Monitoring Home-Based Activity of Stroke Patients: A Digital Solution for Visuo-Spatial Neglect Evaluation

The possibility to prescribe home-based rehabilitation activity after stroke strongly increases the amount of exercises to perform, thus helping the maintenance of relearned skills, the completion of the rehabilitation program, the practice of physical and mental concentration. Even more important is the monitoring of the patient activity at home, as it is provided by the Remote Monitoring Validation Engineering System (ReMoVES) platform [1]. The present work refers to the implementation and integration in ReMoVES platform of a digital and web-based version of Albert\u2019s [2] and Line Bisection [3] tests devoted to visuo-spatial neglect evaluation and its remote monitoring. A statistical analysis devoted to validating test-retest reliability is proposed. Concurrent correlation between digital and traditional administration of the tests is presented, in order to evaluate the validity of the remote monitoring of the home-administration through ReMoVES platform

New techniques for neuro-rehabilitation: Transcranial Electric Stimulation and Virtual Reality

Recovery of motor and cognitive performances after a neurological illness remains a significant challenge for rehabilitation specialists. The traditional rehabilitative interventions are usually delivered using a multidisciplinary approach, whose results are not always satisfactory. These limitations in functional recovery have led researchers to consider alternative approaches. The hypothesis of providing new therapeutic possibilities in the different patients treated is, as a rehabilitator, very rewarding and represents a challenge for the future. The application of simple and low-cost techniques, defined by the literature as "unconventional" or “novel”, can provide new ideas not only in the field of research but above all of application in clinical reality.A suitable approach to improve the rehabilitation outcome is to utilize these novel rehabilitation techniques that act as a substitute or an addition to the traditional ones. In this context, some recent approaches have been proposed that might increase the effectiveness of a traditional treatment. Among them, two techniques have been demonstrated to be very promising, namely non-invasive brain stimulation (NIBS) and Virtual Reality (VR).In light of the foregoing, my thesis has been divided into two main lines of research, namely: a) the study of the effects of transcranial direct current stimulation (tDCS) in different neurological conditions; b) the application of VR (used alone or combined with tDCS) in the treatment of some neurocognitive disorders. A semi-immersive VR tool (ReMOVES system) has been used as a user-friendly platform providing activities based on exergames

Definition of Motion and Biophysical Indicators for Home-Based Rehabilitation through Serious Games

In this paper, we describe Remote Monitoring Validation Engineering System (ReMoVES), a newly-developed platform for motion rehabilitation through serious games and biophysical sensors. The main features of the system are highlighted as follows: motion tracking capabilities through Microsoft Kinect V2 and Leap Motion are disclosed and compared with other solutions; the emotional state of the patient is evaluated with heart rate measurements and electrodermal activity monitored by Microsoft Band 2 during the execution of the functional exercises planned by the therapist. The ReMoVES platform is conceived for home-based rehabilitation after the hospitalisation period, and the system will deploy machine learning techniques to provide an automated evaluation of the patient performance during the training. The algorithms should deliver effective reports to the therapist about the training performance while the patient exercises on their own. The game features that will be described in this manuscript represent the input for the training set, while the feedback provided by the therapist is the output. To face this supervised learning problem, we are describing the most significant features to be used as key indicators of the patient’s performance along with the evaluation of their accuracy in discriminating between good or bad patient actions

Design and Development of ReMoVES Platform for Motion and Cognitive Rehabilitation

Exergames have recently gained popularity and scientific reliability in the field of assistive computing technology for human well-being. The ReMoVES platform, developed by the author, provides motor and cognitive exergames to be performed by elderly or disabled people, in conjunction with traditional rehabilitation. Data acquisition during the exercise takes place through Microsoft Kinect, Leap Motion and touchscreen monitor. The therapist is provided with feedback on patients' activity over time in order to assess their weakness and correct inaccurate movement attitudes. This work describes the technical characteristics of the ReMoVES platform, designed to be used by multiple locations such as rehabilitation centers or the patient's home, while providing a centralized data collection server. The system includes 15 exergames, developed from scratch by the author, with the aim of promoting motor and cognitive activity through patient entertainment. The ReMoVES platform differs from similar solutions for the automatic data processing features in support of the therapist. Three methods are presented: based on classic data analysis, on Support Vector Machine classification, and finally on Recurrent Neural Networks. The results describe how it is possible to discern patient gaming sessions with adequate performance from those with incorrect movements with an accuracy of up to 92%. The system has been used with real patients and a data database is made available to the scientific community. The aim is to encourage the dissemination of such data to lay the foundations for a comparison between similar studies