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Background and Objectives: While body weight support (BWS) intonation is vital during conventional gait training of neurologically challenged subjects, it is important to evaluate its effect during robot assisted gait training. In the present research we have studied the effect of BWS intonation on muscle activities during robotic gait training using dynamic simulations. Methods: Two dimensional (2-D) musculoskeletal model of human gait was developed conjointly with another 2-D model of a robotic orthosis capable of actuating hip, knee and ankle joints simultaneously. The musculoskeletal model consists of eight major muscle groups namely; soleus (SOL), gastrocnemius (GAS), tibialis anterior (TA), hamstrings (HAM), vasti (VAS), gluteus maximus (GLU), uniarticular hip flexors (iliopsoas, IP), and Rectus Femoris (RF). BWS was provided at levels of 0, 20, 40 and 60% during the simulations. In order to obtain a feasible set of muscle activities during subsequent gait cycles, an inverse dynamics algorithm along with a quadratic minimization algorithm was implemented. Results: The dynamic parameters of the robot assisted human gait such as joint angle trajectories, ground contact force (GCF), human limb joint torques and robot induced torques at different levels of BWS were derived. The patterns of muscle activities at variable BWS were derived and analysed. For most part of the gait cycle (GC) the muscle activation patterns are quite similar for all levels of BWS as is apparent from the mean of muscle activities for the complete GC. Conclusions: Effect of BWS variation during robot assisted gait on muscle activities was studied by developing dynamic simulation. It is expected that the proposed dynamic simulation approach will provide important inferences and information about the muscle function variations consequent upon a change in BWS during robot assisted gait. This information shall be quite important while investigating the influence of BWS intonation on neuromuscular parameters of interest during robotic gait training. [ABSTRACT FROM AUTHOR]

It is a common hypothesis in the field of robot-assisted gait rehabilitation that the active involvement and voluntary participation of neurologically impaired subjects in the robotic gait training process may enhance the outcomes of such therapy. An adaptive seamless assist-as-needed (AAN) control scheme was developed for the robotic gait training. The AAN control scheme learns in real time the disability level of human subjects based on the trajectory tracking errors and adapts the robotic assistance accordingly. The overall AAN control architecture works on the basis of a robust adaptive control approach. The performance of seamless AAN control scheme was evaluated during treadmill training with a compliant robotic orthosis having six degrees of freedom. Two experiments, namely, trajectory following experiment and the AAN experiment were carried out to evaluate the performance of seamless adaptive AAN control scheme. It was found that the robotic orthosis is capable of guiding the subjects’ limbs on reference trajectories during the trajectory following experiment. Also, a variation in robotic assistance was recorded during the AAN experiment based on the voluntary participation of human subjects. This work is an advance on the current state of the art in the compliant actuation of robotic gait rehabilitation orthoses in the context of seamless AAN gait training. [ABSTRACT FROM AUTHOR]

In severely affected stroke survivors, cortico-muscular control is disturbed and volitional upper limb movements often absent. Mental rehearsal of the impaired movement in conjunction with sensory feedback provision are suggested as promising rehabilitation exercises. Knowledge about the underlying neural processes, however, remains vague. In male and female chronic stroke patients with hand paralysis, a brain-computer interface controlled a robotic orthosis and turned sensorimotor β-band desynchronization during motor imagery (MI) of finger extension into contingent hand opening. Healthy control subjects performed the same task and received the same proprioceptive feedback with a robotic orthosis or visual feedback only. Only when proprioceptive feedback was provided, cortico-muscular coherence (CMC) increased with a predominant information flow from the sensorimotor cortex to the finger extensors. This effect (1) was specific to the β frequency band, (2) transferred to a motor task (MT), (3) was proportional to subsequent corticospinal excitability (CSE) and correlated with behavioral changes in the (4) healthy and (5) poststroke condition; notably, MIrelated enhancement of β-band CMC in the ipsilesional premotor cortex correlated with motor improvements after the intervention. In the healthy and injured human nervous system, synchronized activation of motor-related cortical and spinal neural pools facilitates, in accordance with the communication-through-coherence hypothesis, cortico-spinal communication and may, thereby, be therapeutically relevant for functional restoration after stroke, when voluntary movements are no longer possible. [ABSTRACT FROM AUTHOR]

This study developed a robotic orthosis capable of detecting the intention of a wearer to move their fingers, thereafter augmenting their muscle force. This was with the aim of producing a device that can be used in post-stroke hand rehabilitation. The design of the orthosis was based on an existing design, which was modified using BLENDER release 2.78 and printed with ABS plastic. An actuator was mounted at the rear end of the orthosis, to provide actuation to perform full range flexion and extension motion for digits. Force sensors were embedded at the fingertips of the orthosis to detect minute finger movements. For severe cases where stroke survivors are incapable of little finger movements, the study employed a brain-computer interface to detect the intent to move. The robotic orthosis achieved an accuracy of 64.1% and 62% in detecting unclench and clench activities respectively and actuating the orthosis digits in response. The results revealed that the design presented here can help provide effective hand rehabilitation. The study concluded that the design incorporated with BCI systems is capable of performing hand rehabilitation in a clinical setting as it obtains some level of accuracy in detecting patient intent to move and actuating in response. This design is low cost, and hence will lessen the economic burden for stroke survivors in a poor-resource country. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for designing a robotic orthosis controller considering physical human-robot interaction (pHRI). Computer simulation for this human-robot system can be advantageous in terms of time and cost due to the laborious nature of designing a robot controller that effectively assists humans with the appropriate magnitude and phase. Therefore, we propose a two-stage policy training framework based on deep reinforcement learning (deep RL) to design a robot controller using human-robot dynamic simulation. In Stage 1, the optimal policy of generating human gaits is obtained from deep RL-based imitation learning on a healthy subject model using the musculoskeletal simulation in OpenSim-RL. In Stage 2, human models in which the right soleus muscle is weakened to a certain severity are created by modifying the human model obtained from Stage 1. A robotic orthosis is then attached to the right ankle of these models. The orthosis policy that assists walking with optimal torque is then trained on these models. Here, the elastic foundation model is used to predict the pHRI in the coupling part between the human and robotic orthosis. Comparative analysis of kinematic and kinetic simulation results with the experimental data shows that the derived human musculoskeletal model imitates a human walking. It also shows that the robotic orthosis policy obtained from two-stage policy training can assist the weakened soleus muscle. The proposed approach was validated by applying the learned policy to ankle orthosis, conducting a gait experiment, and comparing it with the simulation results. [ABSTRACT FROM AUTHOR]

Rehabilitation and mobility assistance using robotic orthosis or exoskeletons have shown potential in aiding those with musculoskeletal disorders. Artificial muscles are the main component used to drive robotics and bio-assistive devices. However, current fabrication methods to produce artificial muscles are technically challenging and laborious for medical staff at clinics and hospitals. This study aims to investigate a printhead system for material extrusion of helical polymer artificial muscles. In the proposed system, an internal fluted mandrel within the printhead and a temperature control module were used simultaneously to solidify and stereotype polymer filaments prior to extrusion from the printhead with a helical shape. Numerical simulation was applied to determine the optimal printhead design, as well as analyze the coupling effects and sensitivity of the printhead geometries on artificial muscle fabrication. Based on the simulation analysis, the printhead system was designed, fabricated, and operated to extrude helical filaments using polylactic acid. The diameter, thickness, and pitch of the extruded filaments were compared to the corresponding geometries of the mandrel to validate the fabrication accuracy. Finally, a printed filament was programmed and actuated to test its functionality as a helical artificial muscle. The proposed printhead system not only allows for the stationary extrusion of helical artificial muscles but is also compatible with commercial 3D printers to freeform print helical artificial muscle groups in the future. [ABSTRACT FROM AUTHOR]

Introduction/Background Gait training is one of the main objectives in rehabilitation of motor incomplete spinal cord injury (SCI). There are different modalities of locomotion training, being the robotic orthosis among them, and offering until now, positive outcomes. However there is still a lack of evidence of the optimal training characteristics. Objective To determine the effect of two different training programs with robotic gait orthosis for patients with chronic motor incomplete SCI. Material and method Study design: randomized, blinded to the observer, clinical trial. Patients from the National Institute of Rehabilitation (INR) with motor incomplete SCI, with at least 6 months of evolution and who were able to walk, were eligible. Patients were randomly assigned to either one of the two different training groups: 30 minutes or 60 minutes training group. Both groups received a training period of six weeks, five days a week. Assessments of gait pattern analysis with the GaitRite instrument, functional assessment with Spinal Cord Independence measure (SCIM), walking index for spinal cord injury (WISCI) and quality of life with life satisfaction questionnaire (Lisat-9); repeating such evaluations in a 6 and 12 months follow-up. Results In total, 12 participants were studied. After 30 training sessions with the robotic orthosis, both groups had significant improvements in gait as well as in SCIM, LISAT-9 and WISCI. No significant differences between groups were found. Conclusion Robotic orthosis gait training has a positive effect improving gait pattern in incomplete SCI. Until now, there are no significant differences between a 30 minutes and a 60 minutes-training program. [ABSTRACT FROM AUTHOR]

Robotic devices are gaining popularity for the physical rehabilitation of stroke survivors. Transition of these robotic systems from research labs to the clinical setting has been successful, however, providing robot-assisted rehabilitation in home settings remains to be achieved. In addition to ensure safety to the users, other important issues that need to be addressed are the real time monitoring of the installed instruments, remote supervision by a therapist, optimal data transmission and processing. The goal of this paper is to advance the current state of robot-assisted in-home rehabilitation. A state-of-the-art approach to implement a novel paradigm for home-based training of stroke survivors in the context of an upper limb rehabilitation robot system is presented in this paper. First, a cost effective and easy-to-wear upper limb robotic orthosis for home settings is introduced. Then, a framework of the internet of robotics things (IoRT) is discussed together with its implementation. Experimental results are included from a proof-of-concept study demonstrating that the means of absolute errors in predicting wrist, elbow and shoulder angles are 0.89180,2.67530 and 8.02580, respectively. These experimental results demonstrate the feasibility of a safe home-based training paradigm for stroke survivors. The proposed framework will help overcome the technological barriers, being relevant for IT experts in health-related domains and pave the way to setting up a telerehabilitation system increasing implementation of home-based robotic rehabilitation. The proposed novel framework includes: • A low-cost and easy to wear upper limb robotic orthosis which is suitable for use at home. • A paradigm of IoRT which is used in conjunction with the robotic orthosis for home-based rehabilitation. • A machine learning-based protocol which combines and analyse the data from robot sensors for efficient and quick decision making.

Background: Transfemoral amputation is a serious intervention that alters the locomotion pattern, leading to secondary disorders and reduced quality of life. The outcomes of current gait rehabilitation for TFAs seem to be highly dependent on factors such as the duration and intensity of the treatment and the age or etiology of the patient. Although the use of robotic assistance for prosthetic gait rehabilitation has been limited, robotic technologies have demonstrated positive rehabilitative effects for other mobility disorders and may thus offer a promising solution for the restoration of healthy gait in TFAs. This study therefore explored the feasibility of using a bilateral powered hip orthosis (APO) to train the gait of community-ambulating TFAs and the effects on their walking abilities.Methods: Seven participants (46-71 years old with different mobility levels) were included in the study and assigned to one of two groups (namely Symmetry and Speed groups) according to their prosthesis type, mobility level, and prior experience with the exoskeleton. Each participant engaged in a maximum of 12 sessions, divided into one Enrollment session, one Tuning session, two Assessment sessions (conducted before and after the training program), and eight Training sessions, each consisting of 20 minutes of robotically assisted overground walking combined with additional tasks. The two groups were assisted by different torque-phase profiles, aiming at improving symmetry for the Symmetry group and at maximizing the net power transferred by the APO for the Speed group. During the Assessment sessions, participants performed two 6-min walking tests (6mWTs), one with (Exo) and one without (NoExo) the exoskeleton, at either maximal (Symmetry group) or self-selected (Speed group) speed. Spatio-temporal gait parameters were recorded by commercial measurement equipment as well as by the APO sensors, and metabolic efficiency was estimated via the Cost of Transport (CoT). Additionally, kinetic and kinematic data were recorded before and after treatment in the NoExo condition.Results: The one-month training protocol was found to be a feasible strategy to train TFAs, as all participants smoothly completed the clinical protocol with no relevant mechanical failures of the APO. The walking performance of participants improved after the training. During the 6mWT in NoExo, participants in the Symmetry and Speed groups respectively walked 17.4% and 11.7% farther and increased walking speed by 13.7% and 17.9%, with improved temporal and spatial symmetry for the former group and decreased energetic expenditure for the latter. Gait analysis showed that ankle power, step width, and hip kinematics were modified towards healthy reference levels in both groups. In the Exo condition metabolic efficiency was reduced by 3% for the Symmetry group and more than 20% for the Speed group.Conclusions: This study presents the first pilot study to apply a wearable robotic orthosis (APO) to assist TFAs in an overground gait rehabilitation program. The proposed APO-assisted training program was demonstrated as a feasible strategy to train TFAs in a rehabilitation setting. Subjects improved their walking abilities, although further studies are required to evaluate the effectiveness of the APO compared to other gait interventions. Future protocols will include a lighter version of the APO along with optimized assistive strategies. [ABSTRACT FROM AUTHOR]

Human hands and fingers are of significant importance in people's capacity to perform daily tasks (touching, feeling, holding, gripping, writing). However, about 1.5 million people around the world are suffering from injuries, muscle and neurological disorders, a loss of hand function, or a few fingers due to stroke. This paper focuses on newly developed finger orthotics, which is thin, adaptable to the length of each finger and low energy costs. The aim of the study is to design and control a new robotic orthosis using for daily rehabilitation therapy. Kinematic and dynamic analysis of orthosis was calculated and the joint regulation of orthosis was obtained. The Lagrange method was used to obtain dynamics, and the Denavit–Hartenberg (D–H) method was used for kinematic analysis of hand. In order to understand its behavior, the robotic finger orthotics model was simulated in MatLab/Simulink. The simulation results show that the efficiency and robustness of proportional integral derivative (PID) controller are appropriate for the use of robotic finger orthotics. [ABSTRACT FROM AUTHOR]

BACKGROUND: Due to physical and psychosocial issues associated with long-term sitting in a wheelchair, devising new ways to facilitate upright mobility is a key issue in rehabilitation medicine. Wearable Power-Assist Locomotor (WPAL) is a motorized orthosis and is developed for providing independent and comfortable walking for paraplegic patients. METHODS: The WPAL consists of a wearable robotic orthosis and custom walker. To facilitate alternate usage with a wheelchair, the wearable robotic orthosis is based on a medial system with motors located at the bilateral hip, knee and ankle joints to reduce the increase in heart rate during gait. The gait parameters include stride length, toe clearance height, swing time, double support time, etc. (gait speed: up to 1.3 km/h). Independent gait with the walker can be learned through a five-stage gait exercise sequence. The first two stages are stepping and gait exercises with parallel bars. The third stage is gait exercise on treadmill. The subsequent two stages are gait exercise with walker. RESULTS: Seven motor-complete paraplegic patients (spinal cord functional levels: T6-T12) participated. Through a series of exercises, all users achieved independent gait on a level floor (Functional Ambulation Categories: 4). The mean duration and distance of consecutively walking were 14.1 ± 11.4 minutes and 165.6 ± 202.6 m, respectively. The most competent user was able to walk continuously for as long as 40 minutes and 640 m whereas only for 6 minutes and 107 m with a conventional orthosis. CONCLUSIONS: These results suggest that WPAL might be useful device for supporting upright walking in persons with paraplegia. [ABSTRACT FROM AUTHOR]

We studied the performance of a robotic orthosis designed to assist the paretic hand after stroke. It is wearable and fully user-controlled, serving two possible roles: as a therapeutic tool that facilitates device-mediated hand exercises to recover neuromuscular function or as an assistive device for use in everyday activities to aid functional use of the hand. We present the clinical outcomes of a pilot study designed as a feasibility test for these hypotheses. 11 chronic stroke (>2 years) patients with moderate muscle tone (Modified Ashworth Scale $\leq 2$ in upper extremity) engaged in a month-long training protocol using the orthosis. Individuals were evaluated using standardized outcome measures, both with and without orthosis assistance. Fugl-Meyer post intervention scores without robotic assistance showed improvement focused specifically at the distal joints of the upper limb, suggesting the use of the orthosis as a rehabilitative device for the hand. Action Research Arm Test scores post intervention with robotic assistance showed that the device may serve an assistive role in grasping tasks. These results highlight the potential for wearable and user-driven robotic hand orthoses to extend the use and training of the affected upper limb after stroke. [ABSTRACT FROM AUTHOR]

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Featured Application: This study can be used as a reference for works that develop active orthoses or prostheses that use artificial tendons to move the fingers, helping in the process of defining these tendons. This study aims to present the design, selection and testing of commercial ropes (artificial tendons) used on robotic orthosis to perform the hand movements for stroke individuals over upper limb rehabilitation. It was determined the load applied in the rope would through direct measurements performed on four individuals after stroke using a bulb dynamometer. A tensile strength test was performed using eight commercial ropes in order to evaluate the maximum breaking force and select the most suitable to be used in this application. Finally, a pilot test was performed with a user of the device to ratify the effectiveness of the rope. The load on the cable was 12.38 kgf (121.4 N) in the stroke-affected hand, which is the maximum tensile force that the rope must to supports. Paragliding rope (DuPont™ Kevlar ® ) supporting a load of 250 N at a strain of 37 mm was selected. The clinical test proved the effectiveness of the rope, supporting the requested efforts, without presenting permanent deformation, effectively performing the participant's finger opening. [ABSTRACT FROM AUTHOR]

Stroke, amyotrophic lateral sclerosis (ALS), and Parkinson's disease are some of the conditions that can lead to neuromotor disabilities requiring rehabilitation. To address the socio-economic burden that is amplified by the rapidly increasing elderly population, traditional rehabilitation techniques have recently been complemented by technological advancements, particularly Robot-Assisted Therapy (RAT). RAT enhances motor learning by improving both accuracy and consistency. This study proposes an innovative rehabilitation system that combines serious gaming and augmented reality (AR) with the LegUp parallel robot, developed for the spatial rehabilitation of the hip, knee, and ankle in bed-ridden patients. The system aims to improve patient outcomes and actively involve patients in their therapy. Electro-goniometers and a HoloLens 2 device are used to provide immediate feedback about the position of the patient's joints, forming the basis of an interactive game in which the patient moves their leg to reach various targets. Two game modes were developed, each targeting different aspects of neuromotor rehabilitation, such as coordination, strength, and flexibility. Preliminary findings suggest that combining RAT with augmented reality-based serious gaming can increase patient motivation and engagement. Furthermore, the personalized and interactive nature of the therapy holds the potential to improve rehabilitation outcomes by fostering sustained engagement and effort. [ABSTRACT FROM AUTHOR]

Background: Treadmill based Robotic-Assisted Gait Training (t-RAGT) provides for automated locomotor training to help the patient achieve a physiological gait pattern, reducing the physical effort required by therapist. By introducing the robot as a third agent to the traditional one-to-one physiotherapist-patient (Pht-Pt) relationship, the therapist might not be fully aware of the patient's motor performance. This gap has been bridged by the integration in rehabilitation robots of a visual FeedBack (FB) that informs about patient's performance. Despite the recognized importance of FB in t-RAGT, the optimal role of the therapist in the complex patient-robot interaction is still unclear. This study aimed to describe whether the type of FB combined with different modalities of Pht's interaction toward Pt would affect the patients' visual attention and emotional engagement during t-RAGT. Methods: Ten individuals with incomplete Spinal Cord Injury (C or D ASIA Impairment Scale level) were assessed using eye-tracking (ET) and high-density EEG during seven t-RAGT sessions with Lokomat where (i) three types of visual FB (chart, emoticon and game) and (ii) three levels of Pht-Pt interaction (low, medium and high) were randomly combined. ET metrics (fixations and saccades) were extracted for each of the three defined areas of interest (AoI) (monitor, Pht and surrounding) and compared among the different experimental conditions (FB, Pht-Pt interaction level). The EEG spectral activations in theta and alpha bands were reconstructed for each FB type applying Welch periodogram to data localised in the whole grey matter volume using sLORETA. Results: We found an effect of FB type factor on all the ET metrics computed in the three AoIs while the factor Pht-Pt interaction level also combined with FB type showed an effect only on the ET metrics calculated in Pht and surrounding AoIs. Neural activation in brain regions crucial for social cognition resulted for high Pht-Pt interaction level, while activation of the insula was found during low interaction, independently on the FB used. Conclusions: The type of FB and the way in which Pht supports the patients both have a strong impact on patients' engagement and should be considered in the design of a t-RAGT-based rehabilitation session. [ABSTRACT FROM AUTHOR]

To address the tracking problem of the hybrid‐driven underwater legged robot, a control strategy is proposed that decomposes the whole tracking control system into two subsystems: body‐level and actuator‐level. The body‐level subsystem uses a central pattern generator (CPG)‐based controller to plan suitable gaits to meet the required heading and the forward velocity, crucial for accurate tracking in underwater environments. The actuators‐level subsystem employs a cooperative approach between the C‐shaped legs and thrusters of the robot. To execute the intended gait while adhering to actuation constraints and the no‐slip requirement, the torques of the legs are calculated by a model predictive control and feedback compensation (MPCF)‐based controller. Simultaneously, the calculation of the thrusters concerns four aspects to keep the legs attached to the ground and maintain the stable locomotion of the robot. Simulations on the ROS‐Gazebo platform verify the mobility of the robot and demonstrate the effectiveness of the proposed CPG‐MPCF strategy. [ABSTRACT FROM AUTHOR]

This study aimed to investigate if voluntary participation in robot-assisted gait training leads to more concentrated muscle activity patterns and clinical measure improvements. A single-participant research design study was conducted with a gradual reduction in robotic assistance during robot-assisted gait training. A child with cerebral palsy participated in 20 robot-assisted gait training sessions and two assessment sessions across 99 days. The assistive force of the Lokomat gradually reduced during repeated training. The effects of reduced assistive force on muscle activity patterns were quantitatively analyzed using a clustering algorithm and electromyography. Improvements in overall gait quality and muscle strength were measured after robot-assisted gait training. The results also showed that the number of clustered representative patterns doubled and muscle activation patterns increased when the assistance decreased by 20%, whereas full robot assistance might have hindered active participation. Since assistive force modulation can be a key in robotic rehabilitation, the proposed protocol, involving gradual assistive force reduction, demonstrates promising efficacy and allows for in-depth analysis. Therefore, further randomized clinical trials based on this study can be possible for children with cerebral palsy. [ABSTRACT FROM AUTHOR]

This paper focuses on the development and position control of a robotic system specifically designed for passive rehabilitation. The system is a two-degree-of-freedom robot, dedicated to elbow and a wrist joints. The objective of this research is to create a robotic rehabilitation emulation test that allows therapists to implement their therapeutic programs smoothly and efficiently while minimizing any excessive movements or overshooting. The real-time experiments were conducted to compare the performances of four controllers: model predictive controller (MPC), proportional–integral (PI) controller, RST controller, and constrained MPC (CMPC). Sinusoidal and filtered trajectories were studied to determine the optimal controller for energy efficiency. The obtained results demonstrate that the embedded MPC outperforms the other two controllers. The constrained model predictive control design is employed to address the stringent constraints of the robot. Using a rapid quadratic programming solver based on the Hildreth method ensures compliance with the short real-time implementation sampling time. This approach achieves reduced computational costs while balancing control effort against closed-loop performance. [ABSTRACT FROM AUTHOR]

Background: Gait disturbances in children with cerebral palsy can increase the hindrance caused by loss of independence and social engagement. The Lokomat, developed by Hocoma, shows promise as a supplementary tool for gait rehabilitation. This study investigates the impact of Lokomat training on gait parameters and trends observed during training. Methods: A total of 26 children (13 male individuals) with a diagnosis of cerebral palsy (CP), aged 4 to 23 years, were enrolled in the study. Patients participated in a standard comprehensive rehabilitation program with additional Lokomat training sessions. Gait function was assessed using the Timed Up and Go Test (TUG) and the 10 m walking test (10mWT) at the beginning and end of the rehabilitation period. Changes in Lokomat parameters (step number, session duration, speed, body weight support, and guidance force) were also analysed. Results: The median duration of the 10mWT and TUG significantly decreased across the groups after the treatment program. The highest increases were observed for the number of steps taken. Across the entire cohort, the linear trend curves for distance and number of steps exhibited near-perpendicular alignment with the horizontal axis, suggesting significant improvement in these parameters. A consistent trend was noted for speed, with the trend line aligned parallel with the horizontal axis. Decreasing trends were observed for body weight support and guidance force. Conclusions: Therapy with the Lokomat functioning as the active gait orthosis can be used as a form of support to the standard rehabilitation protocol for patients with CP. [ABSTRACT FROM AUTHOR]

Study Design: Bibliometric analysis. Objective: The study aims to comprehensively assess the literature related to gait rehabilitation for individuals with spinal cord injury (SCI) to identify significant contributors, and to explore the collaborations and emerging themes in the field. Methods: Original and review articles in English using relevant keywords were searched in the Clarivate Web of Science database. The data from the selected articles were imported into R software. Bibliometric indicators were assessed to determine author contributions, country affiliations, journal sources, and thematic trends. Results: A total of 1313 relevant articles were identified. The USA, followed by Canada and Switzerland were the most prolific countries contributing to gait rehabilitation research in SCI. The most relevant journals were Spinal Cord, Archives of Physical Medicine and Rehabilitation, Journal of Spinal Cord Medicine, Journal of NeuroEngineering, and Journal of Neurotrauma. The highest contributions came from Northwestern University, the University of Miami, and the University of Alberta. The analysis revealed an increase in research interest in gait rehabilitation after 2000, with a focus on interdisciplinary approaches and emerging technologies like robotics, exoskeletons, and neuromodulation. Conclusion: The analysis demonstrates the importance of collaborative and interdisciplinary research in gait rehabilitation. The results indicate a shift in research focus from traditional methods to the integration of technology. The impact of publications from the USA and Europe is a notable finding. The study highlights the growth of articles related to technology-driven approaches and understanding neuroplasticity in gait rehabilitation. [ABSTRACT FROM AUTHOR]

Research has shown that rehabilitation lower limb exoskeletons (RLLEs) are effective tools for improving recovery or regaining lower limb function. This device interacts with the limbs of patients. Thus, actuators and power transmission mechanisms are the key factors in determining smooth human‒machine interaction and comfort in physical therapy activities. A multitude of distinct technologies have been proposed. However, we questioned which consideration point in actuator selection and power transmission mechanisms are used for RLLE. A review of the technical characteristics and status of advanced RLLE designs is discussed. We review actuator selection for RLLE devices. Furthermore, the power transmission mechanisms over the years within each of the RLLE devices are presented. The development issues and possible research directions related to actuators and power transmission mechanisms are provided. Most RLLEs are still in the research phase, and only a few have been commercialized. The aim of this paper is to provide researchers with useful information for investigating technological progress and highlight the latest technological choices in RLLE development., (© 2024 the author(s), published by De Gruyter, Berlin/Boston.)

This paper presents a novel approach for designing a robotic orthosis controller considering physical human-robot interaction (pHRI). Computer simulation for this human-robot system can be advantageous in terms of time and cost due to the laborious nature of designing a robot controller that effectively assists humans with the appropriate magnitude and phase. Therefore, we propose a two-stage policy training framework based on deep reinforcement learning (deep RL) to design a robot controller using human-robot dynamic simulation. In Stage 1, the optimal policy of generating human gaits is obtained from deep RL-based imitation learning on a healthy subject model using the musculoskeletal simulation in OpenSim-RL. In Stage 2, human models in which the right soleus muscle is weakened to a certain severity are created by modifying the human model obtained from Stage 1. A robotic orthosis is then attached to the right ankle of these models. The orthosis policy that assists walking with optimal torque is then trained on these models. Here, the elastic foundation model is used to predict the pHRI in the coupling part between the human and robotic orthosis. Comparative analysis of kinematic and kinetic simulation results with the experimental data shows that the derived human musculoskeletal model imitates a human walking. It also shows that the robotic orthosis policy obtained from two-stage policy training can assist the weakened soleus muscle. The proposed approach was validated by applying the learned policy to ankle orthosis, conducting a gait experiment, and comparing it with the simulation results.

Standard brain stimulation protocols modify human motor cortex excitability by modulating the gain of the activated corticospinal pathways. However, the restoration of motor function following lesions of the corticospinal tract requires also the recruitment of additional neurons to increase the net corticospinal output. For this purpose, we investigated a novel protocol based on brain state- dependent paired associative stimulation. Motor imagery (MI)-related electroencephalography was recorded in healthy males and females for brain state-dependent control of both cortical and peripheral stimulation in a brain-machine interface environment. State-dependency was investigated with concurrent, delayed, and independent stimulation relative to the Ml task. Specifically, sensorimotor event-related desynchronization (ERD) in the jU-band (16 -22 Hz) triggered peripheral stimulation through passive hand opening by a robotic orthosis and transcranial magnetic stimulation to the respective cortical motor representation, either synchronously or subsequently. These MI-related paradigms were compared with paired cortical and peripheral input applied independent of the brain state. Cortical stimulation resulted in a significant increase in corticospinal excitability only when applied brain state-dependently and synchronously to peripheral input. These gains were resistant to a depotentiation task, revealed a nonlinear evolution of plasticity, and were mediated via the recruitment of additional corticospinal neurons rather than via synchronization of neuronal firing. Recruitment of additional corticospinal pathways may be achieved when cortical and peripheral inputs are applied concurrently, and during J3-ERD. These findings resemble a gating mechanism and are potentially important for developing closed-loop brain stimulation for the treatment of hand paralysis following lesions of the corticospinal tract. [ABSTRACT FROM AUTHOR]

Introduction: Soft robotics play an increasing role in the development of exosuits that assist, and in some cases enhance human motion. While most existing efforts have focused on the adult population, devices targeting infants are on the rise. This work investigated how different configurations pertaining to fabric-based pneumatic shoulder and elbow actuator embedding on the passive substrate of an exosuit for pediatric upper extremity motion assistance can affect key performance metrics. Methods: The configurations varied based on actuator anchoring points onto the substrate and the type of fabric used to fabricate the enclosures housing the actuators. Shoulder adduction/abduction and elbow flexion/extension were treated separately. Two different variants (for each case) of similar but distinct actuators were considered. The employed metrics were grouped into two categories; reachable workspace, which includes joint range of motion and end-effector path length; and motion smoothness, which includes end-effector path straightness index and jerk. The former category aimed to capture first-order terms (i.e., rotations and displacements) that capture overall gross motion, while the latter category aimed to shed light on differential terms that correlate with the quality of the attained motion. Extensive experimentation was conducted for each individual considered configuration, and statistical analyses were used to establish distinctive strengths, weaknesses, and trade-offs among those configurations. Results: The main findings from experiments confirm that the performance of the actuators can be significantly impacted by variations in the anchoring and fabric properties of the enclosures while establishing interesting trade-offs. Specifically, the most appropriate anchoring point was not necessarily the same for all actuator variants. In addition, highly stretchable fabrics not only maintained but even enhanced actuator capabilities, in comparison to the less stretchable materials which turned out to hinder actuator performance. Conclusion: The established trade-offs can serve as guiding principles for other researchers and practitioners developing upper extremity exosuits. [ABSTRACT FROM AUTHOR]

This paper proposes a deep generative model-based framework for synthesizing four-bar linkage mechanisms that satisfy specified kinematic and quasi-static conditions. We define two objective functions for crank-rocker mechanisms using kinematic workspaces and geometric configurations. Our approach utilizes a conditional generative adversarial network (cGAN) modified for mechanism synthesis, which learns the relationship between mechanism requirements and linkage lengths. The results demonstrate that the proposed model successfully generates multiple distinct mechanisms meeting specific kinematic and quasi-static requirements. We compare our cGAN approach to traditional optimization methods and other deep learning-based generative models. Our method offers several advantages over traditional design approaches, enabling efficient generation of diverse yet feasible design candidates while exploring a large design space. By considering both kinematic and quasi-static requirements, the proposed model can produce more effective mechanisms for real-world applications. This makes it a promising tool for linkage mechanism design, offering designers a way to efficiently generate multiple viable design options that satisfy key performance criteria. [ABSTRACT FROM AUTHOR]

Background: Immersive virtual reality has the potential to motivate and challenge patients who need and want to relearn movements in the process of neurorehabilitation. Objective: The aim of this study was to evaluate the feasibility and user acceptance of an innovative immersive virtual reality system (head-mounted display) used in combination with robot-assisted gait training in subjects suffering from neurological diseases. Methods: Fifteen participants suffering from cerebrovascular accident or spinal cord injury completed a single session of immersive virtual reality using a head-mounted display during a Lokomat® gait session. Training parameters and safety indicators were collected, and acceptance was investigated among participants and therapists. Results: The results suggest that an immersive virtual reality system is feasible in terms of safety and tolerance. Furthermore, the very positive overall acceptance of the system suggests that it has the potential to be included in a robot-assisted gait training session using Lokomat®. Conclusion: Overall, this study demonstrates that a fully immersive virtual reality system based on a head-mounted display is both feasible and well received by cerebrovascular accident and spinal cord injury patients and their therapists during robot-assisted gait training. This study suggests that such a virtual reality system could be a viable alternative to the screen-based training games currently used in neurorehabilitation. It may be especially suitable for enhancing patient motivation and adherence to training, particularly if the application is enjoyable and not mentally taxing. [ABSTRACT FROM AUTHOR]

Neurological disorders, such as Parkinson's disease (PD), multiple sclerosis (MS), cerebral palsy (CP) and stroke are well-known causes of gait and balance alterations. Innovative devices (i.e., robotics) are often used to promote motor recovery. As an alternative, anti-gravity treadmills, which were developed by NASA, allow early mobilization, walking with less effort to reduce gait energy costs and fatigue. A systematic search, according to PRISMA guidelines, was conducted for all peer-reviewed articles published from January 2010 through September 2023, using the following databases: PubMed, Scopus, PEDro and IEEE Xplore. After an accurate screening, we selected only 16 articles (e.g., 5 RCTs, 2 clinical trials, 7 pilot studies, 1 prospective study and 1 exploratory study). The evidence collected in this systematic review reported promising results in the field of anti-gravity technology for neurological patients, in terms of improvement in gait and balance outcomes. However, we are not able to provide any clinical recommendation about the dose and parameters of anti-gravity treadmill training, because of the lack of robust high-quality RCT studies and large samples. Registration number CRD42023459665. [ABSTRACT FROM AUTHOR]

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Relearning to walk requires progressive training in real scenarios—overground—along with assistance in basic tasks, such as balancing. In addition, user ability must be maximized through compliant robotic assistance as needed. Despite decades of research, gait rehabilitation robotic devices yield controversial results. This article presents the conceptual design of a novel walking assistance and rehabilitation robot, the NIMBLE robot, aimed at providing ambulatory, bodyweight-supported gait training, assisting the user's center of mass trajectory to aid weight transfer and dynamic balance during walking. NIMBLE consists of a robotic mobile frame, a partial bodyweight support (PBWS) system, an ambulatory lower-limb exoskeleton (Exo-H3) and a cable-driven pelvis-assisting robot. Designed as a modular structure, it differentiates hierarchical communication levels through a Robot Operating System (ROS) 2 network. We present the mechatronic design and experimental results assessing the impact of the mechatronic coupling between the robotic modules on the walking kinematics and the frame movement control performance. The robotic frame hardly affects the walking kinematics up to 2 degrees in both the sagittal and frontal planes, making it feasible for lateral balance and weight translation training. Moreover, it successfully tracks and follows user trajectories. The NIMBLE robotic frame assessment shows promising results for ambulatory gait rehabilitation. [ABSTRACT FROM AUTHOR]

Body weight support (BWS) systems are crucial in gait rehabilitation for individuals incapacitated due to injuries or medical conditions. Traditional BWS systems typically employ either static mass–rope or dynamic mass–spring–damper configurations, which can result in inadequate support stiffness, thereby leading to compromised gait training. Additionally, these systems often lack the flexibility for easy customization of stiffness, which is vital for personalized rehabilitation treatments. A novel BWS system with online variable stiffness is introduced in this study. This system incorporates a drive mechanism governed by admittance control that dynamically adjusts the stiffness by modulating the tension of a rope wrapped around a drum. An automated control algorithm is integrated to manage a smart anti-gravity dynamic suspension system, which ensures consistent and precise weight unloading adjustments throughout rehabilitation sessions. Walking experiments were performed to evaluate the displacement and load variations within the suspension ropes, thereby validating the variable-stiffness capability of the system. The findings suggest that the online variable-stiffness BWS system can reliably alter the stiffness levels and that it exhibits robust performance, significantly enhancing the effectiveness of gait rehabilitation. The newly developed BWS system represents a significant advancement in personalized gait rehabilitation, offering real-time stiffness adjustments and ongoing weight support customization. It ensures dependable control and robust operation, marking a significant step forward in tailored therapeutic interventions for gait rehabilitation. [ABSTRACT FROM AUTHOR]