An integrative framework for tailoring virtual reality based motor rehabilitation after stroke

Stroke is a leading cause of life-lasting motor impairments, undermining the quality of life of stroke survivors and their families, and representing a major chal lenge for a world population that is ageing at a dramatic rate. Important technologi cal developments and neuroscientific discoveries have contributed to a better under standing of stroke recovery. Virtual Reality (VR) arises as a powerful tool because it allows merging contributions from engineering, human computer interaction, reha bilitation medicine and neuroscience to propose novel and more effective paradigms for motor rehabilitation. However, despite evidence of the benefits of these novel training paradigms, most of them still rely on the choice of particular technologi cal solutions tailored to specific subsets of patients. Here we present an integrative framework that utilizes concepts of human computer confluence to 1) enable VR neu rorehabilitation through interface technologies, making VR rehabilitation paradigms accessible to wide populations of patients, and 2) create VR training environments that allow the personalization of training to address the individual needs of stroke patients. The use of these features is demonstrated in pilot studies using VR training environments in different configurations: as an online low-cost version, with a myo electric robotic orthosis, and in a neurofeedback paradigm. Finally, we argue about the need of coupling VR approaches and neurocomputational modelling to further study stroke and its recovery process, aiding on the design of optimal rehabilitation programs tailored to the requirements of each user.info:eu-repo/semantics/publishedVersio

Personalized neuromusculoskeletal modeling to improve treatment of mobility impairments: a perspective from European research sites

Mobility impairments due to injury or disease have a significant impact on quality of life. Consequently, development of effective treatments to restore or replace lost function is an important societal challenge. In current clinical practice, a treatment plan is often selected from a standard menu of options rather than customized to the unique characteristics of the patient. Furthermore, the treatment selection process is normally based on subjective clinical experience rather than objective prediction of post-treatment function. The net result is treatment methods that are less effective than desired at restoring lost function. This paper discusses the possible use of personalized neuromusculoskeletal computer models to improve customization, objectivity, and ultimately effectiveness of treatments for mobility impairments. The discussion is based on information gathered from academic and industrial research sites throughout Europe, and both clinical and technical aspects of personalized neuromusculoskeletal modeling are explored. On the clinical front, we discuss the purpose and process of personalized neuromusculoskeletal modeling, the application of personalized models to clinical problems, and gaps in clinical application. On the technical front, we discuss current capabilities of personalized neuromusculoskeletal models along with technical gaps that limit future clinical application. We conclude by summarizing recommendations for future research efforts that would allow personalized neuromusculoskeletal models to make the greatest impact possible on treatment design for mobility impairments

Personalizing paper-and-pencil training for cognitive rehabilitation: a feasibility study with a web-based Task Generator

Cognitive impairments impose important limitations in the performance of activities of daily living. Although there is important evidence on cognitive rehabilitation benefits, its implementation is limited due to the demands in terms of time and human resources. Moreover, many cognitive rehabilitation interventions lack a solid theoretical framework in the selection of paper-and-pencil tasks by the clinicians. In this endeavor, it would be useful to have a tool that could generate standardized paper-and pencil tasks, customized according to patients’ needs. Combining the advantages of information and communication technologies (ICT’s) with a participatory design approach involving 20 health professionals, a novel web-tool for the generation of cognitive rehabilitation training was developed: the Task Generator (TG). The TG is a web-based tool that systematically addresses multiple cognitive domains, and easily generates highly personalized paper and-pencil training tasks. A clinical evaluation of the TG with twenty stroke patients showed that, by enabling the adaptation of task parameters and difficulty levels according to patient cognitive assessment, this tool provides a comprehensive cognitive training.info:eu-repo/semantics/publishedVersio

Lag-lead based assessment and adaptation of exercise speed for stroke survivors

This document is the Accepted Manuscript version of the following article: Angelo Basteris, Sharon M. Mijenhuis, Jaap H. Buurke, Gerdienke B. Prange, and Farshid Amirabdolllahian, ‘Lag–lead based assessment and adaptation of exercise speed for stroke survivors’, Robotics and Autonomous Systems, Vol. 73: 144-154, November 2015. The final, published version is available online at doi: https://doi.org/10.1016/j.robot.2014.08.013.The SCRIPT project aims at delivering machine-mediated hand and wrist exercises to people with stroke in their homes. In this context, adapting the exercise to the individual needs potentially enhances recovery. We designed a system composed of a passive-actuated wearable device, a personal computer and an arm support. The system enables users to exercise their hand and wrist movements by playing interactive games which were developed as part of the project. Movements and their required speed are tailored on the individual's capabilities. During the exercise the system assesses whether the subject is in advance (leading) or in delay (lagging) with respect to a reference trajectory. This information provides input to an adaptive mechanism which changes the required movement speed in order to make the exercise neither too easy nor too challenging. In this paper, we show results of the adaptation process in a study involving seven persons with chronic stroke who completed a six weeks training in their homes. Based on the patterns observed in difficulty and lag-lead score, we defined five session types (challenging, challenging-then supporting, supporting, under-supporting and under-challenging). We show that the mechanism of adaptation has been effective in 195 of 248 (78.6%) sessions. Based on our results, we propose the lag-lead based assessment and adaptation as an auto-tuning tool for machine based exercise, with particular focus on rehabilitation robotics. Also, the classification of sessions among different types can be applied to other studies in order to better understanding the progression of therapy in order to maximize its outcome.Peer reviewe

Visuaal-ruumiliste defitsiitide rehabilitatsioon FORAMENRehab arvutiprogrammiga epilepsiaga lastel

Children with epilepsy have shown deficits in attention and visuospatial functions, which could disrupt their normal life. For example, visuospatial functions have been found to predict achievements in mathematics. Very few systematically controlled evidence-based neurorehabilitation treatments for children exist at the moment. Using modern cognitive rehabilitation methods in children is important for their development and remediation. The aim of the current study was to test the effectiveness of computer-based rehabilitation program in the treatment of visuospatial deficit for children with epilepsy. 58 children aged 8-12 participated in the study: 17 children diagnosed with epilepsy were in the training group, 22 children in the waiting-list control group and 19 healthy controls. The training group received guided visuospatial functions training using the FORAMENRehab software. Trainings took place twice a week for a 5-week period. Baseline assessments were carried out before and immediately after the intervention and a follow-up assessment 1.31 years after. Remarkable improvements were observed in the training group following intervention. The training group showed positive immediate rehabilitation effect in 3 out of 4 visuospatial components: visual organization, visual attention and visuospatial perception. Furthermore, a positive long-term rehabilitation effect in the training group was observed in all 4 of the visuospatial components. The general ability of the children improved, even though some of the visuospatial components showed no significant improvements after intervention. This positive generalized effect of the intervention was confirmed by the parents’ and children’s qualitative feedback with some of the learned skills transferring to the everyday life of the children. 100% compliance further confirms the motivation of the children to participate in the study and the effectiveness of the FORAMENRehab software for neurorehabilitation

A mobile application based on machine learning and music therapy principles for post-stroke upper-limb motor recovery

A stroke is a medical condition caused by a disruption in blood flow to the brain. This can lead to difficulties with everyday activities and movement. Music therapy is a promising new alternative to traditional rehabilitation methods. This therapy uses sound’s natural properties to enhance stroke recovery, improve motor skills and stimulate neural plasticity. This approach motivates people on both a physical and emotional level. Software tools developed to date to aid in motor recovery after stroke rely mainly on external mechanisms and specific hardware components. This limitation restricts the potential scope of these tools. This study aims to examine the effectiveness and mechanisms of using a mobile application with machine learning algorithms and music therapy principles as a complementary intervention for post-stroke motor recovery. This research project has resulted in the development of a mobile app, based on the widely used Fugl Meyer Assessment. The application uses Vision Framework from Apple and a custom Activity Classification CoreML machine learning model to detect an individual's position in a seated posture. It has also been integrated with XCode. The application generates an audio cue when a user successfully completes one of the Fugl-Meyer Assessment activities. To train the model, 340 clips of a variety of exercises have been created. The research sheds light on how this technology can be used to transform neurorehabilitation while also helping to develop accessible and convenient tools that promote stroke motor recovery

Immersive Virtual Reality and Robotics for Upper Extremity Rehabilitation

Stroke patients often experience upper limb impairments that restrict their mobility and daily activities. Physical therapy (PT) is the most effective method to improve impairments, but low patient adherence and participation in PT exercises pose significant challenges. To overcome these barriers, a combination of virtual reality (VR) and robotics in PT is promising. However, few systems effectively integrate VR with robotics, especially for upper limb rehabilitation. Additionally, traditional VR rehabilitation primarily focuses on hand movements rather than joint movements of the limb. This work introduces a new virtual rehabilitation solution that combines VR with KinArm robotics and a wearable elbow sensor to measure elbow joint movements. The framework also enhances the capabilities of a traditional robotic device (KinArm) used for motor dysfunction assessment and rehabilitation. A preliminary study with non-clinical participants (n = 16) was conducted to evaluate the effectiveness and usability of the proposed VR framework. We used a two-way repeated measures experimental design where participants performed two tasks (Circle and Diamond) with two conditions (VR and VR KinArm). We found no main effect of the conditions for task completion time. However, there were significant differences in both the normalized number of mistakes and recorded elbow joint angles (captured as resistance change values from the wearable sensor) between the Circle and Diamond tasks. Additionally, we report the system usability, task load, and presence in the proposed VR framework. This system demonstrates the potential advantages of an immersive, multi-sensory approach and provides future avenues for research in developing more cost-effective, tailored, and personalized upper limb solutions for home therapy applications.Comment: Submitted to International Journal of Human-Computer Interactio