Applications of Robotics for Autism Spectrum Disorder: a Scoping Review

Robotic therapies are receiving growing interest in the autism field, especially for the improvement of social skills of children, enhancing traditional human interventions. In this work, we conduct a scoping review of the literature in robotics for autism, providing the largest review on this field from the last five years. Our work underlines the need to better characterize participants and to increase the sample size. It is also important to develop homogeneous training protocols to analyse and compare the results. Nevertheless, 7 out of the 10 Randomized control trials reported a significant impact of robotic therapy. Overall, robot autonomy, adaptability and personalization as well as more standardized outcome measures were pointed as the most critical issues to address in future research

Development of an Interactive Total Body Robot Enhanced Imitation Therapy for ASD children

Autism is a neurodevelopmental disorder in which the available therapies target the improvement of social skills, in order to ensure a high quality of life for the child. The use of Social Assistive Robots offers new therapeutic possibilities in which robots can act as therapy enhancers. IOGIOCO project emerges in this framework: it aims at the development of a Robot- Assisted Therapy protocol for the treatment of Autism Spectrum Disorder, through gesture training. The definition of these gestures and their recognition by the robot are parameters that directly affect the engagement of the children. However, the design of a protocol becomes harder in a highly unconstrained environment. Therefore, the current work aims at expanding the gesture set and improving the gesture recognition algorithm available in the IOGIOCO platform. More specifically, total body gestures have been added to the available upper limbs movements, and a custom Activity Detection method has been developed, which allows the identification of the time window in which a gesture is performed. The insertion of this method on a recognition algorithm based on a ResNet, a particular kind of Convolutional Neural Network, improved its F1-score from 57% obtained with the previously-available version, in a dataset of ASD children, to 76%, demonstrating the effectiveness of the Activity Detection method. Furthermore, the expansion of the interaction possibilities to total body movements was positively evaluated by the clinical staff, increasing the engagement of patients and the set of possible trained skills. Therefore, the results of the current work are encouraging. To reinforce the conclusions drawn, the proposed algorithm should be tested in real time on several autistic children within a complete Randomized Clinical Trial, also to study the effectiveness of this type of treatment. From the technical point of view, further improvements of the developed methodology should tackle the remained issues, such as further increasing the recognition capability, especially in the transitions from sitting to standing, that proved to be a hard task for the developed method

Sharing Worlds: Design of a Real-Time Attention Classifier for Robotic Therapy of ASD Children

Joint attention is the capacity of sharing attention between two agents and an aspect of the environment, through the use of different cues, namely gaze. This capacity is of paramount importance for social skills. People with Autism Spectrum Disorder (ASD) present certain deficits in joint attention. Therefore, there is an increasing interest in finding therapies to improve this skill. Some of these therapies include robots since they are known to be attractive to people with autism due to their motivation ability and predictability when compared with humans. In this line, we have designed a real-time attention classifier for a triadic robotic therapy, using Gaze360 and geometrical considerations of the scene. We were able to classify the gaze of the therapist and the one of the child during the whole session, even in a highly unconstrained scenario with a single camera, achieving a mean accuracy of 59%. This classifier can be used for the measurement of joint attention, an important metric for the development of adaptive robotic therapies, where increasing levels of difficulty and engagement are provided dependent on the ASD children, who are characterised by high heterogeneity. Future work will pass by the calculation of this metric and integration on a robotic platform for ASD therapy to understand the impact of these robotic therapies in improving ASD symptoms, specifically on how ASD children share their attention with other people present in the rehabilitation scenarios

Safety and efficacy of everolimus, a mTOR inhibitor, as single agent in a phase 1/2 study in patients with myelofibrosis

In addition to dysregulated JAK/STAT signaling, activation of the AKT/mTOR pathway occurs in myelofibrosis, a myeloproliferative neoplasm with no approved therapies. We conducted a phase 1/2 study with everolimus, an mTOR inhibitor, in 39 high- or intermediate-risk primary or postpolycythemia vera/postessential thrombocythemia myelofibrosis subjects. Responses were evaluated in 30 patients of phase 2. No dose-limiting toxicity was observed in phase 1 up to 10 mg/d. When this dose was used in phase 2, grade ≥ 3 toxicities were infrequent; the commonest toxicity was grade 1-2 stomatitis. Rapid and sustained splenomegaly reduction of > 50% and > 30% occurred in 20% and 44% of subjects, respectively. A total of 69% and 80% experienced complete resolution of systemic symptoms and pruritus. Response in leukocytosis, anemia, and thrombocytosis occurred in 15%-25%. Clinical responses were not associated with reduced JAK2V617F burden, circulating CD34+ cells, or cytokine levels, whereas CCDN1 mRNA and phospho-p70S6K level, known targets of mTOR, and WT1 mRNA were identified as possible biomarkers associated with response. Response rate was 60% when European Network for Myelofibrosis criteria were used (8 major, 7 moderate, 3 minor responses) or 23% when IWG-MRT criteria (1 partial response, 6 clinical improvements) were used. These results provide proof-of-concept that targeting mTOR pathway in myelofibrosis may be clinically relevant