Applying an Artificial Neuromolecular System to the Application of Robotic Arm Motion Control in Assisting the Rehabilitation of Stroke Patients-An Artificial World Approach

Stroke patients cannot use their hands as freely as usual. However, recovery after a stroke is a long road for many patients. If artificial intelligence can assist human arm movement, it is believed that the possibility of stroke patients returning to normal hand movement can be significantly increased. In this study, the artificial neuromolecular system (ANM system) developed by our laboratory is used as the core motion control system to learn to control the mechanical arm, produce similar human rehabilitation actions, and assist patients in transiting between different activities. The strength of the ANM system lies in its ability to capture and process spatiotemporal information by exploiting the dynamic information processing inside neurons. Five experiments are conducted in this research: continuous learning, dimensionality reduction, moving problem domains, transfer learning, and fault tolerance. The results show that the ANM system can find out the arm movement trajectory when people perform different rehabilitation actions through the ability of continuous learning and reduce the activation of multiple muscle groups in stroke patients through the learning method of reducing dimensions. Finally, using the ANM system can reduce the learning time and performance required to switch between different actions through transfer learning.

Effects of Noisy Galvanic Vestibular Stimulation During a Bimanual Tracking Robotic Task

Background

Noisy galvanic vestibular stimulation (nGVS) has been shown to improve motor performance in people with and without disabilities. Previous investigations on the use of nGVS to improve upper-limb motor performance have focused on unimanual fine motor movements, nevertheless, bimanual gross movements are also essential for conducting activities of daily living and can be affected as a result of cerebral dysfunction. Consequently, in this study we investigated the effects of nGVS on bimanual gross motor performance.

Methods

Twelve healthy participants completed a visuomotor task in which they performed bimanual upper-limb movements using two robots. During the task, participants tracked a target that oscillated following a sinusoidal amplitude-modulated trajectory. In half of the trials, participants received subthreshold nGVS, in the other half, they received sham stimulation. Primary outcome measure: percent improvement in root mean square error (RMSE) between the target’s and cursors’ trajectories. Secondary outcome measures: percent improvement in lag between the cursors and target; and percent improvement in RMSE between the cursors’ trajectories. A post-test questionnaire was administered to evaluate the experience of participants.

Results

Tracking error was not affected by nGVS: left −2.6(5.5)%, p = 0.128; right −0.9(6.2)%, p = 0.639; nor was bimanual coordination −1.5(9.6)%, p = 0.590. When comparing if one hand was affected more than the other, we did not find a statistically significant difference (−1.7(3.3)%, p = 0.098). Similar results were found for the lag. Questionnaire results indicated that the robotic devices did not limit participants’ movements, did not make participants feel unsafe, nor were they difficult to control. Furthermore, participants did not feel unsafe with the nGVS device, nor did they report any discomfort due to nGVS.

Conclusion

Results suggest that nGVS applied to people without disabilities do not affect bimanual gross motor performance. However, as this was the first study to investigate such effects, stimulation parameters were based on previous unimanual fine motor studies. Future studies should investigate optimal stimulation parameters for improving upper-limb gross motor performance. Overall, participants felt safe using the robotic devices and receiving the noisy electrical stimulation. As such, a similar setup could potentially be employed for subsequent studies investigating the relation between upper-limb performance and nGVS.

Rehabilitation robots for the treatment of sensorimotor deficits: a neurophysiological perspective

The past decades have seen rapid and vast developments of robots for the rehabilitation of sensorimotor deficits after damage to the central nervous system (CNS). Many of these innovations were technology-driven, limiting their clinical application and impact. Yet, rehabilitation robots should be designed on the basis of neurophysiological insights underlying normal and impaired sensorimotor functions, which requires interdisciplinary collaboration and background knowledge.

Recovery of sensorimotor function after CNS damage is based on the exploitation of neuroplasticity, with a focus on the rehabilitation of movements needed for self-independence. This requires a physiological limb muscle activation that can be achieved through functional arm/hand and leg movement exercises and the activation of appropriate peripheral receptors. Such considerations have already led to the development of innovative rehabilitation robots with advanced interaction control schemes and the use of integrated sensors to continuously monitor and adapt the support to the actual state of patients, but many challenges remain. For a positive impact on outcome of function, rehabilitation approaches should be based on neurophysiological and clinical insights, keeping in mind that recovery of function is limited. Consequently, the design of rehabilitation robots requires a combination of specialized engineering and neurophysiological knowledge. When appropriately applied, robot-assisted therapy can provide a number of advantages over conventional approaches, including a standardized training environment, adaptable support and the ability to increase therapy intensity and dose, while reducing the physical burden on therapists. Rehabilitation robots are thus an ideal means to complement conventional therapy in the clinic, and bear great potential for continued therapy and assistance at home using simpler devices.

This review summarizes the evolution of the field of rehabilitation robotics, as well as the current state of clinical evidence. It highlights fundamental neurophysiological factors influencing the recovery of sensorimotor function after a stroke or spinal cord injury, and discusses their implications for the development of effective rehabilitation robots. It thus provides insights on essential neurophysiological mechanisms to be considered for a successful development and clinical inclusion of robots in rehabilitation.

A NOVEL MULTI-DOF EXOSKELETON ROBOT FOR UPPER LIMB REHABILITATION

Patients who suffer from stroke have motion function disorders. They need rehabilitation training guided by doctors and trainers. Nowadays, robots have been introduced to help the patients regain their motion function in rehabilitation training. In this paper, a novel multi degree of freedom (DOF) exoskeleton robot, with light weight, including (6[Formula: see text]1) DOFs, named as Rehab-Arm, is proposed and developed for upper limb rehabilitation. The joints of the robot are equipped with micro motors which are capable of actuating each DOF respectively and simultaneously. The medial/lateral rotation of shoulder is realized by a semi-circle guide mechanism for convenience consideration and safety. The robot is used in sitting posture which is attached to a custom made chair. Hence, the robot can be used to assist patients in passive movement with 7 DOFs of the upper limb for rehabilitation. Five adult healthy male subjects participated in the experiment to test the joint movement accuracy of the robot. Finally, subjects can wear Rehab-Arm and move their upper limb, led by micro motors of the robot, to perform task assigned with specific trajectory.

On the assessment of coordination between upper extremities: towards a common language between rehabilitation engineers, clinicians and neuroscientists

Well-developed coordination of the upper extremities is critical for function in everyday life. Interlimb coordination is an intuitive, yet subjective concept that refers to spatio-temporal relationships between kinematic, kinetic and physiological variables of two or more limbs executing a motor task with a common goal. While both the clinical and neuroscience communities agree on the relevance of assessing and quantifying interlimb coordination, rehabilitation engineers struggle to translate the knowledge and needs of clinicians and neuroscientists into technological devices for the impaired. The use of ambiguous definitions in the scientific literature, and lack of common agreement on what should be measured, present large barriers to advancements in this area. Here, we present the different definitions and approaches to assess and quantify interlimb coordination in the clinic, in motor control studies, and by state-of-the-art robotic devices. We then propose a taxonomy of interlimb activities and give recommendations for future neuroscience-based robotic- and sensor-based assessments of upper limb function that are applicable to the everyday clinical practice. We believe this is the first step towards our long-term goal of unifying different fields and help the generation of more consistent and effective tools for neurorehabilitation.

Bilateral robots for upper-limb stroke rehabilitation: State of the art and future prospects

Robot-assisted bilateral upper-limb training grows abundantly for stroke rehabilitation in recent years and an increasing number of devices and robots have been developed. This paper aims to provide a systematic overview and evaluation of existing bilateral upper-limb rehabilitation devices and robots based on their mechanisms and clinical-outcomes. Most of the articles studied here were searched from nine online databases and the China National Knowledge Infrastructure (CNKI) from year 1993 to 2015. Devices and robots were categorized as end-effectors, exoskeletons and industrial robots. Totally ten end-effectors, one exoskeleton and one industrial robot were evaluated in terms of their mechanical characteristics, degrees of freedom (DOF), supported control modes, clinical applicability and outcomes. Preliminary clinical results of these studies showed that all participants could gain certain improvements in terms of range of motion, strength or physical function after training. Only four studies supported that bilateral training was better than unilateral training. However, most of clinical results cannot definitely verify the effectiveness of mechanisms and clinical protocols used in robotic therapies. To explore the actual value of these robots and devices, further research on ingenious mechanisms, dose-matched clinical protocols and universal evaluation criteria should be conducted in the future.

Fusion of Haptic and Gesture Sensors for Rehabilitation of Bimanual Coordination and Dexterous Manipulation

Disabilities after neural injury, such as stroke, bring tremendous burden to patients, families and society. Besides the conventional constrained-induced training with a paretic arm, bilateral rehabilitation training involves both the ipsilateral and contralateral sides of the neural injury, fitting well with the fact that both arms are needed in common activities of daily living (ADLs), and can promote good functional recovery. In this work, the fusion of a gesture sensor and a haptic sensor with force feedback capabilities has enabled a bilateral rehabilitation training therapy. The Leap Motion gesture sensor detects the motion of the healthy hand, and the omega.7 device can detect and assist the paretic hand, according to the designed cooperative task paradigm, as much as needed, with active force feedback to accomplish the manipulation task. A virtual scenario has been built up, and the motion and force data facilitate instantaneous visual and audio feedback, as well as further analysis of the functional capabilities of the patient. This task-oriented bimanual training paradigm recruits the sensory, motor and cognitive aspects of the patient into one loop, encourages the active involvement of the patients into rehabilitation training, strengthens the cooperation of both the healthy and impaired hands, challenges the dexterous manipulation capability of the paretic hand, suits easy of use at home or centralized institutions and, thus, promises effective potentials for rehabilitation training.

Bimanual elbow robotic orthoses: preliminary investigations on an impairment force-feedback rehabilitation method

Modern rehabilitation practices have begun integrating robots, recognizing their significant role in recovery. New and alternative stroke rehabilitation treatments are essential to enhance efficacy and mitigate associated health costs. Today's robotic interventions can play a significant role in advancing rehabilitation. In addition, robots have an inherent ability to perform tasks accurately and reliably and are typically well suited to measure and quantify performance. Most rehabilitation strategies predominantly target activation of the paretic arm. However, bimanual upper-limb rehabilitation research suggests potential in enhancing functional recovery. Moreover, studies suggest that limb coordination and synchronization can improve treatment efficacy. In this preliminary study, we aimed to investigate and validate our user-driven bimanual system in a reduced intensity rehab practice. A bimanual wearable robotic device (BWRD) with a Master-Slave configuration for the elbow joint was developed to carry out the investigation. The BWRD incorporates position and force sensors for which respective control loops are implemented, and offers varying modes of operation ranging from passive to active training. The proposed system enables the perception of the movements, as well as the forces applied by the hemiparetic arm, with the non-hemiparetic arm. Eight participants with chronic unilateral stroke were recruited to participate in a total of three 1-h sessions per participant, delivered in a week. Participants underwent pre- and post-training functional assessments along with proprioceptive measures. The post-assessment was performed at the end of the last training session. The protocol was designed to engage the user in an assortment of static and dynamic arm matching and opposing tasks. The training incorporates force-feedback movements, force-feedback positioning, and force matching tasks with same and opposite direction movements. We are able to suggest identification of impairment patterns in the position-force plot results. In addition, we performed a proprioception evaluation with the system. We set out to design innovative and user immersive training tasks that utilize the BWRD capabilities, and we demonstrate that the subjects were able to cooperate and accomplish the protocol. We found that the Fugl-Meyer and Wolf Motor Function Test (pre to post) measured improvements (15 and 19%, respectively). Recognizing the brevity of the training, we focus our report primarily on the proprioception testing (32% significant improvement, p prop = 0.033) and protocol distinctive features and results. This paper presents the electromechanical features and performance of the BWRD, the testing protocol, and the assessments utilized. Outcome measures and results are presented and demonstrate the successful application and operation of the system.

Current Trends in Robot-Assisted Upper-Limb Stroke Rehabilitation: Promoting Patient Engagement in Therapy

Stroke is one of the leading causes of long-term disability today; therefore, many research efforts are focused on designing maximally effective and efficient treatment methods. In particular, robotic stroke rehabilitation has received significant attention for upper-limb therapy due to its ability to provide high-intensity repetitive movement therapy with less effort than would be required for traditional methods. Recent research has focused on increasing patient engagement in therapy, which has been shown to be important for inducing neural plasticity to facilitate recovery. Robotic therapy devices enable unique methods for promoting patient engagement by providing assistance only as needed and by detecting patient movement intent to drive to the device. Use of these methods has demonstrated improvements in functional outcomes, but careful comparisons between methods remain to be done. Future work should include controlled clinical trials and comparisons of effectiveness of different methods for patients with different abilities and needs in order to inform future development of patient-specific therapeutic protocols.

Real-Time Estimation of Glenohumeral Joint Rotation Center With Cable-Driven Arm Exoskeleton (CAREX)-A Cable-Based Arm Exoskeleton

In the past few years, the authors have proposed several prototypes of a Cable-driven upper ARm EXoskeleton (CAREX) for arm rehabilitation. One of the assumptions of CAREX was that the glenohumeral joint rotation center (GH-c) remains stationary in the inertial frame during motion, which leads to inaccuracy in the kinematic model and may hamper training performance. In this paper, we propose a novel approach to estimate GH-c using measurements of shoulder joint angles and cable lengths. This helps in locating the GH-c center appropriately within the kinematic model. As a result, more accurate kinematic model can be used to improve the training of human users. An estimation algorithm is presented to compute the GH-c in real-time. The algorithm was implemented on the latest prototype of CAREX. Simulations and preliminary experimental results are presented to validate the proposed GH-c estimation method.

Study of an upper arm exoskeleton for gravity balancing and minimization of transmitted forces

An upper-arm wearable exoskeleton has been designed for the assistance and functional training of humans. One of the goals of this design is to provide passive assistance to a user by gravity balancing, while keeping the transmitted forces to the shoulder joints at a minimum. Consistent with this goal, this paper discusses: analytical gravity balancing design conditions for the structure of the exoskeleton; a possible implementation of these conditions into practical designs; the minimization of transmitted joint forces to the shoulder while satisfying the gravity balancing conditions; the numerical optimization of the system for gravity balancing and minimization of transmitted forces; and the effect of parameter variation on joint moments and joint forces via numerical optimization. An implementation of the design was undertaken using zero-free-length springs. The design idea presented in this paper may be useful in relieving the actuators effort of exoskeletons to support the weight of the arm and therefore the possibility of using small actuators and making the system light and portable or even a stand-alone passive support device can be developed based on these gravity balancing conditions.

Weight-Perception-Based Novel Control of a Power-Assist Robot for the Cooperative Lifting of Light-Weight Objects

We developed a 1-DOF power assist robot system for lifting objects by two humans cooperatively. We hypothesized that weight perception due to inertia might be different from that due to gravity when lifting an object with power-assist because the perceived weight differs from the actual weight. The system was simulated and two humans cooperatively lifted objects with it. We analyzed human features such as weight perception, load forces, motions etc. We found that the robot reduced the perceived weights to 25% of the actual weights, and the load forces were 8 times larger than the actual requirements. The excessive load forces resulted in excessive accelerations that jeopardized the performances. We then implemented a novel control based on the human features, which was such that a virtual mass exponentially declined from a large value to a small one when subjects lifted objects with the robot and the command velocity exceeded a threshold. The novel control reduced excessive load forces and accelerations and thus enhanced performances in terms of maneuverability, safety etc. The findings may be used to develop power assist robots for manipulating heavy objects in industries that may augment human's abilities and skills and may improve interactions between robots and users.

Advances in upper limb stroke rehabilitation: a technology push

Strokes affect thousands of people worldwide leaving sufferers with severe disabilities affecting their daily activities. In recent years, new rehabilitation techniques have emerged such as constraint-induced therapy, biofeedback therapy and robot-aided therapy. In particular, robotic techniques allow precise recording of movements and application of forces to the affected limb, making it a valuable tool for motor rehabilitation. In addition, robot-aided therapy can utilise visual cues conveyed on a computer screen to convert repetitive movement practice into an engaging task such as a game. Visual cues can also be used to control the information sent to the patient about exercise performance and to potentially address psychosomatic variables influencing therapy. This paper overviews the current state-of-the-art on upper limb robot-mediated therapy with a focal point on the technical requirements of robotic therapy devices leading to the development of upper limb rehabilitation techniques that facilitate reach-to-touch, fine motor control, whole-arm movements and promote rehabilitation beyond hospital stay. The reviewed literature suggest that while there is evidence supporting the use of this technology to reduce functional impairment, besides the technological push, the challenge ahead lies on provision of effective assessment of outcome and modalities that have a stronger impact transferring functional gains into functional independence.

Robot assisted treadmill training: mechanisms and training strategies

The rehabilitation engineering community is working towards the development of robotic devices that can assist during gait training of patients suffering from neurologic injuries such as stroke and spinal cord injuries (SCI). The field of robot assisted treadmill training has rapidly evolved during the last decade. The robotic devices can provide repetitive, systematic and prolonged gait training sessions. This paper presents a review of the treadmill based robotic gait training devices. An overview of design configurations and actuation methods used for these devices is provided. Training strategies designed to actively involve the patient in robot assisted treadmill training are studied. These training strategies assist the patient according to the level of disability and type of neurologic injury. Although the efficacy of these training strategies is not clinically proven, adaptive strategies may result in substantial improvements. We end our review with a discussion covering major advancements made at device design and training strategies level and potential challenges to the field.

Design and Optimization of a Cable Driven Upper Arm Exoskeleton

This paper outlines the design of a wearable upper arm exoskeleton that can be potentially used to assist and train arm movements of stroke survivors or subjects with weak musculature. In the last 10 years, a number of upper arm training devices have emerged. However, due to their size and weight, their use is restricted to clinics and research laboratories. Our proposed wearable exoskeleton builds upon our research experience in wire driven manipulators and design of rehabilitative systems. The exoskeleton consists of three main parts: (i) an inverted U-shaped cuff that rests on the shoulder, (ii) a cuff on the upper arm, and (iii) a cuff on the forearm. Six motors mounted on the shoulder cuff drive the cuffs on the upper arm and forearm with the use of cables. In order to assess the performance of this exoskeleton prior to use on humans, a laboratory test-bed has been developed where this exoskeleton is mounted on a model skeleton, instrumented with sensors to measure joint angles. This paper describes the design details of the exoskeleton and addresses the key issue of parameter optimization to achieve a useful workspace based on kinematic and kinetic models. The optimization results have also been motivated from activities of daily living.

Review of control strategies for robotic movement training after neurologic injury

There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies.

The effect of the GENTLE/s robot-mediated therapy system on arm function after stroke

OBJECTIVE

To evaluate the effect of robot-mediated therapy on arm dysfunction post stroke.

DESIGN

A series of single-case studies using a randomized multiple baseline design with ABC or ACB order. Subjects (n = 20) had a baseline length of 8, 9 or 10 data points. They continued measurement during the B - robot-mediated therapy and C - sling suspension phases.

SETTING

Physiotherapy department, teaching hospital.

SUBJECTS

Twenty subjects with varying degrees of motor and sensory deficit completed the study. Subjects attended three times a week, with each phase lasting three weeks.

INTERVENTIONS

In the robot-mediated therapy phase they practised three functional exercises with haptic and visual feedback from the system. In the sling suspension phase they practised three single-plane exercises. Each treatment phase was three weeks long.

MAIN MEASURES

The range of active shoulder flexion, the Fugl-Meyer motor assessment and the Motor Assessment Scale were measured at each visit.

RESULTS

Each subject had a varied response to the measurement and intervention phases. The rate of recovery was greater during the robot-mediated therapy phase than in the baseline phase for the majority of subjects. The rate of recovery during the robot-mediated therapy phase was also greater than that during the sling suspension phase for most subjects.

CONCLUSION

The positive treatment effect for both groups suggests that robot-mediated therapy can have a treatment effect greater than the same duration of non-functional exercises. Further studies investigating the optimal duration of treatment in the form of a randomized controlled trial are warranted.

A review of smart homes- present state and future challenges

In the era of information technology, the elderly and disabled can be monitored with numerous intelligent devices. Sensors can be implanted into their home for continuous mobility assistance and non-obtrusive disease prevention. Modern sensor-embedded houses, or smart houses, cannot only assist people with reduced physical functions but help resolve the social isolation they face. They are capable of providing assistance without limiting or disturbing the resident's daily routine, giving him or her greater comfort, pleasure, and well-being. This article presents an international selection of leading smart home projects, as well as the associated technologies of wearable/implantable monitoring systems and assistive robotics. The latter are often designed as components of the larger smart home environment. The paper will conclude by discussing future challenges of the domain.

A computational model of human-robot load sharing during robot-assisted arm movement training after stroke

An important goal in robot-assisted movement therapy after neurologic injury is to provide an optimal amount of mechanical assistance to patients as they complete motor tasks. This paper presents a computational model of how humans interact with robotic therapy devices for the task of lifting a load to a desired height. The model predicts that an adaptive robotic therapy device will take over performance of the lifting task if the human motor control system contains a slacking term (i.e. a term that tries to the reduce force output of the arm when error is small) but the robot does not. We present experimental data from people with a chronic stroke as they train with a robotic arm orthosis that confirms this prediction. We also show that incorporating a slacking term into the robot overcomes this problem, increasing load sharing by the patient while still keeping kinematic errors small. These results provide insight into the computational mechanisms of human motor adaptation during rehabilitation therapy, and provide a framework for optimizing robot-assisted therapy.

Robot-aided rehabilitation of neural function in the upper extremities

Repetitive movements can improve muscle strength and movement coordination in patients with neurological disorders and impairments. Robot-aided approaches can serve to enhance the rehabilitation process. They can not only improve the therapeutic outcome but also support clinical evaluation and increase the patient motivation. This chapter provides an overview of existing systems that can support the movement therapy of the upper extremities in subjects with neurological pathologies. The devices are compared with respect to technical function, clinical applicability, and clinical outcomes.

Assessing and inducing neuroplasticity with transcranial magnetic stimulation and robotics for motor function

OBJECTIVES

To describe 2 new ways of assessing and inducing neuroplasticity in the human brain--transcranial magnetic stimulation (TMS) and robotics--and to investigate and promote the recovery of motor function after brain damage.

DATA SOURCES

We identified recent articles and books directly bearing on TMS and robotics. Articles using these tools for purposes other than rehabilitation were excluded. From these studies, we emphasize the methodologic and technical details of these tools as applicable for assessing and inducing plasticity.

STUDY SELECTION

Because both tools have only recently been used for rehabilitation, the majority of the articles selected for this review have been published only within the last 10 years.

DATA EXTRACTION

We used the PubMed and Compendex databases to find relevant peer-reviewed studies for this review. The studies were required to be relevant to rehabilitation and to use TMS or robotics methodologies. Guidelines were applied via independent extraction by multiple observers.

DATA SYNTHESIS

Despite the limited amount of research using these procedures for assessing and inducing neuroplasticity, there is growing evidence that both TMS and robotics can be very effective, inexpensive, and convenient ways for assessing and inducing rehabilitation. Although TMS has primarily been used as an assessment tool for motor function, an increasing number of studies are using TMS as a tool to directly induce plasticity and improve motor function. Similarly, robotic devices have been used for rehabilitation because of their suitability for delivery of highly repeatable training. New directions in robotics-assisted rehabilitation are taking advantage of novel measurements that can be acquired via the devices, enabling unique methods of assessment of motor recovery.

CONCLUSIONS

As refinements in technology and advances in our knowledge continue, TMS and robotics should play an increasing role in assessing and promoting the recovery of function. Ongoing and future studies combining TMS and robotics within the same populations may prove fruitful for a more detailed and comprehensive assessment of the central and peripheral changes in the nervous system during precisely induced recovery.

Therapeutic Robotics: A Technology Push: Stroke rehabilitation is being aided by robots that guide movement of shoulders and elbows, wrists, hands, arms and ankles to significantly improve recovery of patients

In this paper, we present a retrospective and chronological review of our efforts to revolutionize the way physical medicine is practiced by developing and deploying therapeutic robots. We present a sample of our clinical results with well over 300 stroke patients, both inpatients and outpatients, proving that movement therapy has a measurable and significant impact on recovery following brain injury. Bolstered by this result, we embarked on a two-pronged approach: 1) to determine what constitutes best therapy practice and 2) to develop additional therapeutic robots. We review our robots developed over the past 15 years and their unique characteristics. All are configured both to deliver reproducible therapy but also to measure outcomes with minimal encumbrance, thus providing critical measurement tools to help unravel the key question posed under the first prong: what constitutes "best practice"? We believe that a "gym" of robots like these will become a central feature of physical medicine and the rehabilitation clinic within the next ten years.

Robot-aided neurorehabilitation of the upper extremities

Task-oriented repetitive movements can improve muscle strength and movement co-ordination in patients with impairments due to neurological lesions. The application of robotics and automation technology can serve to assist, enhance, evaluate and document the rehabilitation of movements. The paper provides an overview of existing devices that can support movement therapy of the upper extremities in subjects with neurological pathologies. The devices are critically compared with respect to technical function, clinical applicability, and, if they exist, clinical outcomes.

The smart house for older persons and persons with physical disabilities: structure, technology arrangements, and perspectives

Smart houses are considered a good alternative for the independent life of older persons and persons with disabilities. Numerous intelligent devices, embedded into the home environment, can provide the resident with both movement assistance and 24-h health monitoring. Modern home-installed systems tend to be not only physically versatile in functionality but also emotionally human-friendly, i.e., they may be able to perform their functions without disturbing the user and without causing him/her any pain, inconvenience, or movement restriction, instead possibly providing him/her with comfort and pleasure. Through an extensive survey, this paper analyzes the building blocks of smart houses, with particular attention paid to the health monitoring subsystem as an important component, by addressing the basic requirements of various sensors implemented from both research and clinical perspectives. The paper will then discuss some important issues of the future development of an intelligent residential space with a human-friendly health monitoring functional system.

Robotics, motor learning, and neurologic recovery

Robotic devices are helping shed light on human motor control in health and injury. By using robots to apply novel force fields to the arm, investigators are gaining insight into how the nervous system models its external dynamic environment. The nervous system builds internal models gradually by experience and uses them in combination with impedance and feedback control strategies. Internal models are robust to environmental and neural noise, generalized across space, implemented in multiple brain regions, and developed in childhood. Robots are also being used to assist in repetitive movement practice following neurologic injury, providing insight into movement recovery. Robots can haptically assess sensorimotor performance, administer training, quantify amount of training, and improve motor recovery. In addition to providing insight into motor control, robotic paradigms may eventually enhance motor learning and rehabilitation beyond the levels possible with conventional training techniques.

Robot-assisted arm trainer for the passive and active practice of bilateral forearm and wrist movements in hemiparetic subjects

OBJECTIVE

To determine whether use of a robotic arm trainer for bilateral exercise in daily repetitive training for a 3-week period reduced spasticity and improved motor control in the arm of severely affected, chronic hemiparetic subjects.

DESIGN

Before-after trial.

SETTING

Community rehabilitation center in Germany.

PARTICIPANTS

Consecutive sample of 12 chronic hemiparetic patients; minimum stroke interval 6 months; patients could maximally protract the affected shoulder, hold the extended arm, or slightly flex and extend the elbow.

INTERVENTIONS

Additional daily therapy of 15 minutes with the arm trainer for 3 weeks; the 1 degree of freedom trainer enabled the bilateral passive and active practice of a forearm pronation and supination and wrist dorsiflexion and volarflexion; impedance control guaranteed a smooth movement.

MAIN OUTCOME MEASURES

Patients' impressions, the Modified Ashworth Scale (MAS) score (range, 0-5) to assess spasticity, and the arm section of the Rivermead Motor Assessment (RMA) score (range, 0-15) to assess motor control were rated before therapy, after each 3-week interval, and at follow-up 3 months later.

RESULTS

All patients had favorable impressions: the extremity felt more vivid, and 8 subjects noticed a reduction in spasticity, an ease of hand hygiene, and pain relief. The MAS score of the wrist and fingers joints decreased significantly (P<.0125) from a median of 3 (2-3) and 3 (3-4) to 2 (1-2) and 2.5 (2-3). The RMA score minimally increased in 5 cases without improvement in functional tasks. The median RMA score before therapy was 2.0 (1-2) and 2.0 (1-3.75) after therapy. There were no side effects. At follow-up, the effects had waned.

CONCLUSIONS

The arm trainer made possible intensive bilateral elbow and wrist training of severely affected stroke patients. Future studies should address the treatment effect in subacute stroke patients and determine the optimum treatment intensity.

Robotics in the rehabilitation treatment of patients with stroke

Stroke is the leading cause of permanent disability despite continued advances in prevention and novel interventional treatments. Post-stroke neuro-rehabilitation programs teach compensatory strategies that alter the degree of permanent disability. Robotic devices are new tools for therapists to deliver enhanced sensorimotor training and concentrate on impairment reduction. Results from several groups have registered success in reducing impairment and increasing motor power with task-specific exercise delivered by the robotic devices. Enhancing the rehabilitation experience with task-specific repetitive exercise marks a different approach to the patient with stroke. The clinical challenge will be to streamline, adapt, and expand the robot protocols to accommodate healthcare economies, to determine which patients sustain the greatest benefit, and to explore the relationship between impairment reduction and disability level. With these new tools, therapists will measure aspects of outcome objectively and contribute to the emerging scientific basis of neuro-rehabilitation.

Is robot-aided sensorimotor training in stroke rehabilitation a realistic option?

Stroke is the leading cause of disability, despite continued advances in prevention and treatment techniques based on novel delivery of new fibrinolytic drugs. Improved medical treatment of the complications caused by acute stroke has contributed to decreased mortality, but 90% of the survivors have significant neurological deficits. Reducing the degree of permanent disability remains the goal of poststroke neuro-rehabilitation programs, and new approaches to impairment reduction through managing sensorimotor experience may contribute further to altering disability. Recent reports from a number of laboratories using enhanced sensorimotor training protocols, particularly those with robotic devices, have indicated modest success in reducing impairment and increasing motor power in the exercised limb of patients with stroke when compared with control individuals. Whether arming the therapist with new tools, especially robotic devices, to treat impairment is a realistic approach to modern interdisciplinary rehabilitation raises questions regarding the added value of impairment reduction, and under what conditions should scientific and clinical development of robotic studies continue.

Quantification of force abnormalities during passive and active-assisted upper-limb reaching movements in post-stroke hemiparesis

We evaluated a method for measuring abnormal upper-limb motor performance in post-stroke hemiparetic subjects. A servomechanism (MIME) moved the forearm in simple planar trajectories, directly controlling hand position and forearm orientation. Design specifications are presented, along with system performance data during an initial test of 13 stroke subjects with a wide range of impairment levels. Performance of subjects was quantified by measuring the forces and torques between the paretic limb and the servomechanism as the subjects relaxed (passive), or attempted to generate force in the direction of movement (active). During passive movements, the more severely impaired subjects resisted movement, producing higher levels of negative work than less-impaired subjects and neurologically normal controls. During active movements, the more severely impaired subjects produced forces with larger directional errors, and were less efficient in producing work. These metrics had significant test-retest repeatability. These motor performance metrics can potentially detect smaller within-subject changes than motor function scales. This method could complement currently used measurement tools for the evaluation of subjects during recovery from stroke, or during therapeutic interventions.