Search Results (478)

Rehabilitation devices such as actuated lower-limb exoskeletons can provide essential mobility assistance for pediatric patients with gait impairments. Enhancing their control systems under conditions of user variability and dynamic disturbances remains a significant challenge, particularly in active-assist modes. This study presents a human-in-the-loop control architecture for a pediatric lower-limb exoskeleton, combining outer-loop admittance control with robust inner-loop trajectory tracking via a non-singular terminal sliding-mode (NSTSM) controller. Designed for active-assist gait rehabilitation in children aged 8–12 years, the exoskeleton dynamically responds to user interaction forces while ensuring finite-time convergence under system uncertainties. To enhance adaptability, we augment the inner-loop control with a twin delayed deep deterministic policy gradient (TD3) reinforcement learning framework. The actor–critic RL agent tunes NSTSM gains in real-time, enabling personalized model-free adaptation to subject-specific gait dynamics and external disturbances. The numerical simulations show improved trajectory tracking, with RMSE reductions of 27.82% (hip) and 5.43% (knee), and IAE improvements of 40.85% and 10.20%, respectively, over the baseline NSTSM controller. The proposed approach also reduced the peak interaction torques across all the joints, suggesting more compliant and comfortable assistance for users. While minor degradation is observed at the ankle joint, the TD3-NSTSM controller demonstrates improved responsiveness and stability, particularly in high-load joints. This research contributes to advancing pediatric gait rehabilitation using RL-enhanced control, offering improved mobility support and adaptive rehabilitation outcomes. 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

Total Knee Arthroplasty (TKA) is a well-established surgical intervention for the management of end-stage knee osteoarthritis. While the procedure is generally successful, postoperative rehabilitation remains a key determinant of long-term functional outcomes. Traditional rehabilitation protocols, particularly those requiring in-person clinical visits, often encounter limitations in accessibility, patient adherence, and personalization. In response, emerging sensor technologies have introduced innovative solutions to support and enhance recovery following TKA. This review provides a thematically organized synthesis of the current landscape and future directions of sensor-assisted rehabilitation in TKA. It examines four main categories of technologies: wearable sensors (e.g., IMUs, accelerometers, gyroscopes), smart implants, pressure-sensing systems, and mobile health (mHealth) platforms such as ReHub^® and BPMpathway. Evidence from recent randomized controlled trials and systematic reviews demonstrates their effectiveness in tracking mobility, monitoring range of motion (ROM), detecting gait anomalies, and delivering real-time feedback to both patients and clinicians. Despite these advances, several challenges persist, including measurement accuracy in unsupervised environments, the complexity of clinical data integration, and digital literacy gaps among older adults. Nevertheless, the integration of artificial intelligence (AI), predictive analytics, and remote rehabilitation tools is driving a shift toward more adaptive and individualized care models. This paper concludes that sensor-enhanced rehabilitation is no longer a future aspiration but an active transition toward a smarter, more accessible, and patient-centered paradigm in recovery after TKA. Full article

Background: Aquatic therapy (AT), immersion in hot water, and supported standing are frequently used to manage spasticity, contractures, and joint retractions in children with cerebral palsy (CP). Recently, the use of exoskeletons has been offering a new treatment option for severe CP. This study aimed to compare the post-immediate effects of four treatments on spasticity, range of motion, and the heart rate of children with severe CP. Methods: Three children with spastic CP (levels IV and V GMFCS) received a single 30-min session in consecutive weeks of robot-assisted gait training (RAGT), AT, supported standing, and immersion in hot water. Post-immediate assessments included knee flexor spasticity (modified Ashworth scale, MAS, and modified Tardieu scale, MTS); knee range of motion (ROM, in degrees (°)); and heart rate (HR). Results: AT and supported standing induced greater reductions in spasticity based on MAS scores. RAGT demonstrated superior spasticity reduction using MTS and yielded the greatest improvement in popliteal angle (mean increase: 27°). AT and RAGT induced a 14 beats-per-minute change in HR, indicating moderate cardiovascular engagement. Conclusions: RAGT appears particularly effective in improving spasticity and ROM in children with severe CP. Nonetheless, conventional treatments still offer an effective option when addressing spasticity. Full article

This paper looks at and describes the potential of using artificial intelligence in smart environments. Various environments such as houses and residential and commercial buildings are becoming smarter through the use of various technologies, i.e., various sensors, smart devices and elements based on artificial intelligence. These technologies are used, for example, to achieve different levels of security in environments, for personalized comfort and control and for ambient assisted living. We investigated the deep learning approach, and, in this paper, describe its use in this context. Accordingly, we developed four deep learning models, which we describe. These are models for hand gesture recognition, emotion recognition, face recognition and gait recognition. These models are intended for use in smart environments for various tasks. In order to present the possible applications of the models, in this paper, a house is used as an example of a smart environment. The models were developed using the TensorFlow platform together with Keras. Four different datasets were used to train and validate the models. The results are promising and are presented in this paper. Full article

Accurate gait assessment is essential for managing pathological locomotion, especially in elderly patients recovering from hip joint surgeries. Inertial measurement units (IMUs) provide real-time, objective data in clinical settings. This study examined pelvic oscillations in sagittal, frontal, and transverse planes using a wearable IMU system in two groups: Group A (n = 15, osteosynthesis metallica) and Group B (n = 34, arthroplasty), all over age 65. Gait analysis was conducted during assisted and unassisted walking. In the frontal plane, both groups showed statistically significant improvements: Group A from 46.4% to 75.2% (p = 0.001) and Group B from 52.6% to 72.2% (p = 0.001), reflecting enhanced lateral stability. In the transverse plane, Group A improved significantly from 47.7% to 80.2% (p = 0.001), while Group B showed a non-significant increase from 73.0% to 80.5% (p = 0.068). Sagittal plane changes were not statistically significant (Group A: 68.8% to 71.1%, p = 0.313; Group B: 76.4% to 69.1%, p = 0.065). These improvements correspond to better pelvic symmetry and postural control, which are critical for a safe and stable gait. Improvements were more pronounced during unassisted walking, indicating better pelvic control. These results confirm the clinical utility of IMUs in capturing subtle gait asymmetries and monitoring recovery progress. The findings support their use in tailoring rehabilitation strategies, particularly for enhancing frontal and transverse pelvic stability in elderly orthopedic patients. Full article

Cerebral palsy is the leading cause of motor disability in early childhood, with no curative treatment currently available. To mitigate its effects and promote motor rehabilitation, robotic-assisted therapies have emerged as a complement to conventional physiotherapy. In particular, cable-driven exoskeletons offer notable advantages, providing patients with additional mobility and interaction with their environment while preserving motion assistance. Within this context, the Discover2Walk project introduces a modular cable-driven robotic platform designed for early-stage gait rehabilitation. This article presents a novel ankle control module capable of actuating 3 degrees of freedom: 2 translational (in the x and z directions) and 1 rotational (dorsiflexion/plantarflexion). Experimental results confirm the technical feasibility of the approach and its effectiveness in guiding motion within the targeted degrees of freedom. Full article

Background: Lokomat-assisted robotic rehabilitation is increasingly used for gait restoration in patients with spinal cord injury (SCI). However, the objective evaluation of treatment effectiveness through biomechanical parameters and machine learning approaches remains underexplored. Methods: This study analyzed data from 29 SCI patients undergoing Lokomat-based rehabilitation. A dataset of 46 variables including range of motion (L-ROM), joint stiffness (L-STIFF), and muscular force (L-FORCE) was examined using statistical methods (paired t-test, ANOVA, and ordinary least squares regression), clustering techniques (k-means), dimensionality reduction (t-SNE), and anomaly detection (Isolation Forest). Predictive modeling was applied to assess the influence of age, speed, body weight, body weight support, and exercise duration on biomechanical outcomes. Results: No statistically significant asymmetries were found between left and right limb measurements, indicating functional symmetry post-treatment (p > 0.05). Clustering analysis revealed a weak structure among patient groups (Silhouette score ≈ 0.31). Isolation Forest identified minimal anomalies in stiffness data, supporting treatment consistency. Regression models showed that body weight and body weight support significantly influenced joint stiffness (p < 0.01), explaining up to 60% of the variance in outcomes. Conclusions: Lokomat-assisted robotic rehabilitation demonstrates high functional symmetry and biomechanical consistency in SCI patients. Machine learning methods provided meaningful insight into the structure and predictability of outcomes, highlighting the clinical value of weight and support parameters in tailoring recovery protocols. Full article

This review provides a comprehensive analysis of recent advancements in lower limb exoskeleton systems, focusing on applications, control strategies, hardware architecture, sensing modalities, human-robot interaction, evaluation methods, and technical innovations. The study spans systems developed for gait rehabilitation, mobility assistance, terrain adaptation, pediatric use, and industrial support. Applications range from sit-to-stand transitions and post-stroke therapy to balance support and real-world navigation. Control approaches vary from traditional impedance and fuzzy logic models to advanced data-driven frameworks, including reinforcement learning, recurrent neural networks, and digital twin-based optimization. These controllers support personalized and adaptive interaction, enabling real-time intent recognition, torque modulation, and gait phase synchronization across different users and tasks. Hardware platforms include powered multi-degree-of-freedom exoskeletons, passive assistive devices, compliant joint systems, and pediatric-specific configurations. Innovations in actuator design, modular architecture, and lightweight materials support increased usability and energy efficiency. Sensor systems integrate EMG, EEG, IMU, vision, and force feedback, supporting multimodal perception for motion prediction, terrain classification, and user monitoring. Human–robot interaction strategies emphasize safe, intuitive, and cooperative engagement. Controllers are increasingly user-specific, leveraging biosignals and gait metrics to tailor assistance. Evaluation methodologies include simulation, phantom testing, and human–subject trials across clinical and real-world environments, with performance measured through joint tracking accuracy, stability indices, and functional mobility scores. Overall, the review highlights the field’s evolution toward intelligent, adaptable, and user-centered systems, offering promising solutions for rehabilitation, mobility enhancement, and assistive autonomy in diverse populations. Following a detailed review of current developments, strategic recommendations are made to enhance and evolve existing exoskeleton technologies. Full article

Background/Objectives: Robotic-assisted gait training (RAGT) is a promising adjunct to conventional rehabilitation for stroke survivors. However, its additive benefit over standard therapy remains to be fully clarified. This systematic review and meta-analysis evaluated the effectiveness of combining RAGT with conventional rehabilitation in improving gait-related outcomes among individuals with stroke. Methods: We searched PubMed, Embase, CINAHL, and Cochrane CENTRAL through September 2024 for randomized controlled trials (RCTs) comparing combined RAGT and conventional rehabilitation versus conventional rehabilitation alone in adults post-stroke. Data were synthesized using a random-effects model, and subgroup analyses examined effects by intervention duration, stroke chronicity, and robotic system type. Results: Twenty-three RCTs (n = 907) were included. The combined intervention significantly improved gait function (SMD = 0.51, p = 0.001), gait speed (SMD = 0.47, p = 0.010), balance (MD = 4.58, p < 0.001), and ADL performance (SMD = 0.35, p = 0.001). Subgroup analyses revealed that end-effector robotic systems yielded superior outcomes compared to exoskeletons, particularly in subacute stroke patients. The most pronounced benefits were seen in gait velocity and dynamic balance, especially with ≤15 training sessions. Conclusions: Integrating RAGT with conventional rehabilitation enhances motor recovery and functional performance in stroke survivors. End-effector devices appear most effective in subacute phases, supporting individualized RAGT application based on patient and device characteristics. Full article

This study aimed to evaluate how wearable hip exoskeleton assistance affects phase-dependent gait stability in healthy adults using a novel visualization technique known as gait tube analysis. Hip exoskeletons offer significant potential to enhance human locomotion through joint torque augmentation, yet their effects on gait stability across the gait cycle remain underexplored. This study introduces gait tube analysis, a novel method for visualizing center of mass velocity trajectories in three-dimensional state space, to quantify phase-dependent gait stability under hip exoskeleton assistance. We analyzed data from ten healthy adults walking under twelve conditions (ten powered with varying torque magnitude and timing, one passive, and one unassisted), assessing variability via covariance-based ellipsoid volumes. Powered conditions, notably HighLater and HighLatest, significantly increased vertical variability (VT) during early-to-mid stance (10–50% of the gait cycle), with HighLater showing the highest mean ellipsoid volume (99,937 mm³/s³; z = 2.3). Conversely, the passive PowerOff condition exhibited the lowest variability (47,285 mm³/s³; z = –1.7) but higher metabolic cost, highlighting a stability-efficiency trade-off. VT was elevated in 11 of 12 conditions (p ≤ 0.0059), and strong correlations (r ≥ 0.65) between ellipsoid volume and total variability validated the method’s robustness. These findings reveal phase-specific stability challenges and metabolic cost variations induced by exoskeleton assistance, providing a foundation for designing adaptive controllers to balance stability and efficiency in rehabilitation and performance enhancement contexts. Full article

Background/Objectives: This study focuses on the motion planning and control of an active ankle–foot orthosis (AFO) that leverages biomechanical insights to mitigate footdrop, a deficit that prevents safe toe clearance during walking. Methods: To adapt the motion of the device to the user’s walking speed, a geometric model was used, together with real-time measurement of the user’s gait cycle. A geometric speed-adaptive model also scales a trapezoidal ankle-velocity profile in real time using the detected gait cycle. The algorithm was tested at three different walking speeds, with a prototype of the AFO worn by a test subject. Results: At walking speeds of 0.44 and 0.61 m/s, reduced tibialis anterior (TA) muscle activity was confirmed by electromyography (EMG) signal measurement during the stance phase of assisted gait. When the AFO was in assistance mode after toe-off (initial and mid-swing phase), it provided an average of 48% of the estimated required power to make up for the deliberate inactivity of the TA muscle. Conclusions: Kinematic analysis of the motion capture data showed that sufficient foot clearance was achieved at all three speeds of the test. No adverse effects or discomfort were reported during the experiment. Future studies should examine the device in populations with footdrop and include a comprehensive evaluation of safety. Full article

Background: Advanced sensor insoles and motion capture technology can significantly enhance the monitoring of rehabilitation progress for patients with distal tibial fractures. This study leverages the potential of these innovative tools to provide a more comprehensive assessment of a patient’s gait and weight-bearing capacity following surgical intervention, thereby offering the possibility of improved patient outcomes. Methods: A patient who underwent distal medial tibial plating surgery in August 2023 and subsequently required revision surgery due to implant failure, involving plate removal and the insertion of an intramedullary nail in December 2023, was meticulously monitored over a 12-week period. Initial assessments in November 2023 revealed pain upon full weight-bearing without crutches. Following the revision, precise weekly measurements were taken, starting two days after surgery, which instilled confidence in accurately tracking the patient’s progress from initial crutch-assisted walking to full recovery. The monitoring tools included insoles, hand pads for force absorption of the crutches, and a motion capture system. The patient was accompanied throughout all steps of his daily life. Objectives: The study aimed to evaluate the hypothesis that the approximation and formation of a healthy gait curve are decisive tools for monitoring healing. Specifically, it investigated whether cadence, imbalance factors, and ground reaction forces could be significant indicators of healing status and potential disorders. Results: The gait parameters, cadence, factor of imbalance ground reaction forces, and the temporal progression of kinematic parameters significantly correlate with the patient’s recovery trajectory. These metrics enable the early identification of deviations from expected healing patterns, facilitating timely interventions and underscoring the transformative potential of these technologies in patient care. Conclusions: Integrating sensor insoles and motion capture technology offers a promising approach for monitoring the recovery process in patients with distal tibial fractures. This method provides valuable insights into the patient’s healing status, potentially predicting and addressing healing disorders more effectively. Future studies are recommended to validate these findings in a larger cohort and explore the potential integration of these technologies into clinical practice. Full article

This case report examines the impact of robotic-assisted therapy (Lokomat) on functional recovery in a 28-year-old male patient with acute dermatomyositis (DM), an autoimmune inflammatory myopathy causing progressive muscle weakness and disability. The patient underwent 21 sessions of robotic therapy combined with physical therapy, and occupational therapy over seven weeks. Assessments were conducted at baseline, week 10, and week 21 using standardized measures for balance, muscle strength, and functionality. Results demonstrated significant improvements across all domains: balance scores progressed from severe impairment (4/56 Berg, 0/28 Tinetti) to near-normal function (55/56, 24/28, respectively); muscle strength increased from grade 1/5 to 4/5 (MMT-8) in all tested muscle groups; and functionality improved from moderate dependence (59/126 FIM) to complete independence (126/126). The trunk functionality scores showed remarkable recovery from 12/100 to 100/100 (TCT), indicating restored trunk control. Lokomat-assisted therapy combined with conventional rehabilitation effectively improves proximal weakness and postural instability in DM. Robotic therapy enhances motor learning via repetitive movements and reduces therapist workload. Though limited by a single-case design, this study offers preliminary evidence for robotic rehabilitation in DM, previously unexplored. Controlled studies are needed to standardize protocols and validate results in larger cohorts. Advanced technologies show promise for functional recovery in inflammatory myopathies. Full article

Background/Objectives: Total hip arthroplasty (THA) is a widely performed procedure to alleviate pain and improve function in patients with hip disorders. However, leg length discrepancy (LLD) remains a prevalent complication. LLD can cause gait disturbances, back pain, postural imbalance, and patient dissatisfaction, along with significant medico-legal implications. This review examines the evaluation, management, and medico-legal aspects of LLD. Methods: The review analyzed literature on the prevalence, evaluation methods, and management strategies for LLD in THA. Radiographic and clinical assessment tools were considered, alongside factors such as pelvic obliquity and pre-existing conditions. The importance of preoperative planning, intraoperative techniques (including computer-assisted methods), and comprehensive documentation was evaluated to address both clinical and legal challenges. Results: The review shows that leg length discrepancy (LLD) following total hip arthroplasty (THA) occurs in 3% to 30% of cases, with mean values ranging from 3 to 17 mm. LLD may result from anatomical or procedural factors, and effective evaluation requires both radiographic imaging and clinical assessment. Preoperative planning plays a critical role in accurately assessing anatomical parameters and selecting appropriate prosthetic components to preserve or restore limb length symmetry. Advanced intraoperative techniques, including computer-assisted surgery, help reduce LLD incidence. While some complications may be unavoidable, proper documentation and patient communication, particularly regarding informed consent, are essential to mitigate medico-legal risks Conclusions: LLD after THA requires a multidimensional approach incorporating clinical, radiological, biomechanical, and legal considerations. Effective preoperative and intraoperative strategies, combined with robust communication and documentation, are essential to minimize LLD and its associated risks. A focus on precision and patient-centered care can improve outcomes and reduce litigation. Full article