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Bilateral proprioception includes the ability to sense the position and motion of one hand relative to the other, without looking. This sensory ability allows us to perform daily activities seamlessly, and its impairment is observed in various neurological disorders such as cerebral palsy and stroke. It can undergo experience-dependent plasticity, as seen in trained piano players. If its neural correlates were better understood, it would provide a useful assay and target for neurorehabilitation for people with impaired proprioception. We designed a non-invasive electroencephalography-based paradigm to assess the neural features relevant to proprioception, especially focusing on bilateral proprioception, i.e., assessing the limb distance from the body with the other limb. We compared it with a movement-only task, with and without the visibility of the target hand. Additionally, we explored proprioceptive accuracy during the tasks. We tested eleven Controls and nine Skilled musicians to assess whether sensorimotor event-related spectral perturbations in µ (8-12Hz) and low-ß (12-18Hz) rhythms differ in people with musical instrument training, which intrinsically involves a bilateral proprioceptive component, or when new sensor modalities are added to the task. The Skilled group showed significantly reduced µ and low-ß suppression in bilateral tasks compared to movement-only, a significative difference relative to Controls. This may be explained by reduced top-down control due to intensive training, despite this, proprioceptive errors were not smaller for this group. Target visibility significantly reduced proprioceptive error in Controls, while no change was observed in the Skilled group. During visual tasks, Controls exhibited significant µ and low-ß power reversals, with significant differences relative to proprioceptive-only tasks compared to the Skilled group-possibly due to reduced uncertainty and top-down control. These results provide support for sensorimotor µ and low-ß suppression as potential neuromarkers for assessing proprioceptive ability. The identification of these features is significant as they could be used to quantify altered proprioceptive neural processing in skill and movement disorders. This in turn can be useful as an assay for pre and post sensory-motor intervention research.
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Propiocepción , Extremidad Superior , Humanos , Movimiento , Mano , ElectroencefalografíaRESUMEN
This paper presents an experimental comparison of multiple admittance control dynamic models implemented on a five-degree-of-freedom arm exoskeleton. The performance of each model is evaluated for transparency, stability, and impact on point-to-point reaching. Although ideally admittance control would render a completely transparent environment for physical human-robot interaction (pHRI), in practice, there are trade-offs between transparency and stability-both of which can detrimentally impact natural arm movements. Here we test four admittance modes: 1) Low-Mass: low inertia with zero damping; 2) High-Mass: high inertia with zero damping; 3) Velocity-Damping: low inertia with damping; and 4) a novel Velocity-Error-Damping: low inertia with damping based on velocity error. A single subject completed two experiments: 1) 20 repetitions of a single reach-and-return, and 2) two repetitions of reach-and-return to 13 different targets. The results suggest that the proposed novel Velocity-Error-Damping model improves transparency the most, achieving a 70% average reduction of vibration power vs. Low-Mass, while also reducing user effort, with less impact on spatial/temporal accuracy than alternate modes. Results also indicate that different models have unique situational advantages so selecting between them may depend on the goals of the specific task (i.e., assessment, therapy, etc.). Future work should investigate merging approaches or transitioning between them in real-time.
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Dispositivo Exoesqueleto , Robótica , Humanos , Robótica/métodos , Algoritmos , Movimiento (Física) , MovimientoRESUMEN
This paper presents the kinematic design and development of a two degree-of-freedom (2DOF) spherical 5-bar thumb exoskeleton to augment the finger individuating grasp exercise robot (FINGER) rehabilitation robot, which assists the index and middle fingers individually in naturalistic grasping. The thumb module expands the capabilities of FINGER, allowing for broader proprioceptive training and assessment of hand function. The design process started by digitizing thumb-grasping motions to the index and the middle fingers separately, recorded from multiple healthy subjects utilizing a motion capture system. Fitting spheres to trajectory data of each subject allowed normalization of all subjects' data to a common center and radius. A two-revolute joint serial-chain mechanism was synthesized (intermediate optimization step) to reach the normalized trajectories. Next, the two resulting grasping trajectories were spatially sampled as targets for the 2DOF spherical 5-bar synthesis. Optimization of the spherical 5-bar included symmetry constraints and cost-function penalties for poor manipulability. The resulting exoskeleton assists both flexion/extension and abduction/adduction of the thumb enabling a wide range of motions. Consistent with FINGER, the parallel structure of the spherical 5-bar places the actuators at the base of the module, allowing for desirable characteristics, including high backdrivability, high controllable bandwidth, and low mechanical impedance. The mechanical design was developed from the kinematic solution, including an adjustable thumb cuff to accommodate different hand sizes. Fit and function of the device were tested on multiple subjects, including survivors of stroke. A proportional-derivative force controller with gravity and friction compensation was implemented to reduce resistance to motion during subject testing.
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BACKGROUND: Significant clinician training is required to mitigate the subjective nature and achieve useful reliability between measurement occasions and therapists. Previous research supports that robotic instruments can improve quantitative biomechanical assessments of the upper limb, offering reliable and more sensitive measures. Furthermore, combining kinematic and kinetic measurements with electrophysiological measurements offers new insights to unlock targeted impairment-specific therapy. This review presents common methods for analyzing biomechanical and neuromuscular data by describing their validity and reporting their reliability measures. METHODS: This paper reviews literature (2000-2021) on sensor-based measures and metrics for upper-limb biomechanical and electrophysiological (neurological) assessment, which have been shown to correlate with clinical test outcomes for motor assessment. The search terms targeted robotic and passive devices developed for movement therapy. Journal and conference papers on stroke assessment metrics were selected using PRISMA guidelines. Intra-class correlation values of some of the metrics are recorded, along with model, type of agreement, and confidence intervals, when reported. RESULTS: A total of 60 articles are identified. The sensor-based metrics assess various aspects of movement performance, such as smoothness, spasticity, efficiency, planning, efficacy, accuracy, coordination, range of motion, and strength. Additional metrics assess abnormal activation patterns of cortical activity and interconnections between brain regions and muscle groups; aiming to characterize differences between the population who had a stroke and the healthy population. CONCLUSION: Range of motion, mean speed, mean distance, normal path length, spectral arc length, number of peaks, and task time metrics have all demonstrated good to excellent reliability, as well as provide a finer resolution compared to discrete clinical assessment tests. EEG power features for multiple frequency bands of interest, specifically the bands relating to slow and fast frequencies comparing affected and non-affected hemispheres, demonstrate good to excellent reliability for populations at various stages of stroke recovery. Further investigation is needed to evaluate the metrics missing reliability information. In the few studies combining biomechanical measures with neuroelectric signals, the multi-domain approaches demonstrated agreement with clinical assessments and provide further information during the relearning phase. Combining the reliable sensor-based metrics in the clinical assessment process will provide a more objective approach, relying less on therapist expertise. This paper suggests future work on analyzing the reliability of metrics to prevent biasedness and selecting the appropriate analysis.
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Rehabilitación de Accidente Cerebrovascular , Accidente Cerebrovascular , Humanos , Rehabilitación de Accidente Cerebrovascular/métodos , Fenómenos Biomecánicos , Reproducibilidad de los Resultados , Accidente Cerebrovascular/diagnóstico , Extremidad Superior , ElectroencefalografíaRESUMEN
Stroke is one of the leading causes of impairment in the world. Many of those who have suffered a stroke experience long-term loss of upper-limb function as a result. BLUE SABINO is an exoskeleton device being developed at the University of Idaho to help assess these patients and aid in their rehabilitation. One of the central design challenges with exoskeletons is limiting the overall weight of the device. Motors used in actuation of these devices are often oversized to allow gravity balancing of the device and user and the creation of torques to facilitate patient movements. If the torques required for gravity balancing are achieved through elastic elements, the motor and other upstream components can be lighter, potentially greatly reducing the overall weight of the device. In this paper, constant-force springs may provide an effective method of generating a constant offsetting torque to compensate for gravity. In experimental testing of multiple mounting configurations of C-shaped constant-force springs (single, back-to-back, double-wrapped), the force output fluctuated less than 8.6% over 180° of wrapping, with friction values below 2.6%, validating the viability of constant-force springs for this application. The results suggest the back-to-back configuration provides a simpler implementation with better force consistency while the double-wrapped configuration adds less friction to the system.
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Diseño de Equipo , Dispositivo Exoesqueleto , Gravitación , Aparatos Ortopédicos , Robótica , Accidente Cerebrovascular , Fenómenos Biomecánicos , HumanosRESUMEN
Background. Proprioception of fingers is essential for motor control. Reduced proprioception is common after stroke and is associated with longer hospitalization and reduced quality of life. Neural correlates of proprioception deficits after stroke remain incompletely understood, partly because of weaknesses of clinical proprioception assessments. Objective. To examine the neural basis of finger proprioception deficits after stroke. We hypothesized that a model incorporating both neural injury and neural function of the somatosensory system is necessary for delineating proprioception deficits poststroke. Methods. Finger proprioception was measured using a robot in 27 individuals with chronic unilateral stroke; measures of neural injury (damage to gray and white matter, including corticospinal and thalamocortical sensory tracts), neural function (activation of and connectivity of cortical sensorimotor areas), and clinical status (demographics and behavioral measures) were also assessed. Results. Impairment in finger proprioception was present contralesionally in 67% and bilaterally in 56%. Robotic measures of proprioception deficits were more sensitive than standard scales and were specific to proprioception. Multivariable modeling found that contralesional proprioception deficits were best explained (r2 = 0.63; P = .0006) by a combination of neural function (connectivity between ipsilesional secondary somatosensory cortex and ipsilesional primary motor cortex) and neural injury (total sensory system injury). Conclusions. Impairment of finger proprioception occurs frequently after stroke and is best measured using a quantitative device such as a robot. A model containing a measure of neural function plus a measure of neural injury best explained proprioception performance. These measurements might be useful in the development of novel neurorehabilitation therapies.
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Dedos/fisiopatología , Propiocepción , Accidente Cerebrovascular/fisiopatología , Adulto , Anciano , Femenino , Sustancia Gris/diagnóstico por imagen , Sustancia Gris/fisiopatología , Humanos , Imagen por Resonancia Magnética , Masculino , Persona de Mediana Edad , Corteza Motora/diagnóstico por imagen , Corteza Motora/fisiopatología , Robótica , Corteza Somatosensorial/diagnóstico por imagen , Corteza Somatosensorial/fisiopatología , Trastornos Somatosensoriales/diagnóstico por imagen , Trastornos Somatosensoriales/fisiopatología , Accidente Cerebrovascular/diagnóstico por imagen , Rehabilitación de Accidente Cerebrovascular , Sustancia Blanca/diagnóstico por imagen , Sustancia Blanca/fisiopatologíaRESUMEN
OBJECTIVE: To test the hypothesis that, in the context of robotic therapy designed to enhance proprioceptive feedback via a Hebbian model, integrity of both somatosensory and motor systems would be important in understanding interparticipant differences in treatment-related motor gains. METHODS: In 30 patients with chronic stroke, behavioral performance, neural injury, and neural function were quantified for somatosensory and motor systems. Patients then received a 3-week robot-based therapy targeting finger movements with enhanced proprioceptive feedback. RESULTS: Hand function improved after treatment (Box and Blocks score increase of 2.8 blocks, p = 0.001) but with substantial variability: 9 patients showed improvement exceeding the minimal clinically important difference (6 blocks), while 8 patients (all of whom had >2-SD greater proprioception deficit compared to 25 healthy controls) showed no improvement. In terms of baseline behavioral assessments, a somatosensory measure (finger proprioception assessed robotically) best predicted treatment gains, outperforming all measures of motor behavior. When the neural basis underlying variability in treatment response was examined, somatosensory-related variables were again the strongest predictors. A multivariate model combining total sensory system injury and sensorimotor cortical connectivity (between ipsilesional primary motor and secondary somatosensory cortices) explained 56% of variance in treatment-induced hand functional gains (p = 0.002). CONCLUSIONS: Measures related to the somatosensory network best explained interparticipant differences in treatment-related hand function gains. These results underscore the importance of baseline somatosensory integrity for improving hand function after stroke and provide insights useful for individualizing rehabilitation therapy. CLINICALTRIALSGOV IDENTIFIER: NCT02048826.
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Corteza Cerebral/fisiopatología , Dedos , Propiocepción , Accidente Cerebrovascular/fisiopatología , Accidente Cerebrovascular/terapia , Adulto , Anciano , Corteza Cerebral/diagnóstico por imagen , Electroencefalografía , Retroalimentación , Femenino , Dedos/fisiopatología , Humanos , Imagen por Resonancia Magnética , Masculino , Persona de Mediana Edad , Propiocepción/fisiología , Tractos Piramidales/diagnóstico por imagen , Tractos Piramidales/fisiopatología , Recuperación de la Función/fisiología , Robótica , Accidente Cerebrovascular/diagnóstico por imagen , Resultado del Tratamiento , Adulto JovenRESUMEN
Design of an upper-arm exoskeleton requires knowledge of human operational ranges and workspace distributions. Motion capture recordings of right-arm motion during common tasks, known as activities of daily living (ADLs), are taken to represent a plausible workspace for an exoskeleton. An inverse kinematic model of BLUE SABINO (BiLateral Upper-extremity Exoskeleton for Simultaneous Assessment of Biomechanical and Neuromuscular Output), driven by ADL data is established to map right-arm joint locations to exoskeleton motor joint space. A kinematic representation of a human right-arm driven by ADL data is implemented via a vector analysis utilizing quaternion rotation/translation and used to visualize ADL recordings. A model of the BLUE SABINO exoskeleton whose motion is driven by the mapped motorjoint-space data is used to validate the mapping graphically. The available ADL database is mapped to motor joint space. Motor position distributions are generated from the resulting dataset and estimates of robot range of motion, (ROM) and statistics for shoulder motor positions are established. A kinematically and inertially accurate model of the BLUE SABINO is developed by exporting SolidWorksOR part models into SimScape Multibody (MathWorks). The model is used to produce operational torque estimates for shoulder motors. Initial simulations indicate that the motors of interest have been properly sized.
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Actividades Cotidianas , Hombro , Fenómenos Biomecánicos , Humanos , Rango del Movimiento Articular , Extremidad SuperiorRESUMEN
OBJECTIVE: The goal of this study was to determine the relative contributions of finger weakness and reduced finger individuation to reduced hand function after stroke, and their association with corticospinal tract (CST) injury. METHODS: We measured individuated and synergistic maximum voluntary contractions (MVCs) of the index and middle fingers, in both flexion and extension, of 26 individuals with a chronic stroke using a robotic exoskeleton. We quantified finger strength and individuation, and defined a novel metric that combines them - "multifinger capacity". We used stepwise linear regression to identify which measure best predicted hand function (Box and Blocks Test, Nine Hole Peg Test) and arm impairment (the Upper Extremity Fugl-Meyer Test). RESULTS: Compared to metrics of strength or individuation, capacity survived the stepwise regression as the strongest predictor of hand function and arm impairment. Capacity was also most strongly related to presence or absence of lesion overlap with the CST. CONCLUSIONS: Reduced strength and individuation combine to shrink the space of achievable finger torques, and it is the resulting size of this space - the multifinger capacity - that is of elevated importance for predicting loss of hand function. SIGNIFICANCE: Multi-finger capacity may be an important target for rehabilitative hand training.
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Dispositivo Exoesqueleto , Dedos/fisiología , Fuerza de la Mano/fisiología , Tractos Piramidales/lesiones , Tractos Piramidales/fisiología , Accidente Cerebrovascular/fisiopatología , Adulto , Anciano , Femenino , Humanos , Masculino , Persona de Mediana Edad , Contracción Muscular/fisiología , Accidente Cerebrovascular/diagnóstico , Rehabilitación de Accidente Cerebrovascular/métodos , Adulto JovenRESUMEN
INTRODUCTION: This study is aimed at developing a task-based methodology for the design of robotic exoskeletons. This is in contrast to prevailing research efforts, which attempt to mimic the human limb, where each human joint is given an exoskeleton counter-joint. Rather, we present an alternative systematic design approach for the design of exoskeletons that can follow the complex three-dimensional motions of the human body independent of anatomical measures and landmarks. With this approach, it is not necessary to know the geometry of the targeted limb but rather to have a description of its motion at the point of attachment. METHODS: The desired trajectory of the targeted limb has been collected through a motion capture system from a healthy subject. Then, an approximate dimensional synthesis has been employed to specify the size of the mechanism and its location with respect to the limb, while generating the desired trajectory. The procedure for this method, from motion capture to kinematic synthesis to mechanism selection and optimization, is validated with an illustrative example. RESULTS: The proposed method resulted an exoskeleton which follows the desired trajectory of the human limb without any need of aligning its joint to the corresponding human joints. CONCLUSION: A method to design lower mobility exoskeletons for specific sets of human motion is presented; the approach result an exoskeleton with lesser actuation system while generating complex 3D limb motions, which in turn results a lighter exoskeletons. It also avoids a need to align each robotic joint axis with its human counterpart.
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BACKGROUND: Robots that physically assist movement are increasingly used in rehabilitation therapy after stroke, yet some studies suggest robotic assistance discourages effort and reduces motor learning. OBJECTIVE: To determine the therapeutic effects of high and low levels of robotic assistance during finger training. METHODS: We designed a protocol that varied the amount of robotic assistance while controlling the number, amplitude, and exerted effort of training movements. Participants (n = 30) with a chronic stroke and moderate hemiparesis (average Box and Blocks Test 32 ± 18 and upper extremity Fugl-Meyer score 46 ± 12) actively moved their index and middle fingers to targets to play a musical game similar to GuitarHero 3 h/wk for 3 weeks. The participants were randomized to receive high assistance (causing 82% success at hitting targets) or low assistance (55% success). Participants performed ~8000 movements during 9 training sessions. RESULTS: Both groups improved significantly at the 1-month follow-up on functional and impairment-based motor outcomes, on depression scores, and on self-efficacy of hand function, with no difference between groups in the primary endpoint (change in Box and Blocks). High assistance boosted motivation, as well as secondary motor outcomes (Fugl-Meyer and Lateral Pinch Strength)-particularly for individuals with more severe finger motor deficits. Individuals with impaired finger proprioception at baseline benefited less from the training. CONCLUSIONS: Robot-assisted training can promote key psychological outcomes known to modulate motor learning and retention. Furthermore, the therapeutic effectiveness of robotic assistance appears to derive at least in part from proprioceptive stimulation, consistent with a Hebbian plasticity model.
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Terapia por Ejercicio/métodos , Dedos/fisiopatología , Actividad Motora/fisiología , Paresia/rehabilitación , Robótica , Rehabilitación de Accidente Cerebrovascular/métodos , Método Doble Ciego , Terapia por Ejercicio/instrumentación , Femenino , Estudios de Seguimiento , Humanos , Aprendizaje , Masculino , Persona de Mediana Edad , Modelos Neurológicos , Motivación , Movimiento/fisiología , Música , Plasticidad Neuronal/fisiología , Paresia/etiología , Paresia/fisiopatología , Paresia/psicología , Recuperación de la Función , Accidente Cerebrovascular/complicaciones , Accidente Cerebrovascular/fisiopatología , Accidente Cerebrovascular/psicología , Rehabilitación de Accidente Cerebrovascular/instrumentación , Resultado del Tratamiento , Juegos de VideoRESUMEN
This paper describes the design and initial prototype of a thumb curling exoskeleton for movement therapy. This add-on device for the Finger INdividuating Grasp Exercise Robot (FINGER) guides the thumb through a single-degree-of-freedom naturalistic grasping motion. This motion complements the grasping motions of the index and middle fingers provided by FINGER. The kinematic design and mechanism synthesis described herein utilized 3D motion capture and included the determination of the principle plane of the thumb motion for the simple grasping movement. The results of the design process and the creation of a first prototype indicate that this thumb module for finger allows naturalistic thumb motion that expands the capabilities of the FINGER device.
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Robótica/instrumentación , Robótica/métodos , Pulgar , Fenómenos Biomecánicos , Dedos , Fuerza de la Mano , Humanos , Pulgar/fisiologíaRESUMEN
This paper extends an adaptive control approach for robotic movement therapy that learns deficiencies in a patient's neuromuscular output and assists accordingly. In this method, adaptation is based on trajectory tracking error and a model of unimpaired motor control forces. The controller presented here adaptively learns and fills the gaps in the patient's ability to generate inertial forces, instead of just static forces, as has been proposed before. To test this method, a two dimensional model of an impaired human arm was used to simulate reaching movements in the horizontal plane. The results from simulation demonstrate that the inertia-based controller assists more effectively without need for increasing the controller's impedance, which suggests that modeling inertial forces during robot movement therapy could improve the ability of robots to deliver assistance-as-needed.
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Aprendizaje Automático , Modalidades de Fisioterapia , Robótica/instrumentación , Rehabilitación de Accidente Cerebrovascular , Brazo/fisiología , Humanos , Modelos Teóricos , Rehabilitación de Accidente Cerebrovascular/instrumentación , Rehabilitación de Accidente Cerebrovascular/métodosRESUMEN
Robotic devices are a promising and dynamic tool in the realm of post-stroke rehabilitation. Researchers are still investigating how the use of robots affects motor learning and what design characteristics best encourage recovery. We present a parallel-actuated, end-effector robot designed to provide spatial assistance for upper-limb therapy while exhibiting low impedance and high backdrivability. A gradient based optimization was performed to find an optimal design that accounted for force isotropy, mechanical advantage, workspace size, and counter-balancing. A beta prototype has been built to these specifications (low impedance and high backdrivability) and has undergone initial controller performance as well as fit and function testing. By fitting a nonlinear model to experimental frequency response data, the apparent mass, viscous friction coefficient, and dynamic dry friction coefficient were determined to be 0.242 kg, 0.114 Ns/m, and 0.894 N respectively. The robot will serve as a testing platform to investigate motor learning and evaluate the efficacy of control schemes for post-stroke movement therapy.
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Robótica/instrumentación , Rehabilitación de Accidente Cerebrovascular/instrumentación , Diseño de Equipo , Humanos , Rehabilitación de Accidente Cerebrovascular/métodos , Extremidad Superior/fisiología , Extremidad Superior/fisiopatologíaRESUMEN
Age-related changes in proprioception are known to affect postural stability, yet the extent to which such changes affect the finger joints is poorly understood despite the importance of finger proprioception in the control of skilled hand movement. We quantified age-related changes in finger proprioception in 37 healthy young, middle-aged, and older adults using two robot-based tasks wherein participants' index and middle fingers were moved by an exoskeletal robot. The first task assessed finger position sense by asking participants to indicate when their index and middle fingers were directly overlapped during a passive crisscross movement; the second task assessed finger movement detection by asking participants to indicate the onset of passive finger movement. When these tasks were completed without vision, finger position sense errors were 48 % larger in older adults compared to young participants (p < 0.05); proprioceptive reaction time was 78 % longer in older adults compared to young adults (p < 0.01). When visual feedback was provided in addition to proprioception, these age-related differences were no longer apparent. No difference between dominant and non-dominant hand performance was found for either proprioception task. These findings demonstrate that finger proprioception is impaired in older adults, and visual feedback can be used to compensate for this deficit. The findings also support the feasibility and utility of the FINGER robot as a sensitive tool for detecting age-related decline in proprioception.
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Envejecimiento/fisiología , Retroalimentación Sensorial/fisiología , Dedos/fisiología , Propiocepción/fisiología , Robótica/instrumentación , Adulto , Anciano , Anciano de 80 o más Años , Humanos , Persona de Mediana Edad , Tiempo de Reacción/fisiología , Adulto JovenRESUMEN
BACKGROUND: This paper describes the design and preliminary testing of FINGER (Finger Individuating Grasp Exercise Robot), a device for assisting in finger rehabilitation after neurologic injury. We developed FINGER to assist stroke patients in moving their fingers individually in a naturalistic curling motion while playing a game similar to Guitar Hero. The goal was to make FINGER capable of assisting with motions where precise timing is important. METHODS: FINGER consists of a pair of stacked single degree-of-freedom 8-bar mechanisms, one for the index and one for the middle finger. Each 8-bar mechanism was designed to control the angle and position of the proximal phalanx and the position of the middle phalanx. Target positions for the mechanism optimization were determined from trajectory data collected from 7 healthy subjects using color-based motion capture. The resulting robotic device was built to accommodate multiple finger sizes and finger-to-finger widths. For initial evaluation, we asked individuals with a stroke (n = 16) and without impairment (n = 4) to play a game similar to Guitar Hero while connected to FINGER. RESULTS: Precision design, low friction bearings, and separate high speed linear actuators allowed FINGER to individually actuate the fingers with a high bandwidth of control (-3 dB at approximately 8 Hz). During the tests, we were able to modulate the subject's success rate at the game by automatically adjusting the controller gains of FINGER. We also used FINGER to measure subjects' effort and finger individuation while playing the game. CONCLUSIONS: Test results demonstrate the ability of FINGER to motivate subjects with an engaging game environment that challenges individuated control of the fingers, automatically control assistance levels, and quantify finger individuation after stroke.
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Dedos/fisiología , Modalidades de Fisioterapia/instrumentación , Robótica/métodos , Rehabilitación de Accidente Cerebrovascular , Juegos de Video , Algoritmos , Femenino , Humanos , Masculino , Persona de Mediana Edad , Proyectos PilotoRESUMEN
OBJECTIVES: Robot-assisted movement training can help individuals with stroke reduce arm and hand impairment, but robot therapy is typically only about as effective as conventional therapy. Refining the way that robots assist during training may make them more effective than conventional therapy. Here, the authors measured the therapeutic effect of a robot that required individuals with a stroke to achieve virtual tasks in three dimensions against gravity. DESIGN: The robot continuously estimated how much assistance patients needed to perform the tasks and provided slightly less assistance than needed to reduce patient slacking. Individuals with a chronic stroke (n = 26; baseline upper limb Fugl-Meyer score, 23 ± 8) were randomized into two groups and underwent 24 one-hour training sessions over 2 mos. One group received the assist-as-needed robot training and the other received conventional tabletop therapy with the supervision of a physical therapist. RESULTS: Training helped both groups significantly reduce their motor impairment, as measured by the primary outcome measure, the Fugl-Meyer score, but the improvement was small (3.0 ± 4.9 points for robot therapy vs. 0.9 ± 1.7 for conventional therapy). There was a trend for greater reduction for the robot-trained group (P = 0.07). The robot group largely sustained this gain at the 3-mo follow-up. The robot-trained group also experienced significant improvements in Box and Blocks score and hand grip strength, whereas the control group did not, but these improvements were not sustained at follow-up. In addition, the robot-trained group showed a trend toward greater improvement in sensory function, as measured by the Nottingham Sensory Test (P = 0.06). CONCLUSIONS: These results suggest that in patients with chronic stroke and moderate-severe deficits, assisting in three-dimensional virtual tasks with an assist-as-needed controller may make robotic training more effective than conventional tabletop training.
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Robótica/métodos , Rehabilitación de Accidente Cerebrovascular , Brazo/fisiopatología , Isquemia Encefálica/rehabilitación , Hemorragia Cerebral/complicaciones , Hemorragia Cerebral/rehabilitación , Diseño de Equipo , Mano/fisiopatología , Fuerza de la Mano , Humanos , Aparatos Ortopédicos , Accidente Cerebrovascular/etiología , Accidente Cerebrovascular/fisiopatología , Análisis y Desempeño de Tareas , Resultado del TratamientoRESUMEN
This paper presents the kinematic design of a spatial, 1-degree-of-freedom closed linkage to be used as an exoskeleton for thumb motion. Together with an already-designed finger mechanism, it forms a robotic device for hand therapy. The goal for the exoskeleton is to generate the desired grasping and pinching path of the thumb with one degree of freedom, rather than using a system actuating all its joints independently. In addition to the path of the thumb, additional constraints are added in order to control the position and size of the exoskeleton, reducing physical and sensory interference with the user.
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Aparatos Ortopédicos , Diseño de Prótesis , Rehabilitación , Pulgar/fisiopatología , Fenómenos Biomecánicos , Falanges de los Dedos de la Mano/fisiopatología , Humanos , Articulaciones/fisiopatologíaRESUMEN
This paper describes the design and testing of a robotic device for finger therapy after stroke: FINGER (Finger Individuating Grasp Exercise Robot). FINGER makes use of stacked single degree-of-freedom mechanisms to assist subjects in moving individual fingers in a naturalistic grasping pattern through much of their full range of motion. The device has a high bandwidth of control (-3dB at approximately 8 Hz) and is backdriveable. These characteristics make it capable of assisting in grasping tasks that require precise timing. We therefore used FINGER to assist individuals with a stroke (n= 8) and without impairment (n= 4) in playing a game similar to Guitar Hero©. The subjects attempted to move their fingers to target positions at times specified by notes that were graphically streamed to popular music. We show here that by automatically adjusting the robot gains, it is possible to use FINGER to modulate the subject's success rate at the game, across a range of impairment levels. Modulating success rates did not alter the stroke subject's effort, although the unimpaired subjects exerted more force when they were made less successful. We also present a novel measure of finger individuation that can be assessed as individuals play Guitar Hero with FINGER. The results demonstrate the ability of FINGER to provide controlled levels of assistance during an engaging computer game, and to quantify finger individuation after stroke.
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Dedos/fisiopatología , Música , Robótica , Rehabilitación de Accidente Cerebrovascular , Accidente Cerebrovascular/fisiopatología , Juegos de Video , Adulto , Femenino , Mano , Fuerza de la Mano , Humanos , Masculino , Persona de Mediana EdadRESUMEN
This paper presents the kinematic design of a single degree-of-freedom exoskeleton mechanism: a planar eight-bar mechanism for finger curling. The mechanism is part of a finger-thumb robotic device for hand therapy that will allow users to practice key pinch grip and finger-thumb opposition, allowing discrete control inputs for playing notes on a musical gaming interface. This approach uses the mechanism to generate the desired grasping trajectory rather than actuating the joints of the fingers and thumb independently. In addition, the mechanism is confined to the back of the hand, so as to allow sensory input into the palm of the hand, minimal size and apparent inertia, and the possibility of placing multiple mechanisms side-by-side to allow control of individual fingers.