Rehabilitation Robots for Neurorehabilitation in High, Low, and Middle Income Countries: Current Practice, Barriers, and Future Directions describes the state-of-art research of stroke rehabilitation using robot systems in selected High Income Countries (HICs) and Low and Middle Income Countries (LMICs), along with potential solutions that enable these technologies to be available to clinicians worldwide, regardless of country and economic status. The book brings together engineers and clinicians, offers insights into healthcare disparities, and highlights potential solutions to facilitate the availability and accessibility of more robot systems to stroke survivors and their clinicians worldwide, regardless of country and economic status.In addition, the book provides examples on how robotic technology is used to bridge rehabilitation gaps in LMICs and describes potential strategies for increasing the expansion of robot-assisted stroke rehabilitation across more LMICs.
There is increasing evidence that HIV is an independent risk factor for stroke, resulting in an emerging population of people living with both HIV and stroke all over the world. However, neurorehabilitation strategies for the HIV-stroke population are distinctly lacking, which poses an enormous global health challenge. In order to address this gap, a better understanding of the HIV-stroke population is needed, as well as potential approaches to design effective neurorehabilitation strategies for this population. This review goes into the mechanisms, manifestations, and treatment options of neurologic injury in stroke and HIV, the additional challenges posed by the HIV-stroke population, and rehabilitation engineering approaches for both high and low resource areas. The aim of this review is to connect the underlying neurologic properties in both HIV and stroke to rehabilitation engineering. It reviews what is currently known about the association between HIV and stroke and gaps in current treatment strategies for the HIV-stroke population. We highlight relevant current areas of research that can help advance neurorehabilitation strategies specifically for the HIV-stroke population. We then explore how robot-assisted rehabilitation combined with community-based rehabilitation could be used as a potential approach to meet the challenges posed by the HIV-stroke population. We include some of our own work exploring a community-based robotic rehabilitation exercise system. The most relevant strategies will be ones that not only take into account the individual status of the patient but also the cultural and economic considerations of their respective environment.
Robot-based neurorehabilitation strategies often ignore cognitive performance during treatment, but this is a need in populations dealing with a wide variety of cognitive and motor impairments, such as the stroke and HIV populations, for which an association between the two have been established. In this study, we concurrently measure cognitive and motor performance on a robotic cognitive-motor task and quantify cognitive-motor interference. We apply this method to a pilot group of healthy, stroke, and HIV-stroke subjects, and we demonstrate the potential of smoothness and correct response rate as metrics to capture motor and cognitive-related dual-task effects.
Task-oriented therapy consists of three stages: demonstration, observation and assistance. While demonstration using robots has been extensively studied, the other two stages rarely involve robots. This paper focuses on the transition between observation and assistance. More specifically, we tackle the robot’s decision making problem of whether to assist a patient or not based on the observation. The proposed method is to train a discrete tunnel shape 3-D decision boundary through correct demonstration to classify motions. Additional conditions such as slow progress, self correction and overshot motions are taken into account of the decision making. Preliminary experiments have been performed on BAXTER robot for a cup reaching task. The BAXTER robot is programmed to react according to the decision boundary. It assists the patient when the patient’s hand position is determined by the proposed algorithm to be unacceptable. Multiple cases including correct motion, continuous assistance, overshot, misaim and slow progress are tested. Results have confirmed the feasibility of the proposed method, which can reduce the current shortage of physical rehabilitation therapists.
There are currently no effective tools to assess the range of physical, cognitive, and social issues seen in the emerging HIV-stroke population. In turn, this poses a barrier to developing effective neurorehabilitation strategies to deal with the unique challenges of living with both HIV and stroke. Rehabilitation robotics provide a potential approach to address this problem. In this study, we develop a cognitive-motor task on the Haptic Theradrive, a single degree-of-freedom robot designed for upper limb rehabilitation. We collect preliminary data on healthy and HIV-stroke subjects from both upper limbs. We identify metrics that could potentially be useful in assessing motor and cognitive impairment across the HIV-stroke disability spectrum.
There is an increasing population of people living with both HIV and stroke around the world with no effective neurorehabilitation strategies to deal with the combination of physical, cognitive, and social impairment that result from both diseases. This gap is caused by a lack of tools that are able to assess the various impairments across the HIV-stroke spectrum. Rehabilitation robotics provide a potential approach to address this problem. In this study, we implement a motor and cognitive task on the Haptic TheraDrive, a single degree-of-freedom upper limb rehabilitation robot. We collect data on healthy and HIV-stroke subjects from both upper limbs. Our preliminary data show that mean performance error on a trajectory tracking task and total score and reaction time on the n-back task are metrics that show differences between HIV-stroke patients and a healthy population.
Haptic TheraDrive is a low-cost robotic system that uses off-the-shelf computer gaming wheels with force feedback for post-stroke upper extremity rehabilitation. Preliminary results have shown that the Haptic TheraDrive system is not capable of delivering effective therapy to low-functioning patients. A new low-cost, high-force haptic robot with a single degree of freedom has been developed to address this concern. The purpose of this case is to determine the impact on motor performance and function with use of a custom force-feedback device, Haptic TheraDrive, to complete games for rehabilitation in a low-to-moderate functioning stroke survivor with hemiplegia.
In this study, we aim to explore ways to objectively assess cognitive deficits in the stroke and HIV/stroke populations, where cognitive and motor impairments can be hard to separate. Using an upper limb rehabilitation robot called the Haptic TheraDrive, we collect performance error scores and motor learning data on the impaired and unimpaired limb during a trajectory tracking task. We compare these data to clinical cognitive scores. The preliminary results suggest a possible relationship between unimpaired upper limb performance error and visuospatial/executive function cognitive domains, but more work needs to be done to further investigate this. The potential of using robot-assisted technologies to measure unimpaired limb kinematics as a tool to assess cognitive deficits would be useful to inform more effective rehabilitation strategies for HIV, stroke, and HIV/stroke populations.
https://upenn.alma.exlibrisgroup.com/discovery/openurl?institution=01UPENN_INST&vid=01UPENN_INST:Services&=%3Fsid%3Dgoogle&auinit=DO&aulast=Adewole&atitle=A%20computer%20model%20of%20the%20human%20arm:%20Predictive%20biomechanics%20for%20the%20theradrive%20rehabilitation%20system&id=doi:10.1109%2FICORR.2015.7281300
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