to-sit phase. These preliminary findings suggest functional benefits of exoskeleton gait training for individuals with MS. Full article

This research study proposes a heuristic hybrid deep neural network (DNN) gait sub-phase recognition model based on multi-source heterogeneous motion data fusion which quantifies gait phases and is applied in balance disorder rehabilitation control, achieving a recognition accuracy exceeding 99%. Building upon this model, a motion control strategy for a novel rehabilitation training robot is designed and developed. For patients with some degree of independent movement, an active training strategy is introduced; it combines gait recognition with a variable admittance control strategy. This strategy provides assistance during the stance phase and moderate support during the swing phase, effectively enhancing the patient’s autonomous movement capabilities and increasing engagement in the rehabilitation process. The gait phase recognition system not only provides rehabilitation practitioners with a comprehensive tool for patient assessment but also serves as a theoretical foundation for collaborative control in rehabilitation robots. Through the innovative active–passive training control strategy and its application in the novel rehabilitation robot, this research study overcomes the limitations of traditional rehabilitation robots, which typically operate in a single functional mode, thereby expanding their functional boundaries and enabling more precise, personalized rehabilitation training programs tailored to the needs of patients in different stages of recovery. Full article

Parkinson’s disease (PD) is a progressive movement disorder with no cure. In this randomized controlled study, 100 patients with PD were assigned to four intervention groups (Exergame, Cycling, Agility, and Robot) for 14 weeks. This study evaluates the effectiveness of high-intensity therapy in a randomized clinical trial. Exergaming, cycling, agility, and robot therapies improved motor function, postural stability, and cardiovascular health. Heart rate monitoring and Borg Scale ratings confirmed the safety and adaptability of high-intensity training, with patients sustaining moderate-to-high exertion without adverse effects. Significant improvements were observed in gait speed (+0.30–0.50 m/s), Functional Independence Measure (FIM) (+25–30 points), and Berg Balance Scale scores. Integrating high-intensity, functional movement-based therapies into PD rehabilitation may offer superior motor, gait, and cardiovascular benefits compared to conventional methods. Full article

Neurological disorders like stroke are one of the main causes of motor dysfunction and gait function disabilities in humans. These disorders impact the mobility of patients often leading to weakened and impaired ankle joints which further compromise their balance and walking abilities. Over the span of the last twenty years, there has been a rising interest in designing, developing, and using rehabilitative robots for patients suffering from various ankle joint disabilities. These robotic devices are developed by employing diverse mechanical designs, materials, and control strategies. The aim of this study is to provide a detailed overview of the recent developments in mechanical design, actuation, and control strategies of ankle rehabilitation robots. Experimental evaluation of the discussed ankle robots has also been carried out discussing their results and limitations. This article concludes by highlighting future challenges and opportunities for the advancement of ankle rehabilitation robots, stressing the need for robust and effective devices to better serve patients. Full article

The integration of redundant structures into robotic systems enhances the degrees of freedom (DOFs), flexibility, and capability to perform complex tasks. This study evaluates the mechanical performance of a 9-DOF series-parallel hybrid redundant device designed for rehabilitation training of patients with balance disorders. The redundant structural design improves the robot’s movement flexibility, optimizes load distribution, and mitigates stress concentration in local joints or components. To optimize the robot’s overall structural parameters and reduce joint driving forces, a genetic algorithm (GA) was employed. A custom dataset was created by collecting motion-related data, including foot posture and position. The robot’s mechanical characteristics were comprehensively analyzed, followed by simulation experiments. The results demonstrate that incorporating the redundant structure, along with the optimization of structural parameters, significantly enhances the robot’s mechanical performance. This study provides a solid foundation for the functional development and control system design of rehabilitation robots, extending the capabilities of existing systems and offering a novel, reliable, and efficient therapeutic tool for patients with balance disorders. Full article

Background: With South Korea’s growing aging population, the demand for accessible rehabilitation solutions is increasing. Home-based robotic rehabilitation presents a feasible alternative to conventional in-clinic rehabilitation. This study explores the impact of the Rebless robotic rehabilitation device in a home-based setting for people with physical disabilities and their caregivers. Methods: We prospectively collected data from individuals with brain disorders or physical disabilities living in Dongdaemun-gu, from August 2023 to March 2024. Participants completed an 8-week rehabilitation program using the Rebless robotic device. Assessments were conducted at baseline and after the eight-week program, measuring motor function, caregiver burden, and quality of life. Exercises were performed three times weekly for at least 90 min total. Results: We conducted an intervention with 26 adults with physical or neurological disabilities, of which 20 completed the program. Significant improvements were observed in upper limb function within the elbow exercise group (Fugl–Meyer assessment for upper extremity, p = 0.043) and a reduction in caregiver burden across the total groups (Zarit Burden Interview, p = 0.003). However, no statistically significant changes were found in balance and mobility measures (Berg balance scale, timed up-and-go, 10 m walk test). Conclusions: Home-based robotic rehabilitation demonstrates potential for improving upper limb function and reducing caregiver burden and mental health, proving beneficial to both patients and caregivers. Full article

Gait and balance have a direct impact on patients’ independence and quality of life. Due to a higher life expectancy, the number of patients suffering neurological disorders has increased exponentially, with gait and balance impairments being the main side effects. In this context, the use of rehabilitation robotic devices arises as an effective and complementary tool to recover gait and balance functions. Among rehabilitation devices, end effectors present some advantages and have shown encouraging outcomes. The objective of this study is twofold: to propose a general classification of devices for gait and balance rehabilitation and to provide a review of the existing end effectors for such purposes. We classified the devices into five groups: treadmills, exoskeletons, patient-guided systems, perturbation platforms, and end effectors. Overall, 55 end effectors were identified in the literature, of which 16 were commercialized. We found a disproportionate number of end effectors capable of providing both types of rehabilitation (2/55) and those focused on either balance (21/55) or gait (32/55). The analysis of their features from a mechanical standpoint (degrees of freedom, topology, and training mode) allowed us to identify the potential of parallel manipulators as driving mechanisms of end effector devices and to suggest several future research directions. Full article

This study delves into the multifaceted approaches to treating Parkinson’s disease (PD), a neurodegenerative disorder primarily affecting motor function but also manifesting in a variety of symptoms that vary greatly among individuals. The complexity of PD symptoms necessitates a comprehensive treatment strategy that integrates surgical interventions, pharmacotherapy, and physical therapy to tailor to the unique needs of each patient. Surgical options, such as deep brain stimulation (DBS), have been pivotal for patients not responding adequately to medication, offering significant symptom relief. Pharmacotherapy remains a cornerstone of PD management, utilizing drugs like levodopa, dopamine agonists, and others to manage symptoms and, in some cases, slow down disease progression. However, these treatments often lead to complications over time, such as motor fluctuations and dyskinesias, highlighting the need for precise dosage adjustments and sometimes combination therapies to optimize patient outcomes. Physical therapy plays a critical role in addressing the motor symptoms of PD, including bradykinesia, muscle rigidity, tremors, postural instability, and akinesia. PT techniques are tailored to improve mobility, balance, strength, and overall quality of life. Strategies such as gait and balance training, strengthening exercises, stretching, and functional training are employed to mitigate symptoms and enhance functional independence. Specialized approaches like proprioceptive neuromuscular facilitation (PNF), the Bobath concept, and the use of assistive devices are also integral to the rehabilitation process, aimed at improving patients’ ability to perform daily activities and reducing the risk of falls. Innovations in technology have introduced robotic-assisted gait training (RAGT) and other assistive devices, offering new possibilities for patient care. These tools provide targeted support and feedback, allowing for more intensive and personalized rehabilitation sessions. Despite these advancements, high costs and accessibility issues remain challenges that need addressing. The inclusion of exercise and activity beyond structured PT sessions is encouraged, with evidence suggesting that regular physical activity can have neuroprotective effects, potentially slowing disease progression. Activities such as treadmill walking, cycling, and aquatic exercises not only improve physical symptoms but also contribute to emotional well-being and social interactions. In conclusion, treating PD requires a holistic approach that combines medical, surgical, and therapeutic strategies. While there is no cure, the goal is to maximize patients’ functional abilities and quality of life through personalized treatment plans. This integrated approach, along with ongoing research and development of new therapies, offers hope for improving the management of PD and the lives of those affected by this challenging disease. Full article

Osteoarthritis is a common chronic condition in the elderly population and, with falls, represents a major public health problem. Patients with hip or knee osteoarthritis often have poor balance, which is considered an important risk factor for falls. In recent years, there has been increasing research supporting the use of robotic rehabilitation to improve function after total knee and hip replacement. The aim of this study is to investigate the effects of robotic balance rehabilitation on elderly patients who have undergone hip and knee replacement, with the aim of reducing the risk of falls and improving balance and walking, as well as motor function, fatigue, and overall quality of life. Twenty-four elderly patients with knee or hip replacement underwent robotic balance treatment with the Hunova^® platform or conventional treatment three times a week for four weeks. Patients underwent an assessment of balance, walking, autonomy, quality of life and fatigue. Patients who underwent rehabilitation with Hunova^® showed an improvement in dynamic balance (p = 0.0039) and walking (p = 0.001) and a reduction in both motor (p = 0.001) and cognitive (p = 0.05) fatigue. The study found that specific treatment for balance disorders in these patients could improve balance and reduce the risk of falling. Full article

In the neurorehabilitation field, robot-aided motion analysis (R-AMA) could be helpful for two main reasons: (1) it allows the registration and monitoring of patients’ motion parameters in a more accurate way than clinical scales (clinical purpose), and (2) the multitude of data produced using R-AMA can be used to build machine learning algorithms, detecting prognostic and predictive factors for better motor outcomes (research purpose). Despite their potential in clinical settings, robotic assessment tools have not gained widespread clinical acceptance. Some barriers remain to their clinical adoption, such as their reliability and validity compared to the existing standardized scales. In this narrative review, we sought to investigate the usefulness of R-AMA systems in patients affected by neurological disorders. We found that the most used R-AMA tools are the Lokomat (an exoskeleton device used for gait and balance rehabilitation) and the Armeo (both Power and Spring, used for the rehabilitation of upper limb impairment). The motion analysis provided by these robotic devices was used to tailor rehabilitation sessions based on the objective quantification of patients’ functional abilities. Spinal cord injury and stroke patients were the most investigated individuals with these common exoskeletons. Research on the use of robotics as an assessment tool should be fostered, taking into account the biomechanical parameters able to predict the accuracy of movements. Full article

Cerebral palsy (CP) is a congenital and permanent neurological disorder due to non-progressive brain damage that affects gross motor functions, such as balance, trunk control and gait. CP gross motor impairments yield more challenging right foot placement during gait phases, as well as the correct direction of the whole-body center of mass with a stability reduction and an increase in falling and tripping. For these reasons, robotic devices, thanks to their biomechanical features, can adapt easily to CP children, allowing better motor recovery and enjoyment. In fact, physiotherapists should consider each pathological gait feature to provide the patient with the best possible rehabilitation strategy and reduce extra energy efforts and the risk of falling in children affected by CP. Full article

Background: Motor, gait and balance disorders reduce functional capabilities for activities of daily living in children with cerebral palsy (CP). Robot-assisted gait therapy (RAGT) is being used to complement conventional therapy (CT) or treadmill therapy (TT) in CP rehabilitation. The aim of this systematic review is to assess the effect of RAGT on gait, balance and functional independence in CP children, in comparison to CT or TT. Methods: We have conducted a systematic review with meta-analysis. A search in PubMed Medline, Web of Science, Scopus, CINAHL, PEDro and SciELO has been conducted for articles published until October 2022. Controlled clinical trials (CCT), in which RAGT was compared to TT or CT and assessed gait speed, step and stride length, width step, walking distance, cadence, standing ability, walking, running and jumping ability, gross motor function and functional independence in children with CP, have been included. Methodological quality was assessed with the PEDro scale and the pooled effect was calculated with Cohen’s Standardized Mean Difference (SMD) and its 95% Confidence Interval (95% CI). Results: A total of 15 CCTs have been included, providing data from 413 participants, with an averaged methodological quality of 5.73 ± 1.1 points in PEDro. The main findings of this review are that RAGT shows better results than CT in the post-intervention assessment for gait speed (SMD 0.56; 95% CI 0.03 to 1.1), walking distance (SMD 2; 95% CI 0.36 to 3.65) and walking, running and jumping ability (SMD 0.63; 95% CI 0.12 to 1.14). Conclusions: This study shows that the effect of RAGT is superior to CT on gait speed, walking distance and walking, running and jumping ability in post-intervention, although no differences were found between RAGT and TT or CT for the remaining variables. Full article