After Stroke Movement Impairments: A Review of Current Technologies for Rehabilitation

This chapter presents a review of the rehabilitation technologies for people who have suffered a stroke, comparing and analyzing the impact that these technologies have on their recovery in the short and long term. The problematic is presented, and motor impairments for upper and lower limbs are characterized. The goal of this chapter is to show novel trends and research for the assistance and treatment of motor impairment caused by strokes

Markerless Analysis of Upper Extremity Kinematics during Standardized Pediatric Assessment

Children with hemiplegic cerebral palsy experience reduced motor performance in the affected upper extremity and are typically evaluated based on degree of functional impairment using activity-based assessments such as the Shriners Hospitals for Children Upper Extremity Evaluation (SHUEE), a validated clinical measure, to describe performance prior to and following rehabilitative or surgical interventions. Evaluations rely on subjective therapist scoring techniques and lack sensitivity to detect change. Objective clinical motion analysis systems are an available but time-consuming and cost-intensive alternative, requiring uncomfortable application of markers to the patient. There is currently no available markerless, low-cost system that quantitatively assesses upper extremity kinematics to improve sensitivity of evaluation during standardized task performance. A motion analysis system was developed, using Microsoft Kinect hardware to track motion during broad arm and subtle hand and finger movements. Algorithms detected and recorded skeletal position and calculated angular kinematics. Lab-developed articulating hand model and elbow fixation devices were used to evaluate accuracy, intra-trial, and inter-trial reliability of the Kinect platform. Results of technical evaluation indicate reasonably accurate detection and differentiation between hand and arm positions. Twelve typically-developing adolescent subjects were tested to characterize and evaluate performance scores obtained from the SHUEE and Kinect motion analysis system. Feasibility of the platform was determined in terms of kinematics and as an enhancement of quantitative kinematic reporting to the SHUEE, and a population mean of typically developing subject kinematics obtained for future development of performance scoring algorithms. The system was observed to be easily operable and clinically effective in subject testing. The Kinect motion analysis platform developed to quantify upper extremity motion during standardized tasks is a low-cost, portable, accurate, and reliable system in kinematic reporting, and has demonstrated quality of results in both technical evaluation of the system and a study of its applicability to standardized task-based evaluation, but has hardware and software limitations which will be resolved in future improvements of the system. The SHUEE benefits from improved quantitative data, and the Kinect system provides enhanced sensitivity in clinical upper extremity analysis for children with hemiplegic cerebral palsy

Modeling & Analysis of Design Parameters for Portable Hand Orthoses to Assist Upper Motor Neuron Syndrome Impairments and Prototype Design

Wearable assistive robotics have the potential to address an unmet medical need of reducing disability in individuals with chronic hand impairments due to neurological trauma. Despite myriad prior works, few patients have seen the benefits of such devices. Following application experience with tendon-actuated soft robotic gloves and a collaborator\u27s orthosis with novel flat-spring actuators, we identified two common assumptions regarding hand orthosis design. The first was reliance on incomplete studies of grasping forces during activities of daily living as a basis for design criteria, leading to poor optimization. The second was a neglect of increases in muscle tone following neurological trauma, rendering most devices non-applicable to a large subset of the population. To address these gaps, we measured joint torques during activities of daily living with able-bodied subjects using dexterity representative of orthosis-aided motion. Next, we measured assistive torques needed to extend the fingers of individuals with increased flexor tone following TBI. Finally, we applied this knowledge to design a cable actuated orthosis for assisting finger extension, providing a basis for future work focused on an under-represented subgroup of patients

Effect of a mixed reality-based intervention on arm, hand, and finger function on chronic stroke

[EN] Background: Virtual and mixed reality systems have been suggested to promote motor recovery after stroke. Basing on the existing evidence on motor learning, we have developed a portable and low-cost mixed reality tabletop system that transforms a conventional table in a virtual environment for upper limb rehabilitation. The system allows intensive and customized training of a wide range of arm, hand, and finger movements and enables interaction with tangible objects, while providing audiovisual feedback of the participants' performance in gamified tasks. This study evaluates the clinical effectiveness and the acceptance of an experimental intervention with the system in chronic stroke survivors. Methods: Thirty individuals with stroke were included in a reversal (A-B-A) study. Phase A consisted of 30 sessions of conventional physical therapy. Phase B consisted of 30 training sessions with the experimental system. Both interventions involved flexion and extension of the elbow, wrist, and fingers, and grasping of different objects. Sessions were 45-min long and were administered three to five days a week. The body structures (Modified Ashworth Scale), functions (Motricity Index, Fugl-Meyer Assessment Scale), activities (Manual Function Test, Wolf Motor Function Test, Box and Blocks Test, Nine Hole Peg Test), and participation (Motor Activity Log) were assessed before and after each phase. Acceptance of the system was also assessed after phase B (System Usability Scale, Intrinsic Motivation Inventory). Results: Significant improvement was detected after the intervention with the system in the activity, both in arm function measured by the Wolf Motor Function Test (p < 0.01) and finger dexterity measured by the Box and Blocks Test (p < 0.01) and the Nine Hole Peg Test (p < 0.01); and participation (p < 0.01), which was maintained to the end of the study. The experimental system was reported as highly usable, enjoyable, and motivating. Conclusions: Our results support the clinical effectiveness of mixed reality interventions that satisfy the motor learning principles for upper limb rehabilitation in chronic stroke survivors. This characteristic, together with the low cost of the system, its portability, and its acceptance could promote the integration of these systems in the clinical practice as an alternative to more expensive systems, such as robotic instruments.The authors wish to thank the staff and patients of the Servicio de Neurorrehabilitación y Daño Cerebral de los Hospitales NISA for their involvement in the study. The authors also wish to thank the staff of LabHuman for their support in this project, especially Francisco Toledo and José Roda for their assistance. This study was funded in part by the Project TEREHA (IDI-20110844) and Project NeuroVR (TIN2013-44741-R) of the Ministerio de Economia y Competitividad of Spain, the Project Consolider-C (SEJ2006-14301/PSIC) of the Ministerio de Educacion y Ciencia of Spain, the "CIBER of Physiopathology of Obesity and Nutrition, an initiative of ISCIII", and the Excellence Research Program PROMETEO of the Conselleria de Educacion of Generalitat Valenciana (2008-157).Colomer Font, C.; Llorens Rodríguez, R.; Noé Sebastián, E.; Alcañiz Raya, ML. (2016). Effect of a mixed reality-based intervention on arm, hand, and finger function on chronic stroke. Journal of NeuroEngineering and Rehabilitation. 13:1-10. https://doi.org/10.1186/s12984-016-0153-6S11013Fregni F, Pascual-Leone A. Hand motor recovery after stroke: tuning the orchestra to improve hand motor function. Cogn Behav Neurol. 2006;19(1):21–33.Patten C, Condliffe EG, Dairaghi CA, Lum PS. 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Wearable Robotics for Impaired Upper-Limb Assistance and Rehabilitation: State of the Art and Future Perspectives

Despite more than thirty-five years of research on wearable technologies to assist the upper-limb and a multitude of promising preliminary results, the goal of restoring pre-impairment quality of life of people with physical disabilities has not been fully reached yet. Whether it is for rehabilitation or for assistance, nowadays robotics is still only used in a few high-tech clinics and hospitals, limiting the access to a small amount of people. This work provides a description of the three major 'revolutions' occurred in the field (end-effector robots, rigid exoskeletons, and soft exosuits), reviewing forty-eight systems for the upper-limb (excluding hand-only devices) used in eighty-nine studies enrolling a clinical population before June 2022. The review critically discusses the state of the art, analyzes the different technologies, and compares the clinical outcomes, with the goal of determine new potential directions to follow

Development and Biomechanical Analysis toward a Mechanically Passive Wearable Shoulder Exoskeleton

Shoulder disability is a prevalent health issue associated with various orthopedic and neurological conditions, like rotator cuff tear and peripheral nerve injury. Many individuals with shoulder disability experience mild to moderate impairment and struggle with elevating the shoulder or holding the arm against gravity. To address this clinical need, I have focused my research on developing wearable passive exoskeletons that provide continuous at-home movement assistance. Through a combination of experiments and computational tools, I aim to optimize the design of these exoskeletons. In pursuit of this goal, I have designed, fabricated, and preliminarily evaluated a wearable, passive, cam-driven shoulder exoskeleton prototype. Notably, the exoskeleton features a modular spring-cam-wheel module, allowing customizable assistive force to compensate for different proportions of the shoulder elevation moment due to gravity. The results of my research demonstrated that this exoskeleton, providing modest one-fourth gravity moment compensation at the shoulder, can effectively reduce muscle activity, including deltoid and rotator cuff muscles. One crucial aspect of passive shoulder exoskeleton design is determining the optimal anti-gravity assistance level. I have addressed this challenge using computational tools and found that an assistance level within the range of 20-30% of the maximum gravity torque at the shoulder joint yields superior performance for specific shoulder functional tasks. When facing a new task dynamic, such as wearing a passive shoulder exoskeleton, the human neuro-musculoskeletal system adapts and modulates limb impedance at the end-limb (i.e., hand) to enhance task stability. I have presented development and validation of a realistic neuromusculoskeletal model of the upper limb that can predict stiffness modulation and motor adaptation in response to newly introduced environments and force fields. Future studies will explore the model\u27s applicability in predicting stiffness modulation for 3D movements in novel environments, such as passive assistive devices\u27 force fields

Design and Control of Robotic Systems for Lower Limb Stroke Rehabilitation

Lower extremity stroke rehabilitation exhausts considerable health care resources, is labor intensive, and provides mostly qualitative metrics of patient recovery. To overcome these issues, robots can assist patients in physically manipulating their affected limb and measure the output motion. The robots that have been currently designed, however, provide assistance over a limited set of training motions, are not portable for in-home and in-clinic use, have high cost and may not provide sufficient safety or performance. This thesis proposes the idea of incorporating a mobile drive base into lower extremity rehabilitation robots to create a portable, inherently safe system that provides assistance over a wide range of training motions. A set of rehabilitative motion tasks were established and a six-degree-of-freedom (DOF) motion and force-sensing system was designed to meet high-power, large workspace, and affordability requirements. An admittance controller was implemented, and the feasibility of using this portable, low-cost system for movement assistance was shown through tests on a healthy individual. An improved version of the robot was then developed that added torque sensing and known joint elasticity for use in future clinical testing with a flexible-joint impedance controller

Evidence-informed discharge planning model for stroke rehabilitation

Stroke is a leading cause of long-term disability (Benjamin et al., 2017) and patients with this diagnosis have been found to have higher incidences of inappropriately long hospital lengths of stay (McDonagh, Smith, & Goddard, 2000). Generalist training in occupational therapy curriculum coupled with variable research utilization (Dysart & Tomlin, 2002; McKenna et al., 2005) leads to inconsistent methods of evaluation and decreased communication between providers across settings. Furthermore, there are currently no standardized discharge planning models or guidelines for clinicians to follow when evaluating patients or making recommendations (Ilett, Brock, Graven, & Cotton, 2010). An evidence-informed discharge planning model was created to address these issues. This model utilizes a multidisciplinary approach, with guidelines for selecting and administering evaluations to quantify a patient’s functional status. Assessments are clustered into four domains: activities of daily living, balance and mobility, cognition, and other (i.e. visual inattention, motor control and spasticity). These assessments supplement a basic patient evaluation, and results are used to guide clinical decision making regarding recommendations for the next level of care. Stroke rehabilitation and care cannot be standardized, but the methods used to select measures and make discharge recommendations should have distinct guidelines. By choosing from a core set of measures, clinicians can use a common “language” to describe patient function and measure progress across settings over time. This will ensure patients are discharged to the appropriate level of rehabilitation to optimize their recovery, and it will also help prevent excessively long hospital admissions