A Portable Passive Rehabilitation Robot for Upper-Extremity Functional Resistance Training

Portable robots for upper-limb rehabilitation after stroke: a systematic review and meta-analysis

BACKGROUND

Robot-assisted upper-limb rehabilitation has been studied for many years, with many randomised controlled trials (RCTs) investigating the effects of robotic-assisted training on affected limbs. The current trend directs towards end-effector devices. However, most studies have focused on the effectiveness of rehabilitation devices, but studies on device sizes are relatively few.

GOAL

Systematically review the effect of a portable rehabilitation robot (PRR) on the rehabilitation effectiveness of paralysed upper limbs compared with non-robotic therapy.

METHODS

A meta-analysis was conducted on literature that included the Fugl-Meyer Assessment (FMA) obtained from the PubMed and Web of Science (WoS) electronic databases until June 2023.

RESULTS

A total of 9 studies, which included RCTs, were completed and a meta-analysis was conducted on 8 of them. The analysis involved 295 patients. The influence on upper-limb function before and after treatment in a clinical environment is analysed by comparing the experimental group using the portable upper-limb rehabilitation robot with the control group using conventional therapy. The result shows that portable robots prove to be effective (FMA: SMD = 0.696, 95% = 0.099 to.293, p < 0.05).

DISCUSSION

Both robot-assisted and conventional rehabilitation effects are comparable. In some studies, PRR performs better than conventional rehabilitation, but conventional treatments are still irreplaceable. Smaller size with better portability has its advantages, and portable upper-limb rehabilitation robots are feasible in clinical rehabilitation.

CONCLUSION

Although portable upper-limb rehabilitation robots are clinically beneficial, few studies have focused on portability. Further research should focus on modular design so that rehabilitation robots can be decomposed, which benefits remote rehabilitation and household applications.

Teaching Motor Skills Without a Motor: A Semi-Passive Robot to Facilitate Learning

Semi-passive rehabilitation robots resist and steer a patient's motion using only controllable passive force elements (e.g., controllable brakes). Contrarily, passive robots use uncontrollable passive force elements (e.g., springs), while active robots use controllable active force elements (e.g., motors). Semi-passive robots can address cost and safety limitations of active robots, but it is unclear if they have utility in rehabilitation. Here, we assessed if a semi-passive robot could provide haptic guidance to facilitate motor learning. We first performed a theoretical analysis of the robot's ability to provide haptic guidance, and then used a prototype to perform a motor learning experiment that tested if the guidance helped participants learn to trace a shape. Unlike prior studies, we minimized the confounding effects of visual feedback during motor learning. Our theoretical analysis showed that our robot produced guidance forces that were, on average, 54 ° from the current velocity (active devices achieve 90 °). Our motor learning experiment showed, for the first time, that participants who received haptic guidance during training learned to trace the shape more accurately (97.57% error to 52.69%) than those who did not receive guidance (81.83% to 78.18%). These results support the utility of semi-passive robots in rehabilitation.

An analysis of stimulation methods used in rehabilitation equipment for children with cerebral palsy

Objective

This paper summarizes the research progress into stimulation methods used in rehabilitation equipment for pediatric cerebral palsy (CP) for the past 20 years from 2003 to 2023. We also provide ideas for innovative research and development of artificial intelligence-based rehabilitation equipment.

Methods

Through a certain search strategy, Keywords are searched in the China National Knowledge Network Database (CNKI), the Wanfang Database knowledge service platform, the Chongqing VIP information service, PubMed, Web of Science, Cochrane, ScienceDirect, Medline, Embase, and IEEE database. A total of 3,049 relevant articles were retrieved, and 49 articles were included that mentioned research and development of rehabilitation equipment. We excluded articles that were not specific to children with CP, were duplicated or irrelevant literature, were missing data, the full article was not available, the article did not describe the method of stimulation used with the rehabilitation equipment on children with CP, were not Chinese and English, and were the types of reviews and commentaries.

Results

Physical stimulation is the main stimulation method of rehabilitation equipment for children with CP. Force stimulation is the main mode of physical stimulation, and there are 17 articles that have verified the clinical efficacy of force stimulation-based equipment.

Conclusion

Research on the stimulation mode of pediatric cerebral palsy rehabilitation equipment is likely to focus on simulating the force of the Chinese medicine called "tuina manipulation." When this method is combined with artificial intelligence and personalized direction we believe this will lay the foundation for future development of a novel therapy for children with CP.

Corticospinal excitability during motor preparation of upper extremity reaches reflects flexor muscle synergies: A novel principal component-based motor evoked potential analyses

Background

Previous research has shown that noninvasive brain stimulation can be used to study how the central nervous system (CNS) prepares the execution of a motor task. However, these previous studies have been limited to a single muscle or single degree of freedom movements (e.g., wrist flexion). It is currently unclear if the findings of these studies generalize to multi-joint movements involving multiple muscles, which may be influenced by kinematic redundancy and muscle synergies.

Objective

The objective of this study was to characterize corticospinal excitability during motor preparation in the cortex prior to functional upper extremity reaches.

Methods

20 participants without neurological impairments volunteered for this study. During the experiment, the participants reached for a cup in response to a visual "Go Cue". Prior to movement onset, we used transcranial magnetic stimulation (TMS) to stimulate the motor cortex and measured the changes in motor evoked potentials (MEPs) in several upper extremity muscles. We varied each participant's initial arm posture and used a novel synergy-based MEP analysis to examine the effect of muscle coordination on MEPs. Additionally, we varied the timing of the stimulation between the Go Cue and movement onset to examine the time course of motor preparation.

Results

We found that synergies with strong proximal muscle (shoulder and elbow) components emerged as the stimulation was delivered closer to movement onset, regardless of arm posture, but MEPs in the distal (wrist and finger) muscles were not facilitated. We also found that synergies varied with arm posture in a manner that reflected the muscle coordination of the reach.

Conclusions

We believe that these findings provide useful insight into the way the CNS plans motor skills.

Utilizing the intelligence edge framework for robotic upper limb rehabilitation in home

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 0.8918 0 , 2.6753 0 and 8.0258 0 , 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.

Home-based upper limb stroke rehabilitation mechatronics: challenges and opportunities

Interest in home-based stroke rehabilitation mechatronics, which includes both robots and sensor mechanisms, has increased over the past 12 years. The COVID-19 pandemic has exacerbated the existing lack of access to rehabilitation for stroke survivors post-discharge. Home-based stroke rehabilitation devices could improve access to rehabilitation for stroke survivors, but the home environment presents unique challenges compared to clinics. The present study undertakes a scoping review of designs for at-home upper limb stroke rehabilitation mechatronic devices to identify important design principles and areas for improvement. Online databases were used to identify papers published 2010-2021 describing novel rehabilitation device designs, from which 59 publications were selected describing 38 unique designs. The devices were categorized and listed according to their target anatomy, possible therapy tasks, structure, and features. Twenty-two devices targeted proximal (shoulder and elbow) anatomy, 13 targeted distal (wrist and hand) anatomy, and three targeted the whole arm and hand. Devices with a greater number of actuators in the design were more expensive, with a small number of devices using a mix of actuated and unactuated degrees of freedom to target more complex anatomy while reducing the cost. Twenty-six of the device designs did not specify their target users' function or impairment, nor did they specify a target therapy activity, task, or exercise. Twenty-three of the devices were capable of reaching tasks, 6 of which included grasping capabilities. Compliant structures were the most common approach of including safety features in the design. Only three devices were designed to detect compensation, or undesirable posture, during therapy activities. Six of the 38 device designs mention consulting stakeholders during the design process, only two of which consulted patients specifically. Without stakeholder involvement, these designs risk being disconnected from user needs and rehabilitation best practices. Devices that combine actuated and unactuated degrees of freedom allow a greater variety and complexity of tasks while not significantly increasing their cost. Future home-based upper limb stroke rehabilitation mechatronic designs should provide information on patient posture during task execution, design with specific patient capabilities and needs in mind, and clearly link the features of the design to users' needs.

Clinically oriented ankle rehabilitation robot with a novel mechanism

In order to make the designed ankle robotic system simpler, practical, and clinically oriented, we developed a novel $\underline{R}-2\underline{U}PS/RR$ ankle rehabilitation robot with a variety of training functions covering all the required ranges of motion of the ankle joint complex (AJC), where $U$ , $P$ , $S$ , and $R$ denote universal, prismatic, spherical, and revolute joints, respectively, and the underlined letter denotes the actuated joint. The robot was designed with three degrees of freedom (DOFs), with a series $R$ mechanism and a $2\underline{U}PS/RR$ parallel mechanism. The main advantage is that the height of the robot is very low, which is convenient for clinical use by patients. At first, the mechanism design and inverse solution of positions were introduced in detail. Then, the patient-passive exercise based on the predefined trajectory tracking and patient-active exercise based on the spring model were developed to satisfy different rehabilitation stages. Finally, experiments with healthy subjects were conducted to verify the effectiveness of the developed patient-passive and patient-active exercises of the developed ankle rehabilitation robot, with results compared with the existing ankle robotic system showing good trajectory tracking performance and interactive performance.

Development of portable robotic orthosis and biomechanical validation in people with limited upper limb function after stroke

Stroke has a considerable incidence in the world population and would cause sequelae in the upper limbs. One way to increase the efficiency in the rehabilitation process of patients with these sequelae is through robot-assisted therapy. The present study developed a portable robotic orthosis called Pinotti Portable Robotic Exoskeleton (PPRE) and validated its functioning in clinical tests. The static and dynamic parts of the device modules are described. Design issues, such as heavyweight and engine positioning, have been optimized. The implementation of control was through a smartphone application that communicates with a microcontroller to perform desired movements. Four individuals with motor impairment of the upper limbs due to stroke performed clinical tests to validate the device. Participants did not mention pain, discomfort, tingling, and paresthesia. The robotic device showed the ability to perform the flexion and extension movements of the fingers and elbow. The PPRE was confirmed to be adequate and functional at different levels of motor impairment assessed. The orthosis presented advantages over the currently existing devices, concerning its biomechanical functioning, portability, comfort, and versatility. Thus, the apparatus has the great innovative potential to become a device for home use, serving as an aid to the therapist and facilitating the rehabilitation of patients after an injury. In a larger sample, future studies are needed to assess the effect of a robotic orthosis on the level of rehabilitation in individuals with upper limb impairment.

Requirements and Solutions for Motion Limb Assistance of COVID-19 Patients

COVID-19 patients are strongly affected in terms of limb motion when imbedded during the acute phase of the infection, but also during the course of recovery therapies. Peculiarities are investigated for design requirements for medical devices in limb motion assistance for those patients. Solutions are analyzed from existing medical devices to outline open issues to provide guidelines for the proper adaption or for new designs supporting patients against COVID-19 effects. Examples are reported from authors’ activities with cable driven assisting devices.

PARS, low-cost portable rehabilitation system for upper arm

This study introduces a compact low-cost single degree of freedom end-effector type upper arm rehabilitation system (PARS) along with its hardware and software elements. Proposed system is also suitable to be used in conjunction with a gaming environment. Throughout the study structural setup of the system was explained in detail along with its electronics, control system and gaming software. Introduced virtual gaming interface supports various game levels with different difficulties generated via interaction type control algorithms. Having simple structural design constructed by using basic available components, proposed system can be easily manufactured and utilized in physical rehabilitation procedures by using supplied open source codes. Introduced systems compactness and user friendly interface also allow its usage for individual home therapies for remote rehabilitation treatment procedures.

Functional resistance training methods for targeting patient-specific gait deficits: A review of devices and their effects on muscle activation, neural control, and gait mechanics

BACKGROUND

Injuries to the neuromusculoskeletal system often result in weakness and gait impairments. Functional resistance training during walking-where patients walk while a device increases loading on the leg-is an emerging approach to combat these symptoms. However, there are many methods that can be used to resist the patient, which may alter the biomechanics of the training. Thus, all methods may not address patient-specific deficits.

METHODS

We performed a comprehensive electronic database search to identify articles that acutely (i.e., after a single training session) examined how functional resistance training during walking alters muscle activation, gait biomechanics, and neural plasticity. Only articles that examined these effects during training or following the removal of resistance (i.e., aftereffects) were included.

FINDINGS

We found 41 studies that matched these criteria. Most studies (24) used passive devices (e.g., weighted cuffs or resistance bands) while the remainder used robotic devices. Devices varied on if they were wearable (14) or externally tethered, and the type of resistance they applied (i.e., inertial [14], elastic [8], viscous [7], or customized [12]). Notably, these methods provided device-specific changes in muscle activation, biomechanics, and spatiotemporal and kinematic aftereffects. Some evidence suggests this training results in task-specific increases in neural excitability.

INTERPRETATION

These findings suggest that careful selection of resistive strategies could help target patient-specific strength deficits and gait impairments. Also, many approaches are low-cost and feasible for clinical or in-home use. The results provide new insights for clinicians on selecting an appropriate functional resistance training strategy to target patient-specific needs.

A Robotic System to Deliver Multiple Physically Bimanual Tasks via Varying Force Fields

Individuals with physical limb disabilities are often restricted to perform activities of daily life (ADLs). While efficacy of bilateral training has been demonstrated in improving physical coordination of human limbs, few robots have been developed in simulating people's ADLs integrated with task-specific force field control. This study sought to develop a bilateral robot for better task rendering of general ADLs (gADLs), where gADL-consistent workspace is achieved by setting linear motors in series, and haptic rendering of multiple bimanual tasks (coupled, uncoupled and semi-coupled) is enabled by regulating force fields between robotic handles. Experiments were conducted with human users, and our results present a viable method of a single robotic system in simulating multiple physically bimanual tasks. In future, the proposed robotic system is expected to be serving as a coordination training device, and its clinical efficacy will be also investigated.

Effect of Continuous Care Combined with Constraint-Induced Movement Therapy Based on a Continuing Care Health Platform on MBI and FMA Scores of Acute Stroke Patients

Methods

68 acute stroke patients admitted to our hospital from July 2018 to July 2019 were selected as the study participants and divided into group A and group B based on the odd and even numbers of their admission numbers, with 34 cases in each group. Patients in group B accepted the routine rehabilitation exercise, while patients in group A accepted the continuous care combined with constraint-induced movement therapy (CIMT) under a health platform, so as to compare their upper limb function recovery by the Fugl–Meyer assessment (FMA) and improved median Barthel index (MBI).

Results

The general information of the two groups were not obviously different (P > 0.05) but comparable; after intervention, the FMA scores (38.42 ± 7.62 vs 31.22 ± 7.25) and MBI scores (78.63 ± 6.52 vs 70.24 ± 6.48) of patients in group A were significantly higher than those of group B (P < 0.001); the activities of daily living (ADL) and trunk control test (TCT) scores at T1, T2, and T3 of group A were significantly higher than those of group B (P < 0.05); at 6 months after discharge, the self-concept, self-care skills, self-care, self-responsibility, health knowledge level, and total ability scores of patients in group A were significantly higher than those in group B (P < 0.05); the Generic Quality of Life Inventory-74 (GQOL-74) scores after intervention of the two groups were significantly higher than those before intervention (P < 0.05) and those of group A were significantly higher than those of group B (72.13 ± 4.69 vs 63.19 ± 4.72; P < 0.05); when comparing with group B, group A presented significantly higher walking speed and gait period and lower support phase (P < 0.05).

Conclusion

The combination of continuous care and CIMT under a health platform can effectively promote the rehabilitation of upper limb functions and improve the activities of daily living and trunk control for acute stroke patients, with an effect better than conventional rehabilitation exercises, which is worthy of promotion.

Manipulating abnormal synergistic coupling of joint torques through force applications at the Hand: A Simulation-Based study

Loss of independent joint control due to abnormal coupling of shoulder and elbow torques (i.e., abnormal synergies) is a common impairment after stroke and has been linked to poor upper-extremity function in stroke survivors. Previous research has shown that the flexor synergy (i.e., shoulder abduction coupled with elbow flexion) can be treated by progressively increasing shoulder abduction loading during elbow extension exercises. However, this finding has not been implemented in planar reaching exercises, as this requires a clear understanding of the relationship between external forces on the hand and elicited joint torques when reaching for different targets on a table. The objective of this study was to model this relationship and determine reach/force combinations that could be used to counteract either the flexor or extensor synergies. We used a musculoskeletal model to compute shoulder and elbow joint torques when reaching for targets on a table against different force directions and magnitudes. We found that force direction modulated the coupling of shoulder and elbow torques and force magnitude scaled each torque uniformly such that the extent of coupling remained the same. Additionally, we found that forces on the hand could be used to gradually increase the magnitude of simultaneous shoulder and elbow torques that counteract either the flexor or extensor synergy. These results provide the foundation to develop therapeutic interventions that address abnormal joint couplings following stroke using forces on the hand during planar reaching. Future studies should examine the therapeutic benefits of these findings in patient populations such as stroke.

Challenges and solutions for application and wider adoption of wearable robots

The science and technology of wearable robots are steadily advancing, and the use of such robots in our everyday life appears to be within reach. Nevertheless, widespread adoption of wearable robots should not be taken for granted, especially since many recent attempts to bring them to real-life applications resulted in mixed outcomes. The aim of this article is to address the current challenges that are limiting the application and wider adoption of wearable robots that are typically worn over the human body. We categorized the challenges into mechanical layout, actuation, sensing, body interface, control, human-robot interfacing and coadaptation, and benchmarking. For each category, we discuss specific challenges and the rationale for why solving them is important, followed by an overview of relevant recent works. We conclude with an opinion that summarizes possible solutions that could contribute to the wider adoption of wearable robots.

Gaze-controlled Robot-assisted Painting in Virtual Reality for Upper-limb Rehabilitation

Stroke is the leading cause of adult disability. Robot-assisted rehabilitation systems show great promise for motor recovery after a stroke. In this work, we present a gazecontrolled robotic system for upper limb rehabilitation. Subjects perform a painting task in virtual reality. We designed a novel and challenging painting task to encourage motivation and engagement, as these are critical factors in treatment efficacy. Because the robotic system can be programmed to provide varying amounts of assistance or resistance to the subject, it can be applied to a wide range of patients at different phases of recovery. We describe here the system configured in two modes: resistive control and hierarchical control. The former is designed for later stages of recovery, where the patient's impaired limb has recovered some function. It can be configured to provide varying degrees of resistance by adjusting the properties of an admittance controller. The latter targets patients in more acute phases, where the impaired limb is less responsive. It provides a combination of assistive and corrective control. We pilot tested our system on 10 able-bodied subjects. Our results show that the system can provide varying degrees of resistive control, and that the integration of high level control modulated by gaze can improve engagement. These results suggest that the system may provide a more engaging environment for a wide range of rehabilitative therapies than currently available.

Robotic Home-Based Rehabilitation Systems Design: From a Literature Review to a Conceptual Framework for Community-Based Remote Therapy During COVID-19 Pandemic

During the COVID-19 pandemic, the higher susceptibility of post-stroke patients to infection calls for extra safety precautions. Despite the imposed restrictions, early neurorehabilitation cannot be postponed due to its paramount importance for improving motor and functional recovery chances. Utilizing accessible state-of-the-art technologies, home-based rehabilitation devices are proposed as a sustainable solution in the current crisis. In this paper, a comprehensive review on developed home-based rehabilitation technologies of the last 10 years (2011-2020), categorizing them into upper and lower limb devices and considering both commercialized and state-of-the-art realms. Mechatronic, control, and software aspects of the system are discussed to provide a classified roadmap for home-based systems development. Subsequently, a conceptual framework on the development of smart and intelligent community-based home rehabilitation systems based on novel mechatronic technologies is proposed. In this framework, each rehabilitation device acts as an agent in the network, using the internet of things (IoT) technologies, which facilitates learning from the recorded data of the other agents, as well as the tele-supervision of the treatment by an expert. The presented design paradigm based on the above-mentioned leading technologies could lead to the development of promising home rehabilitation systems, which encourage stroke survivors to engage in under-supervised or unsupervised therapeutic activities.

Design and evaluation of a surface electromyography-controlled lightweight upper arm exoskeleton rehabilitation robot

Nowadays, the rehabilitation robot has been developed for rehabilitation therapy. However, there are few studies on upper arm exoskeletons for rehabilitation training of muscle strength. This article aims to design a surface electromyography-controlled lightweight exoskeleton rehabilitation robot for home-based progressive resistance training. The exoskeleton’s lightweight structure is designed based on the kinematic model of the elbow joint and ergonomics sizes of the arm. At the same time, the overall weight of the exoskeleton is controlled at only 3.03 kg. According to the rehabilitation training task, we use torque limit mode to ensure stable torque output at variable velocity. We also propose a surface electromyography-based control method, which uses k- Nearest Neighbor algorithm to classify surface electromyographic signals under progressive training loads, and utilizes principal component analysis to improve the recognition accuracy to control the exoskeleton to provide muscle strength compensation. The assessment experiment of the exoskeleton rehabilitation robot shows that the dynamic recognition accuracy of this control method is 80.21%. Muscle activity of biceps brachii and triceps brachii under each training load decreases significantly when subjects with the exoskeleton robot. The results indicate that the exoskeleton rehabilitation robot can output the corresponding torque to assist in progressive resistance training. This study provides a solution to potential problems in the family-oriented application of exoskeleton rehabilitation robots.

Review: How Can Intelligent Robots and Smart Mechatronic Modules Facilitate Remote Assessment, Assistance, and Rehabilitation for Isolated Adults With Neuro-Musculoskeletal Conditions?

Worldwide, at the time this article was written, there are over 127 million cases of patients with a confirmed link to COVID-19 and about 2.78 million deaths reported. With limited access to vaccine or strong antiviral treatment for the novel coronavirus, actions in terms of prevention and containment of the virus transmission rely mostly on social distancing among susceptible and high-risk populations. Aside from the direct challenges posed by the novel coronavirus pandemic, there are serious and growing secondary consequences caused by the physical distancing and isolation guidelines, among vulnerable populations. Moreover, the healthcare system's resources and capacity have been focused on addressing the COVID-19 pandemic, causing less urgent care, such as physical neurorehabilitation and assessment, to be paused, canceled, or delayed. Overall, this has left elderly adults, in particular those with neuromusculoskeletal (NMSK) conditions, without the required service support. However, in many cases, such as stroke, the available time window of recovery through rehabilitation is limited since neural plasticity decays quickly with time. Given that future waves of the outbreak are expected in the coming months worldwide, it is important to discuss the possibility of using available technologies to address this issue, as societies have a duty to protect the most vulnerable populations. In this perspective review article, we argue that intelligent robotics and wearable technologies can help with remote delivery of assessment, assistance, and rehabilitation services while physical distancing and isolation measures are in place to curtail the spread of the virus. By supporting patients and medical professionals during this pandemic, robots, and smart digital mechatronic systems can reduce the non-COVID-19 burden on healthcare systems. Digital health and cloud telehealth solutions that can complement remote delivery of assessment and physical rehabilitation services will be the subject of discussion in this article due to their potential in enabling more effective and safer NMSDK rehabilitation, assistance, and assessment service delivery. This article will hopefully lead to an interdisciplinary dialogue between the medical and engineering sectors, stake holders, and policy makers for a better delivery of care for those with NMSK conditions during a global health crisis including future pandemics.

Comparison of active-assisted and active-unassisted robot-mediated upper limb therapy in subacute stroke

BACKGROUND

Upper-limb robot-mediated therapy is usually carried out in active-assisted mode because it enables performance of many movements. However, assistance may reduce the patient's own efforts which could limit motor recovery.

OBJECTIVE

The aim of this study was to compare the effects of active-assisted and active-unassisted robotic interactions on motor recovery in subacute stroke patients with moderate hemiparesis.

METHODS

Fourteen patients underwent a 6-week combined upper limb program of usual therapy and robotic therapy using either the active-unassisted (n = 8) or active-assisted (n = 6) modes. In the active-assisted group, assistance was only provided for the first 3 weeks (1st period) and was then switched off for the remaining 3 weeks (2nd period). The Fugl-Meyer Assessment (FMA) was carried out pre- and post-treatment. The mean number of movements performed and the mean working distance during the 1st and 2nd periods were compared between groups.

RESULTS

FMA score improved post-treatment in both groups with no between-group differences: active-assisted group: +8±6 pts vs active-unassisted group: +10±6 pts (ns). Between the 1st and 2nd periods, there was a statistical trend towards an improvement in the number of movements performed (p = 0.06) in the active-unassisted group (526±253 to 783±434, p = 0.06) but not in the active-assisted group (882±211 to 880±297, ns). Another trend of improvement was found for the working distance in the active-unassisted group (8.7±4.5 to 9.9±4.7, p = 0.09) but not in the active-assisted group (14.0±0 to 13.5±1.1, ns).

CONCLUSIONS

The superiority of the non-assistive over assistive robotic modes has not been demonstrated. However, the non-assistive mode did not appear to reduce motor recovery in this population, despite the performance of fewer movements on shorter working distance compared with the group who had assistance. It seems that the requirement of effort could be a determinant factor for recovery in neurorehabilitation however further well-design studies are needed to fully understand this phenomenon.

Functional Resistance Training to Improve Knee Strength and Function After Acute Anterior Cruciate Ligament Reconstruction: A Case Study

BACKGROUND

Thigh muscle weakness after anterior cruciate ligament reconstruction (ACLR) can persist after returning to activity. While resistance training can improve muscle function, "nonfunctional" training methods are not optimal for inducing transfer of benefits to activities such as walking. Here, we tested the feasibility of a novel functional resistance training (FRT) approach to restore strength and function in an individual with ACLR.

HYPOTHESIS

FRT would improve knee strength and function after ACLR.

STUDY DESIGN

Case report.

LEVEL OF EVIDENCE

Level 5.

METHODS

A 15-year-old male patient volunteered for an 8-week intervention where he performed 30 minutes of treadmill walking, 3 times per week, while wearing a custom-designed knee brace that provided resistance to the thigh muscles of his ACLR leg. Thigh strength, gait mechanics, and corticospinal and spinal excitability were assessed before and immediately after the 8-week intervention. Voluntary muscle activation was evaluated immediately after the intervention.

RESULTS

Knee extensor and flexor strength increased in the ACLR leg from pre- to posttraining (130 to 225 N·m [+74%] and 44 to 88 N·m [+99%], respectively) and increases in between-limb extensor and flexor strength symmetry (45% to 92% [+74%] and 47% to 72% [+65%], respectively) were also noted. After the intervention, voluntary muscle activation in the ACLR leg was 72%, compared with the non-ACLR leg at 75%. Knee angle and moment during late stance phase decreased (ie, improved) in the ACLR leg and appeared more similar to the non-ACLR leg after FRT training (18° to 14° [-23.4] and 0.07 to -0.02 N·m·kg^-1·m^-1 [-122.8%], respectively). Corticospinal and spinal excitability in the ACLR leg decreased (3511 to 2511 [-28.5%] and 0.42 to 0.24 [-43.7%], respectively) from pre- to posttraining.

CONCLUSION

A full 8 weeks of FRT that targeted both quadriceps and hamstring muscles lead to improvements in strength and gait, suggesting that FRT may constitute a promising and practical alternative to traditional methods of resistance training.

CLINICAL RELEVANCE

FRT may serve as a viable approach to improve knee strength and function after ACL reconstruction.

Design and Preliminary Assessment of a Passive Elastic Leg Exoskeleton for Resistive Gait Rehabilitation

OBJECTIVE

This article aimed to develop a unique exoskeleton to provide different types of elastic resistances (i.e., resisting flexion, extension, or bidirectionally) to the leg muscles during walking.

METHODS

We created a completely passive leg exoskeleton, consisting of counteracting springs, pulleys, and clutches, to provide different types of elastic resistance to the knee. We first used a benchtop setting to calibrate the springs and validate the resistive capabilities of the device. We then tested the device's ability to alter gait mechanics, muscle activation, and kinematic aftereffects when walking on a treadmill under the three resistance types.

RESULTS

Benchtop testing indicated that the device provided a nearly linear torque profile and could be accurately configured to alter the angle where the spring system was undeformed (i.e., the resting position). Treadmill testing indicated the device could specifically target knee flexors, extensors, or both, and increase eccentric loading at the joint. Additionally, these resistance types elicited different kinematic aftereffects that could be used to target user-specific spatiotemporal gait deficits.

CONCLUSION

These results indicate that the elastic device can provide various types of targeted resistance training during walking.

SIGNIFICANCE

The proposed elastic device can provide a diverse set of resistance types that could potentially address user-specific muscle weaknesses and gait deficits through functional resistance training.

Evaluating Rehabilitation Progress Using Motion Features Identified by Machine Learning

Evaluating progress throughout a patient's rehabilitation episode is critical for determining the effectiveness of the selected treatments and is an essential ingredient in personalised and evidence-based rehabilitation practice. The evaluation process is complex due to the inherently large human variations in motor recovery and the limitations of commonly used clinical measurement tools. Information recorded during a robot-assisted rehabilitation process can provide an effective means to continuously quantitatively assess movement performance and rehabilitation progress. However, selecting appropriate motion features for rehabilitation evaluation has always been challenging. This paper exploits unsupervised feature learning techniques to reduce the complexity of building the evaluation model of patients' progress. A new feature learning technique is developed to select the most significant features from a large amount of kinematic features measured from robotics, providing clinically useful information to health practitioners with reduction of modeling complexity. A novel indicator that uses monotonicity and trendability is proposed to evaluate kinematic features. The data used to develop the feature selection technique consist of kinematic data from robot-aided rehabilitation for a population of stroke patients. The selected kinematic features allow for human variations across a population of patients as well as over the sequence of rehabilitation sessions. The study is based on data records pertaining to 41 stroke patients using three different robot assisted exercises for upper limb rehabilitation. Consistent with the literature, the results indicate that features based on movement smoothness are the best measures among 17 kinematic features suitable to evaluate rehabilitation progress.

Motor Modules are Impacted by the Number of Reaching Directions Included in the Analysis

Muscle synergy analysis is commonly used to study how the nervous system coordinates the activation of a large number of muscles during human reaching. In synergy analysis, muscle activation data collected from various reaching directions are subjected to dimensionality reduction techniques to extract muscle synergies. Typically, muscle activation data are obtained only from a limited set of reaches with an inherent assumption that the performed reaches adequately represent all possible reaches. In this study, we investigated how the number of reaching directions included in the synergy analysis influences the validity of the extracted synergies. We used a musculoskeletal model to compute muscle activations required to perform 36 evenly spaced planar reaches. Nonnegative matrix factorization (NMF) and principal component analysis (PCA) were then used to extract reference synergies. We then selected several subsets of reaches and compared the ability of the extracted synergies from each subset to represent the muscle activation from all 36 reaches. We found that 6 reaches were required to extract valid synergies, and a further reduction in the number of reaches changed the composition of the resulting synergies. Further, we found that the choice of reaching directions included in the analysis for a given number of reaches also affected the validity of the extracted synergies. These findings indicate that both the number and the choice of reaching directions included in the analysis impacted the validity of the extracted synergies.

Detection of Participation and Training Task Difficulty Applied to the Multi-Sensor Systems of Rehabilitation Robots

In the process of rehabilitation training for stroke patients, the rehabilitation effect is positively affected by how much physical activity the patients take part in. Most of the signals used to measure the patients' participation are EMG signals or oxygen consumption, which increase the cost and the complexity of the robotic device. In this work, we design a multi-sensor system robot with torque and six-dimensional force sensors to gauge the patients' participation in training. By establishing the static equation of the mechanical leg, the man-machine interaction force of the patient can be accurately extracted. Using the impedance model, the auxiliary force training mode is established, and the difficulty of the target task is changed by adjusting the K value of auxiliary force. Participation models with three intensities were developed offline using support vector machines, for which the C and σ parameters are optimized by the hybrid quantum particle swarm optimization and support vector machines (Hybrid QPSO-SVM) algorithm. An experimental statistical analysis was conducted on ten volunteers' motion representation in different training tasks, which are divided into three stages: over-challenge, challenge, less challenge, by choosing characteristic quantities with significant differences among the various difficulty task stages, as a training set for the support vector machines (SVM). Experimental results from 12 volunteers, with tasks conducted on the lower limb rehabilitation robot LLR-II show that the rehabilitation robot can accurately predict patient participation and training task difficulty. The prediction accuracy reflects the superiority of the Hybrid QPSO-SVM algorithm.

Self-powered robots to reduce motor slacking during upper-extremity rehabilitation: a proof of concept study

BACKGROUND

Robotic rehabilitation is a highly promising approach to recover lost functions after stroke or other neurological disorders. Unfortunately, robotic rehabilitation currently suffers from "motor slacking", a phenomenon in which the human motor system reduces muscle activation levels and movement excursions, ostensibly to minimize metabolic- and movement-related costs. Consequently, the patient remains passive and is not fully engaged during therapy. To overcome this limitation, we envision a new class of body-powered robots and hypothesize that motor slacking could be reduced if individuals must provide the power to move their impaired limbs via their own body (i.e., through the motion of a healthy limb).

OBJECTIVE

To test whether a body-powered exoskeleton (i.e. robot) could reduce motor slacking during robotic training.

METHODS

We developed a body-powered robot that mechanically coupled the motions of the user's elbow joints. We tested this passive robot in two groups of subjects (stroke and able-bodied) during four exercise conditions in which we controlled whether the robotic device was powered by the subject or by the experimenter, and whether the subject's driven arm was engaged or at rest. Motor slacking was quantified by computing the muscle activation changes of the elbow flexor and extensor muscles using surface electromyography.

RESULTS

Subjects had higher levels of muscle activation in their driven arm during self-powered conditions compared to externally-powered conditions. Most notably, subjects unintentionally activated their driven arm even when explicitly told to relax when the device was self-powered. This behavior was persistent throughout the trial and did not wane after the initiation of the trial.

CONCLUSIONS

Our findings provide novel evidence indicating that motor slacking can be reduced by self-powered robots; thus demonstrating promise for rehabilitation of impaired subjects using this new class of wearable system. The results also serve as a foundation to develop more sophisticated body-powered robots (e.g., with controllable transmissions) for rehabilitation purposes.

Development, Dynamic Modeling, and Multi-Modal Control of a Therapeutic Exoskeleton for Upper Limb Rehabilitation Training

Robot-assisted training is a promising technology in clinical rehabilitation providing effective treatment to the patients with motor disability. In this paper, a multi-modal control strategy for a therapeutic upper limb exoskeleton is proposed to assist the disabled persons perform patient-passive training and patient-cooperative training. A comprehensive overview of the exoskeleton with seven actuated degrees of freedom is introduced. The dynamic modeling and parameters identification strategies of the human-robot interaction system are analyzed. Moreover, an adaptive sliding mode controller with disturbance observer (ASMCDO) is developed to ensure the position control accuracy in patient-passive training. A cascade-proportional-integral-derivative (CPID)-based impedance controller with graphical game-like interface is designed to improve interaction compliance and motivate the active participation of patients in patient-cooperative training. Three typical experiments are conducted to verify the feasibility of the proposed control strategy, including the trajectory tracking experiments, the trajectory tracking experiments with impedance adjustment, and the intention-based training experiments. The experimental results suggest that the tracking error of ASMCDO controller is smaller than that of terminal sliding mode controller. By optimally changing the impedance parameters of CPID-based impedance controller, the training intensity can be adjusted to meet the requirement of different patients.