Publications

Background: There is a pressing need for scalable healthcare solutions and a shift in the rehabilitation paradigm from hospitals to homes to tackle the increase in stroke incidence while reducing the practical and economic burden for patients, hospitals, and society. Digital health technologies can contribute to addressing this challenge; however, little is known about their effectiveness in at-home settings. In response, we have designed the RGS@home study to investigate the effectiveness, acceptance, and cost of a deep tech solution called the Rehabilitation Gaming System (RGS). RGS is a cloud-based system for delivering Al-enhanced rehabilitation using virtual reality, motion capture, and wearables that can be used in the hospital and at home. The core principles of the brain theory-based RGS intervention are to deliver rehabilitation exercises in the form of embodied, goal-oriented, and task-specific action.; Methods: The RGS@home study is a randomized longitudinal clinical trial designed to assess whether the combination of the RGS intervention with standard care is superior to standard care alone for the functional recovery of stroke patients at the hospital and at home. The study is conducted in collaboration with hospitals in Spain, Sweden, and France and includes inpatients and outpatients at subacute and chronic stages post-stroke. The intervention duration is 3 months with assessment at baseline and after 3, 6, and 12 months. The impact of RGS is evaluated in terms of quality of life measurements, usability, and acceptance using standardized clinical scales, together with health economic analysis. So far, one-third of the patients expected to participate in the study have been recruited (N = 90, mean age 60, days after stroke >= 30 days). The trial will end in July 2023.; Discussion: We predict an improvement in the patients' recovery, high acceptance, and reduced costs due to a soft landing from the clinic to home rehabilitation. In addition, the data provided will allow us to assess whether the prescription of therapy at home can counteract deterioration and improve quality of life while also identifying new standards for online and remote assessment, diagnostics, and intervention across European hospitals.

JTD Keywords: deep tech, e-health, home treatment, motor recovery, randomized clinical trial, stroke, upper extremities, virtual reality, Deep tech, E-health, Functional recovery, Home treatment, Humans, Middle aged, Motor recovery, Quality of life, Randomized clinical trial, Randomized controlled trials as topic, Recovery of function, Stroke, Stroke rehabilitation, Telemedicine, Upper extremities, Virtual reality, Wearables

Large doses of movement practice have been shown to restore upper extremities' motor function in a significant subset of individuals post-stroke. However, such large doses are both difficult to implement in the clinic and highly inefficient. In addition, an important reduction in upper extremity function and use is commonly seen following rehabilitation-induced gains, resulting in “rehabilitation in vain”. For those with mild to moderate sensorimotor impairment, the limited spontaneous use of the more affected limb during activities of daily living has been previously proposed to cause a decline of motor function, initiating a vicious cycle of recovery, in which non-use and poor performance reinforce each other. Here, we review computational, experimental, and clinical studies that support the view that if arm use is raised above an effective threshold, one enters a virtuous cycle in which arm use and function can reinforce each other via self-practice in the wild. If not, one enters a vicious cycle of declining arm use and function. In turn, and in line with best practice therapy recommendations, this virtuous/vicious cycle model advocates for a paradigm shift in neurorehabilitation whereby rehabilitation be embedded in activities of daily living such that self-practice with the aid of wearable technology that reminds and motivates can enhance paretic limb use of those who possess adequate residual sensorimotor capacity. Altogether, this model points to a user-centered approach to recovery post-stroke that is tailored to the participant's level of arm use and designed to motivate and engage in self-practice through progressive success in accomplishing meaningful activities in the wild. Copyright © 2022 Ballester, Winstein and Schweighofer.

JTD Keywords: compensatory movement, computational neurorehabilitation, decision-making, individuals, learned non-use, learned nonuse, monkeys, neurorehabilitation, recovery, rehabilitation, stroke, stroke patients, wearable sensors, wrist, Arm movement, Article, Cerebrovascular accident, Clinical decision making, Clinical practice, Clinical study, Compensatory movement, Computational neurorehabilitation, Computer model, Daily life activity, Decision-making, Experimental study, Human, Induced movement therapy, Learned non-use, Musculoskeletal function, Neurorehabilitation, Paresis, Sensorimotor function, Stroke, Stroke rehabilitation, User-centered design, Vicious cycle, Virtuous cycle, Wearable sensors

[No abstract available]

JTD Keywords: Adult, Aged, Female, Hemiplegia, Humans, Male, Middle aged, Recovery of function, Rehabilitation, Retrospective studies, Stroke, Stroke recovery, Stroke rehabilitation

Underpowered trials risk inaccurate results. Recruitment to stroke rehabilitation randomised controlled trials (RCTs) is often a challenge. Statistical simulations offer an important opportunity to explore the adequacy of sample sizes in the context of specific outcome measures. We aimed to examine and compare the adequacy of stroke rehabilitation RCT sample sizes using the Barthel Index (BI) or modified Rankin Scale (mRS) as primary outcomes.We conducted computer simulations using typical experimental event rates (EER) and control event rates (CER) based on individual participant data (IPD) from stroke rehabilitation RCTs. Event rates are the proportion of participants who experienced clinically relevant improvements in the RCT experimental and control groups. We examined minimum sample size requirements and estimated the number of participants required to achieve a number needed to treat within clinically acceptable boundaries for the BI and mRS.We secured 2350 IPD (18 RCTs). For a 90% chance of statistical accuracy on the BI a rehabilitation RCT would require 273 participants per randomised group. Accurate interpretation of effect sizes would require 1000s of participants per group. Simulations for the mRS were not possible as a clinically relevant improvement was not detected when using this outcome measure.Stroke rehabilitation RCTs with large sample sizes are required for accurate interpretation of effect sizes based on the BI. The mRS lacked sensitivity to detect change and thus may be unsuitable as a primary outcome in stroke rehabilitation trials.Copyright © 2021 Elsevier Inc. All rights reserved.

JTD Keywords:  , barthel index, design, increasing value, modified rankin scale, randomised controlled trials, recruitment, reducing waste, reliability, sample size calculations, simulations, stroke rehabilitation, Adult, Article, Barthel index, Calculation, Computer simulation, Controlled study, Effect size, Female, Human, Human experiment, Major clinical study, Male, Modified rankin scale, Numbers needed to treat, Outcome assessment, Randomised controlled trials, Randomized controlled trial, Randomized controlled-trials, Rankin scale, Recruitment, Rehabilitation, Sample size, Sample size calculations, Simulations, Stroke rehabilitation

Stroke is a major cause of disability, usually causing hemiplegic damage on the motor abilities of the patient. Stroke rehabilitation seeks restoring normal motion on the affected limb. However, normality’ of movements is usually assessed by clinical and functional tests, without considering how the motor system responds to therapy. We hypothesized that electromyographic (EMG) recordings could provide useful information for evaluating the outcome of rehabilitation from a neuromuscular perspective. Four healthy subjects were asked to perform 14 different functional movements simulating the action of reaching over a table. Each movement was defined according to the starting and target positions that the subject had to connect using linear trajectories. Bipolar recordings of EMG signals were taken from biceps and triceps muscles, and spectral and temporal characteristics were extracted for each movement. Using pattern recognition techniques we found that only two EMG channels were sufficient to accurately determine the spatial characteristics of motor activity: movement direction, length and execution zone. Our results suggest that muscles may fire in a patterned way depending on the specific characteristics of the movement and that EMG signals may codify such detailed information. These findings may be of great value to quantitatively assess post-stroke rehabilitation and to compare the neuromuscular activity of the affected and unaffected limbs, from a physiological perspective. Furthermore, disturbed movements could be characterized in terms of the muscle function to identify, which is the spatial characteristic that fails, e.g. movement direction, and guide personalized rehabilitation to enhance the training of such characteristic.

JTD Keywords: EMG, Movement spatial characteristics, Pattern recognition, Stroke rehabilitation, Upper-limb