Interaction Modalities Used on Serious Games for Upper Limb Rehabilitation: A Systematic Review

This systematic review aims to analyze the state-of-the-art regarding interaction modalities used on serious games for upper limb rehabilitation. A systematic search was performed in IEEE Xplore and Web of Science databases. PRISMA and QualSyst protocols were used to filter and assess the articles. Articles must meet the following inclusion criteria: they must be written in English; be at least four pages in length; use or develop serious games; focus on upper limb rehabilitation; and be published between 2007 and 2017. Of 121 articles initially retrieved, 33 articles met the inclusion criteria. Three interaction modalities were found: vision systems (42.4%), complementary vision systems (30.3%), and no-vision systems (27.2%). Vision systems and no-vision systems obtained a similar mean QualSyst (86%) followed by complementary vision systems (85.7%). Almost half of the studies used vision systems as the interaction modality (42.4%) and used the Kinect sensor to collect the body movements (48.48%). The shoulder was the most treated body part in the studies (19%). A key limitation of vision systems and complementary vision systems is that their device performances might be affected by lighting conditions. A main limitation of the no-vision systems is that the range-of-motion in angles of the body movement might not be measured accurately. Due to a limited number of studies, fruitful areas for further research could be the following: serious games focused on finger rehabilitation and trauma injuries, game difficulty adaptation based on user's muscle strength and posture, and multisensor data fusion on interaction modalities

Home-based exergames to improve cognitive function in Multiple Sclerosis: the EXTREMUS Study ​

Background. Motor and cognitive dysfunctions are common and disabling features in multiple sclerosis (MS) that remain challenging to be treated. Exergaming is an emerging tool in neurorehabilitation, which promotes motor functions and fitness level. Evidence in general population and in other neurological conditions suggests that exergames may be beneficial also for cognitive functions, as playing action video games requires the engagement of high-level domains for visuo-motor integration and spatial attention. Objective. To test if home-based exergaming is not inferior to cognitive rehabilitation delivered by a software application (app) for mobile devices and both interventions are superior to a placebo-analogue (sham) cognitive intervention. The hypothesis is that exergames offer a comprehensive approach to improve both motor and cognitive domains. Methods. This is a multicenter, randomized, sham-controlled, single blind, parallel arm study. People with MS (pwMS) will be randomized in a 1:1:1 ratio to receive 1) an 8-week home-based training with exergames, specifically with Nintendo Wii (intervention of interest) or 2) adaptive COGNI-TRAcK (comparator intervention) or 3) sham COGNI-TRAcK (placebo-analogue intervention). Assessments will be conducted at study enrolment (baseline), at the end of the 8-week intervention period (immediate post-training, Week 8) and after 16 weeks from randomization (post-training follow-up, Week 16). At each point in the assessment, Brief International Cognitive Assessment for MS (BICAMS) and the Stroop Color Word Test (SCWT). In addition, pwMS were assessed with the 29-item Multiple Sclerosis Impact Scale (MSIS-29), the 21-item Modified Fatigue Impact Scale (MFIS-21), the 2-Minute Walking Test (2MWT), the Timed Up&Go test (TUG) and by a static posturography under single- (ST) and dual-task (DT) conditions were conducted. Results. Sixty-nine pwMS were assessed for eligibility in this pre-planned interim analysis; of these, 47 were randomized to the three treatment groups. The three treatment groups were comparable in terms of demographic and clinical characteristics at baseline (all p values >0.2). Preliminary analyses show statistically significant results between the SHAM group and the ADAPTIVE group (p=0.04) for the Symbol Digit Modalities Test (SDMT), the information processing speed assessment test that is part of BICAMS; the improvement observed between the EXERGAMES group and the SHAM group, did not reach statistical significance (p=0.06). TUG among the three groups showed statistically significant improvement between the EXERGAMES group and the SHAM group (p=0.01) and the ADAPTIVE group (p<0.001). Regarding fatigue, statistically significant results emerged between the SHAM group and the ADAPTIVE group (p=0.04) and between the ADAPTIVE group and the EXERGAMES group (p=0.01). In the EXERGAMES group, there was an improvement in balance measured by posturography the ST and DT conditions (p=0.01 and p=0.02). Discussion. Although this is only preliminary data, some interesting results emerged from the study. First, both COGNI-TRAcK and Nintendo Wii-treated patients experienced improvements in SDMT compared to the SHAM group. In addition, the study found that patients undergoing home rehabilitation with the Nintendo Wii also achieved improvements in the motor domain. Second, it appears that rehabilitation training with exergames can bring improvements in some specific domains of QoL and fatigue. The results obtained for fatigue in people with MS show that exergames are significantly effective in improving after the intervention, compared with the other groups. These results indicate that rehabilitation with exergames, which requires simultaneous physical and cognitive effort on the part of the patient, promotes not only the strengthening of motor functions, but also the efficiency of brain networks, particularly those dedicated to attention

Contribuciones a la Rehabilitación Cognitiva de Pacientes con Enfermedades Neurodegenerativas por Medio de Realidad Virtual y Dispositivos de Bajo Coste

La realidad virtual es una tecnología que ha estado en constante desarrollo en las últimas décadas, aportando soluciones para complementar a la medicina tradicional. En particular, la salud cognitiva se ha visto beneficiada con entornos virtuales orientados a la evaluación y rehabilitación del paciente. No obstante, son limitadas las investigaciones realizadas para determinar su validez ecológica. En esta tesis doctoral se evalúan aplicaciones de realidad virtual diseñadas para cribado y rehabilitación cognitiva, incluyendo las aplicaciones orientadas a la tele rehabilitación. Con este objetivo se ha diseñado tareas basadas en dispositivos de bajo coste para sistemas inmersivos y no inmersivos, respectivamente. Bajo esta perspectiva se ha creado un marco de desarrollo para aplicaciones de realidad virtual con diferentes niveles de dificultad, que integran la recolección automatizada de resultados y el intercambio de información con servidores remotos mediante el enfoque de computación en la niebla. Las diferentes tareas han sido validadas en una población de sujetos sanos y con referencia a métodos tradicionales de valoración cognitiva. Para ello, además de utilizar las pruebas de contraste de hipótesis tradicionales, se han utilizado cuestionarios estandarizados y validados de usabilidad y satisfacción. Además, se ha optimizado el ancho de banda de red requerido para la ejecución de las tareas de rehabilitación supervisadas en tiempo real. Nuestros resultados confirman algunos de los obtenidos en investigaciones similares y aportan una mayor evidencia sobre los beneficios de la realidad virtual para la rehabilitación cognitiva, suponiendo, por ende, una base para futuros trabajos que utilicen esta tecnología para el tratamiento de enfermedades neurodegenerativas.<br /

Effects of dance therapy on balance, gait and neuro-psychological performances in patients with Parkinson's disease and postural instability

Postural Instability (PI) is a core feature of Parkinson’s Disease (PD) and a major cause of falls and disabilities. Impairment of executive functions has been called as an aggravating factor on motor performances. Dance therapy has been shown effective for improving gait and has been suggested as an alternative rehabilitative method. To evaluate gait performance, spatial-temporal (S-T) gait parameters and cognitive performances in a cohort of patients with PD and PI modifications in balance after a cycle of dance therapy

Validation of design artefacts for blockchain-enabled precision healthcare as a service.

Healthcare systems around the globe are currently experiencing a rapid wave of digital disruption. Current research in applying emerging technologies such as Big Data (BD), Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Augmented Reality (AR), Virtual Reality (VR), Digital Twin (DT), Wearable Sensor (WS), Blockchain (BC) and Smart Contracts (SC) in contact tracing, tracking, drug discovery, care support and delivery, vaccine distribution, management, and delivery. These disruptive innovations have made it feasible for the healthcare industry to provide personalised digital health solutions and services to the people and ensure sustainability in healthcare. Precision Healthcare (PHC) is a new inclusion in digital healthcare that can support personalised needs. It focuses on supporting and providing precise healthcare delivery. Despite such potential, recent studies show that PHC is ineffectual due to the lower patient adoption in the system. Anecdotal evidence shows that people are refraining from adopting PHC due to distrust. This thesis presents a BC-enabled PHC ecosystem that addresses ongoing issues and challenges regarding low opt-in. The designed ecosystem also incorporates emerging information technologies that are potential to address the need for user-centricity, data privacy and security, accountability, transparency, interoperability, and scalability for a sustainable PHC ecosystem. The research adopts Soft System Methodology (SSM) to construct and validate the design artefact and sub-artefacts of the proposed PHC ecosystem that addresses the low opt-in problem. Following a comprehensive view of the scholarly literature, which resulted in a draft set of design principles and rules, eighteen design refinement interviews were conducted to develop the artefact and sub-artefacts for design specifications. The artefact and sub-artefacts were validated through a design validation workshop, where the designed ecosystem was presented to a Delphi panel of twenty-two health industry actors. The key research finding was that there is a need for data-driven, secure, transparent, scalable, individualised healthcare services to achieve sustainability in healthcare. It includes explainable AI, data standards for biosensor devices, affordable BC solutions for storage, privacy and security policy, interoperability, and usercentricity, which prompts further research and industry application. The proposed ecosystem is potentially effective in growing trust, influencing patients in active engagement with real-world implementation, and contributing to sustainability in healthcare