25 research outputs found

    A Robot based Hybrid Lower-Limb System for Assist-As-Needed Rehabilitation of Stroke Patients:Technical Evaluation and Clinical Feasibility

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    Background: Although early rehabilitation is important following a stroke, severely affected patients have limited options for intensive rehabilitation as they are often bedridden. To create a system for early rehabilitation of lower extremities in severely affected patients, we have combined the robotic manipulator ROBERT® and EMG-triggered FES and developed a novel user-driven Assist- As-Needed (AAN) control approach. The method is based on a state machine that can detect user movement capability and provide different levels of assistance, as required by the patient (no support, FES only, and simultaneous FES and mechanical support). Methods: To technically validate the system, we tested 10 able-bodied participants who were instructed to perform specific behaviors to trigger the desired system states while conducting knee extension and ankle dorsal flexion exercise. In addition, the system was tested on two stroke patients to establish the clinical feasibility. Results: The technical validation showed that the state machine correctly detected the participants’ behavior and activated the target AAN state in more than 96% of the exercise repetitions. The clinical feasibility test showed that the system successfully recognized the patients’ movement capacity and activated assistive states according to their needs, providing the minimal level of support required to perform the exercise successfully. Conclusions: The system was technically validated and preliminarily proven clinically feasible. The present study shows that the novel system can be used to deliver exercises with a high number of repetitions while engaging the participants’ residual capabilities through an effective AAN strategy.</p

    European evidence-based recommendations for clinical assessment of upper limb in neurorehabilitation (CAULIN): data synthesis from systematic reviews, clinical practice guidelines and expert consensus

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    Background: Technology-supported rehabilitation can help alleviate the increasing need for cost-effective rehabilitation of neurological conditions, but use in clinical practice remains limited. Agreement on a core set of reliable, valid and accessible outcome measures to assess rehabilitation outcomes is needed to generate strong evidence about effectiveness of rehabilitation approaches, including technologies. This paper collates and synthesizes a core set from multiple sources; combining existing evidence, clinical practice guidelines and expert consensus into European recommendations for Clinical Assessment of Upper Limb In Neurorehabilitation (CAULIN). Methods: Data from systematic reviews, clinical practice guidelines and expert consensus (Delphi methodology) were systematically extracted and synthesized using strength of evidence rating criteria, in addition to recommendations on assessment procedures. Three sets were defined: a core set: strong evidence for validity, reliability, responsiveness and clinical utility AND recommended by at least two sources; an extended set: strong evidence OR recommended by at least two sources and a supplementary set: some evidence OR recommended by at least one of the sources. Results: In total, 12 measures (with primary focus on stroke) were included, encompassing body function and activity level of the International Classification of Functioning and Health. The core set recommended for clinical practice and research: Fugl-Meyer Assessment of Upper Extremity (FMA-UE) and Action Research Arm Test (ARAT); the extended set recommended for clinical practice and/or clinical research: kinematic measures, Box and Block Test (BBT), Chedoke Arm Hand Activity Inventory (CAHAI), Wolf Motor Function Test (WMFT), Nine Hole Peg Test (NHPT) and ABILHAND; the supplementary set recommended for research or specific occasions: Motricity Index (MI); Chedoke-McMaster Stroke Assessment (CMSA), Stroke Rehabilitation Assessment Movement (STREAM), Frenchay Arm Test (FAT), Motor Assessment Scale (MAS) and body-worn movement sensors. Assessments should be conducted at pre-defined regular intervals by trained personnel. Global measures should be applied within 24 h of hospital admission and upper limb specific measures within 1 week. Conclusions: The CAULIN recommendations for outcome measures and assessment procedures provide a clear, simple, evidence-based three-level structure for upper limb assessment in neurological rehabilitation. Widespread adoption and sustained use will improve quality of clinical practice and facilitate meta-analysis, critical for the advancement of technology-supported neurorehabilitation.The European Network on Robotics for NeuroRehabilitation (Working Group 1) developed these recommendations. Their work was funded by the European Co-Operation in Science and Technology (COST Action TD1006) programme. The funding body had no role in or infuence on the selected approach and synthesis, analysis, and interpretation of data and in writing the manuscript

    Six weeks Use of a Wearable Soft-robotic Glove During ADL:Preliminary Results of Ongoing Clinical Study

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    In this ongoing study, an assistive wearable soft-robotic glove, named Carbonhand, is tested at home for 6 weeks by subjects with decreased handgrip strength to receive a first insight in the therapeutic effect of using this assistive grip-supporting glove during ADLs. Preliminary results of the first 13 participants showed that participants appreciated use of the glove to assist them with daily life activities. Even more, grip strength without glove improved and functional performance showed increases as well. These preliminary findings hold promise for observing a clinical effect of using the soft-robotic glove as assistance in ADLs upon completion of data collection

    Assessing effects of exoskeleton misalignment on knee joint load during swing using an instrumented leg simulator

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    Background: Exoskeletons are working in parallel to the human body and can support human movement by exerting forces through cuffs or straps. They are prone to misalignments caused by simplified joint mechanics and incorrect fit or positioning. Those misalignments are a common safety concern as they can cause undesired interaction forces. However, the exact mechanisms and effects of misalignments on the joint load are not yet known. The aim of this study was therefore to investigate the influence of different directions and magnitudes of exoskeleton misalignment on the internal knee joint forces and torques of an artificial leg. Methods: An instrumented leg simulator was used to quantify the changes in knee joint load during the swing phase caused by misalignments of a passive knee brace being manually flexed. This was achieved by an experimenter pulling on a rope attached to the distal end of the knee brace to create a flexion torque. The extension was not actuated but achieved through the weight of the instrumented leg simulator. The investigated types of misalignments are a rotation of the brace around the vertical axis and a translation in anteroposterior as well as proximal/distal direction. Results: The amount of misalignment had a significant effect on several directions of knee joint load in the instrumented leg simulator. In general, load on the knee joint increased with increasing misalignment. Specifically, stronger rotational misalignment led to higher forces in mediolateral direction in the knee joint as well as higher ab-/adduction, flexion and internal/external rotation torques. Stronger anteroposterior translational misalignment led to higher mediolateral knee forces as well as higher abduction and flexion/extension torques. Stronger proximal/distal translational misalignment led to higher posterior and tension/compression forces. Conclusions: Misalignments of a lower leg exoskeleton can increase internal knee forces and torques during swing to a multiple of those experienced in a well-aligned situation. Despite only taking swing into account, this is supporting the need for carefully considering hazards associated with not only translational but also rotational misalignments during wearable robot development and use. Also, this warrants investigation of misalignment effects in stance, as a target of many exoskeleton applications

    Prototype measuring device for assessing interaction forces between human limbs and rehabilitation robots - A proof of concept study

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    Rehabilitation robots can provide high intensity and dosage training or assist patients in activities of daily living and decrease physical strain on clinicians. However, the physical human robot interaction poses a major safety issue, as the close physical contact between user and robot can lead to injuries. Moreover, the magnitude of forces as well as best practices for measuring them, are widely unknown. Therefore, a measurement setup was developed to assess normal and tangential forces that occur in the contact area between an arm and a splint. Force sensitive resistors and a force / torque sensor were combined with two different splint shapes. Initial experiments indicated that the setup gives some insight into magnitudes and distribution of normal forces on the splint-forearm-interface. Experiment results show a dependency of force distributions on the splint shape and sensor locations. Based on these outcomes, we proposed an improved setup for subsequent investigations

    Safety Assessment of Rehabilitation Robots: A Review Identifying Safety Skills and Current Knowledge Gaps

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    International audienceThe assessment of rehabilitation robot safety is a vital aspect of the development process, which is often experienced as difficult. There are gaps in best practices and knowledge to ensure safe usage of rehabilitation robots. Currently, safety is commonly assessed by monitoring adverse events occurrence. The aim of this article is to explore how safety of rehabilitation robots can be assessed early in the development phase, before they are used with patients. We are suggesting a uniform approach for safety validation of robots closely interacting with humans, based on safety skills and validation protocols. Safety skills are an abstract representation of the ability of a robot to reduce a specific risk or deal with a specific hazard. They can be implemented in various ways, depending on the application requirements, which enables the use of a single safety skill across a wide range of applications and domains. Safety validation protocols have been developed that correspond to these skills and consider domain-specific conditions. This gives robot users and developers concise testing procedures to prove the mechanical safety of their robotic system, even when the applications are in domains with a lack of standards and best practices such as the healthcare domain. Based on knowledge about adverse events occurring in rehabilitation robot use, we identified multi-directional excessive forces on the soft tissue level and musculoskeletal level as most relevant hazards for rehabilitation robots and related them to four safety skills, providing a concrete starting point for safety assessment of rehabilitation robots. We further identified a number of gaps which need to be addressed in the future to pave the way for more comprehensive guidelines for rehabilitation robot safety assessments. Predominantly, besides new developments of safety by design features, there is a strong need for reliable measurement methods as well as acceptable limit values for human-robot interaction forces both on skin and joint level

    Occurrence and Type of Adverse Events During the Use of Stationary Gait Robots—A Systematic Literature Review

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    Robot-assisted gait training (RAGT) devices are used in rehabilitation to improve patients' walking function. While there are some reports on the adverse events (AEs) and associated risks in overground exoskeletons, the risks of stationary gait trainers cannot be accurately assessed. We therefore aimed to collect information on AEs occurring during the use of stationary gait robots and identify associated risks, as well as gaps and needs, for safe use of these devices. We searched both bibliographic and full-text literature databases for peer-reviewed articles describing the outcomes of stationary RAGT and specifically mentioning AEs. We then compiled information on the occurrence and types of AEs and on the quality of AE reporting. Based on this, we analyzed the risks of RAGT in stationary gait robots. We included 50 studies involving 985 subjects and found reports of AEs in 18 of those studies. Many of the AE reports were incomplete or did not include sufficient detail on different aspects, such as severity or patient characteristics, which hinders the precise counts of AE-related information. Over 169 device-related AEs experienced by between 79 and 124 patients were reported. Soft tissue-related AEs occurred most frequently and were mostly reported in end-effector-type devices. Musculoskeletal AEs had the second highest prevalence and occurred mainly in exoskeleton-type devices. We further identified physiological AEs including blood pressure changes that occurred in both exoskeleton-type and end-effector-type devices. Training in stationary gait robots can cause injuries or discomfort to the skin, underlying tissue, and musculoskeletal system, as well as unwanted blood pressure changes. The underlying risks for the most prevalent injury types include excessive pressure and shear at the interface between robot and human (cuffs/harness), as well as increased moments and forces applied to the musculoskeletal system likely caused by misalignments (between joint axes of robot and human). There is a need for more structured and complete recording and dissemination of AEs related to robotic gait training to increase knowledge on risks. With this information, appropriate mitigation strategies can and should be developed and implemented in RAGT devices to increase their safety

    Detection thresholds for electrostimulation combined with robotic leg support in sub-acute stroke patients

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    Stroke is one of the leading causes of disability in adults in the European Union. It often leads to motor impairments, such as a hemiparetic lower extremity. Research indicates that early task-specific and intensive training promotes neuroplasticity and leads to recovery and/or compensation. One way to provide intensive training early after a stroke is via robot-supported training. A rehabilitation robot was designed by Life Science Robotics (Aalborg, Denmark) that can provide continuous repetitive movements of the hip, knee, and/or ankle in e.g., a lying position. In order to emphasize active contribution by the patient, actively triggered electrical stimulation (via muscle activation) can be combined with robotic assistance. The current study aims to compare different threshold estimation methods for detection of movement intention from muscle activity for actively triggered electrical stimulation during robot-supported leg movement in stroke patients. Three sub-acute stroke patients were included for a single measurement session. They performed knee extension and/or ankle dorsal flexion with four different threshold estimation methods to assess the intention detection threshold to initiate electrostimulation. The thresholds were based on the resting level of muscle activity (of m. rectus femoris or m. tibialis anterior) plus two or three times the standard deviation of the average resting value, or the resting level plus 5% or 10% of the peak muscle activity during a maximal voluntary contraction. The results showed that the method based on the resting muscle activity plus two times the standard deviation was the most stable across the three included stroke patients. This method had a detection success rate of 86.7% and was experienced as moderately comfortable. In conclusion, performing knee extension and/or ankle dorsal flexion with electromyography triggered electrostimulation is feasible in sub-acute stroke patients. Muscle activity-triggered electrostimulation combined with robotic support based on a threshold of resting levels plus two times the standard deviation seems to detect movement initiation most consistently in this small sample of sub-acute stroke patients
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