In the attempt to mitigate the effects of COVID-19 lockdown, most countries have recently authorized and promoted the adoption of e-learning and remote teaching technologies, often with the support of teleconferencing platforms. Unfortunately, not all students can benefit from the adoption of such a surrogate of their usual school. We were asked to devise a way to allow a community of children affected by the Rett genetic syndrome, and thus unable to communicate verbally, in writing or by gestures, to actively participate in remote rehabilitation and special education sessions by exploiting eye-gaze tracking. As not all subjects can access commercial eye-tracking devices, we investigated new ways to facilitate the access to eye gaze-based interaction for this specific case. The adopted communication platform is a videoconferencing software, so all we had at our disposal was a live video stream of the child. As a solution to the problem, we developed a software (named SWYG) that only runs at the “operator” side of the communication, at the side of the videoconferencing software, and does not require to install other software in the child’s computer. The preliminary results obtained are very promising and the software is ready to be deployed on a larger base. While this paper is being written, several children are finally able to communicate with their caregivers from home, without relying on expensive and cumbersome devices.

Passive human sensing approaches based on the analysis of the radio signals emitted by the most common wireless communication technologies have been steadily gaining momentum during the last decade. In this context, the Bluetooth technology, despite its widespread adoption in mobile and IoT applications, so far has not received all the attention it deserves. However, the introduction of the Bluetooth direction finding feature and the application of Artificial Intelligence techniques to the processing and analysis of the wireless signal for passive human sensing pave the way for novel Bluetooth-based passive human sensing applications, which will leverage Bluetooth Low Energy features, such as low power consumption, noise resilience, wide diffusion, and relatively low deployment cost. This paper provides a reasoned analysis of the data preprocessing and classification techniques proposed in the literature on Bluetooth-based remote passive human sensing, which is supported by a comparison of the reported accuracy results. Building on such results, the paper also identifies and discusses the multiple factors and operating conditions that explain the different accuracy values achieved by the considered techniques, and it draws the main research directions for the near future.

Telerehabilitation (TR) has been proven to be an effective tool in improving the adaptive skills of children and young adults with Multiple Disabilities (MDs). The application of a comprehensive set of new technologies reveals new opportunities for both physical and cognitive telerehabilitation, but there is no holistic approach in the case of genetic syndromes. In this paper we present reflections and early results of the TCTRS project that aims at implementing a telerehabilitation system capable of offering complete coverage of rehabilitation needs for people with Rett Syndrome, from both the physical and cognitive points of view. Moreover, the data acquired through the system can also represent a basis for machine learning applications to remotely support therapists and physicians. Our first tests on the system application show the great potential of our approach, in terms of feasibility and applicability, for both rehabilitation centers and families.

The aim of this study is to compare the performances of patients with Rett syndrome that were undergoing advanced telerehabilitation (ATR) and patients that were undergoing basic telerehabilitation (BTR). It was hypothesized that patients that were undergoing ATR training would have better improvement in nearly all the motor and cognitive scale scoring activities that were administered, thus showing reduced disability. A total of 20 young girls and women with a diagnosis of RTT, ranging from age 4 to 31 years old (Median: 12.50; IQR: 9.50–17.25) underwent a pre-test, treatment post-test 1, treatment, and post-test 2 procedure. The treatment consisted of either ATR or BTR, lasting 10 weeks with three sessions a week of about an hour. The results showed that the group with advanced telerehabilitation improved their performance better than the control group only in some neuropsychological measurements. The results are discussed in the light of critical factors of telerehabilitation.

Within the context of telerehabilitation, serious games have a significant role, but creating software for serious games is resource demanding. We present Proteo, a modular and open-source framework for developing serious games from scratch. We also present two serious game implementation examples with analysis of end user and therapist/researcher satisfaction. By involving a group of 11 specialized therapists and 9 end users we analyzed the Proteo’s user satisfaction. We found that both groups scored high for the level of involvement, and the therapists scored also high for the level of suitability. More in depth, both groups showed significant differences between positive and negative feelings, with positive feelings scoring higher than negative ones. Finally, the user level of suitability was reported as high while the difficulty of the system and the difficulty of the task were reported as low. Proteo has proven to be a useful tool to develop serious games for telerehabilitation and has been well accepted by the users involved in the evaluation tests.