Giovanni Pioggia

A mobile data collection platform for mental health research

Ubiquitous computing technologies offer exciting new possibilities for monitoring and analyzing user’s experience in real time. In this paper, we describe the design and development of Psychlog, a mobile phone platform designed to collect users’ psychological, physiological, and activity information for mental health research. The tool allows administering self-report questionnaires at specific times or randomly within a day. The system also permits to collect heart rate and activity information from a wireless electrocardiogram equipped with a three-axial accelerometer. By combining self-reports with heart rate and activity data, the application makes it possible to investigate the relationship between psychological, physiological, and behavioral variables, as well as to monitor their fluctuations over time. The software runs on Windows mobile operative system and is available as open source (http://sourceforge.net/projects/psychlog/).

An android for enhancing social skills and emotion recognition in people with autism

It is well documented that the processing of social and emotional information is impaired in people with autism. Recent studies have shown that individuals, particularly those with high functioning autism, can learn to cope with common social situations if they are made to enact possible scenarios they may encounter in real life during therapy. The main aim of this work is to describe an interactive life-like facial display (FACE) and a supporting therapeutic protocol that will enable us to verify if the system can help children with autism to learn, identify, interpret, and use emotional information and extend these skills in a socially appropriate, flexible, and adaptive context. The therapeutic setup consists of a specially equipped room in which the subject, under the supervision of a therapist, can interact with FACE. The android display and associated control system has automatic facial tracking, expression recognition, and eye tracking. The treatment scheme is based on a series of therapist-guided sessions in which a patient communicates with FACE through an interactive console. Preliminary data regarding the exposure to FACE of two children are reported.

Interactive Technologies for Autistic Children: A Review

Recently, there have been considerable advances in the research on innovative information communication technology (ICT) for the education of people with autism. This review focuses on two aims: (1) to provide an overview of the recent ICT applications used in the treatment of autism and (2) to focus on the early development of imitation and joint attention in the context of children with autism as well as robotics. There have been a variety of recent ICT applications in autism, which include the use of interactive environments implemented in computers and special input devices, virtual environments, avatars and serious games as well as telerehabilitation. Despite exciting preliminary results, the use of ICT remains limited. Many of the existing ICTs have limited capabilities and performance in actual interactive conditions. Clinically, most ICT proposals have not been validated beyond proof of concept studies. Robotics systems, developed as interactive devices for children with autism, have been used to assess the child’s response to robot behaviors; to elicit behaviors that are promoted in the child; to model, teach and practice a skill; and to provide feedback on performance in specific environments (e.g., therapeutic sessions). Based on their importance for both early development and for building autonomous robots that have humanlike abilities, imitation, joint attention and interactive engagement are key issues in the development of assistive robotics for autism and must be the focus of further research.

An electronic nose for odour annoyance assessment

Although in most cases annoying atmospheric emissions do not menace public health, they are less and less tolerated because of the effects on quality of life. Several approaches have been proposed to face this problem but none of them offers a completely satisfying solution. The development of electronic noses, which promise to mimic human sense of smell by means of a sensor array and a pattern recognition model, offers new interesting perspectives. In this paper, an electronic nose based on conducting polymer sensors and a fuzzy logic-based pattern recognition system is tested with waste water samples, obtaining 87% recognition rate on the test set. Current limits of this new technology are discussed and a strategy for their overcoming is proposed.

Coexistence of amplitude and frequency modulations in intracellular calcium dynamics

The complex dynamics of intracellular calcium regulates cellular responses to information encoded in extracellular signals. Here we study the encoding of these external signals in the context of the Li-Rinzel model. We show that by control of biophysical parameters the information can be encoded in amplitude modulation (AM), frequency modulation (FM), or mixed (AM and FM) modulation. We briefly discuss the possible implications of this role of information encoding for astrocytes.

On the application of quantitative EEG for characterizing autistic brain: a systematic review

Autism-Spectrum Disorders (ASD) are thought to be associated with abnormalities in neural connectivity at both the global and local levels. Quantitative electroencephalography (QEEG) is a non-invasive technique that allows a highly precise measurement of brain function and connectivity. This review encompasses the key findings of QEEG application in subjects with ASD, in order to assess the relevance of this approach in characterizing brain function and clustering phenotypes. QEEG studies evaluating both the spontaneous brain activity and brain signals under controlled experimental stimuli were examined. Despite conflicting results, literature analysis suggests that QEEG features are sensitive to modification in neuronal regulation dysfunction which characterize autistic brain. QEEG may therefore help in detecting regions of altered brain function and connectivity abnormalities, in linking behavior with brain activity, and subgrouping affected individuals within the wide heterogeneity of ASD. The use of advanced techniques for the increase of the specificity and of spatial localization could allow finding distinctive patterns of QEEG abnormalities in ASD subjects, paving the way for the development of tailored intervention strategies.

Personal Health System architecture for stress monitoring and support to clinical decisions

Developments in computational techniques including clinical decision support systems, information processing, wireless communication and data mining hold new premises in Personal Health Systems. Pervasive Healthcare system architecture finds today an effective application and represents in perspective a real technological breakthrough promoting a paradigm shift from diagnosis and treatment of patients based on symptoms to diagnosis and treatment based on risk assessment. Such architectures must be able to collect and manage a large quantity of data supporting the physicians in their decision process through a continuous pervasive remote monitoring model aimed to enhance the understanding of the dynamic disease evolution and personal risk. In this work an automatic simple, compact, wireless, personalized and cost efficient pervasive architecture for the evaluation of the stress state of individual subjects suitable for prolonged stress monitoring during normal activity is described. A novel integrated processing approach based on an autoregressive model, artificial neural networks and fuzzy logic modeling allows stress conditions to be automatically identified with a mobile setting analysing features of the electrocardiographic signals and human motion. The performances of the reported architecture were assessed in terms of classification of stress conditions.

Autism and social robotics: A systematic review.

Social robotics could be a promising method for Autism Spectrum Disorders (ASD) treatment. The aim of this article is to carry out a systematic literature review of the studies on this topic that were published in the last 10 years. We tried to address the following questions: can social robots be a useful tool in autism therapy? We followed the PRISMA guidelines, and the protocol was registered within PROSPERO database (CRD42015016158). We found many positive implications in the use of social robots in therapy as for example: ASD subjects often performed better with a robot partner rather than a human partner; sometimes, ASD patients had, toward robots, behaviors that TD patients had toward human agents; ASDs had a lot of social behaviors toward robots; during robotic sessions, ASDs showed reduced repetitive and stereotyped behaviors and, social robots manage to improve spontaneous language during therapy sessions. Therefore, robots provide therapists and researchers a means to connect with autistic subjects in an easier way, but studies in this area are still insufficient. It is necessary to clarify whether sex, intelligence quotient, and age of participants affect the outcome of therapy and whether any beneficial effects only occur during the robotic session or if they are still observable outside the clinical/experimental context. Autism Res 2016, 9: 165–183.

An efficient unsupervised fetal QRS complex detection from abdominal maternal ECG.

Non-invasive fetal heart rate is of great relevance in clinical practice to monitor fetal health state during pregnancy. To date, however, despite significant advances in the field of electrocardiography, the analysis of abdominal fetal ECG is considered a challenging problem for biomedical and signal processing communities. This is mainly due to the low signal-to-noise ratio of fetal ECG and difficulties in cancellation of maternal QRS complexes, motion and electromyographic artefacts. In this paper we present an efficient unsupervised algorithm for fetal QRS complex detection from abdominal multichannel signal recordings combining ICA and maternal ECG cancelling, which outperforms each single method. The signal is first pre-processed to remove impulsive artefacts, baseline wandering and power line interference. The following steps are then applied: maternal ECG extraction through independent component analysis (ICA); maternal QRS detection; maternal ECG cancelling through weighted singular value decomposition; enhancing of fetal ECG through ICA and fetal QRS detection. We participated in the Physionet/Computing in Cardiology Challenge 2013, obtaining the top official scores of the challenge (among 53 teams of participants) of event 1 and event 2 concerning fetal heart rate and fetal interbeat intervals estimation section. The developed algorithms are released as open-source on the Physionet website.

Experiential Virtual Scenarios With Real-Time Monitoring (Interreality) for the Management of Psychological Stress: A Block Randomized Controlled Trial

Background The recent convergence between technology and medicine is offering innovative methods and tools for behavioral health care. Among these, an emerging approach is the use of virtual reality (VR) within exposure-based protocols for anxiety disorders, and in particular posttraumatic stress disorder. However, no systematically tested VR protocols are available for the management of psychological stress. Objective Our goal was to evaluate the efficacy of a new technological paradigm, Interreality, for the management and prevention of psychological stress. The main feature of Interreality is a twofold link between the virtual and the real world achieved through experiential virtual scenarios (fully controlled by the therapist, used to learn coping skills and improve self-efficacy) with real-time monitoring and support (identifying critical situations and assessing clinical change) using advanced technologies (virtual worlds, wearable biosensors, and smartphones). Methods The study was designed as a block randomized controlled trial involving 121 participants recruited from two different worker populations—teachers and nurses—that are highly exposed to psychological stress. Participants were a sample of teachers recruited in Milan (Block 1: n=61) and a sample of nurses recruited in Messina, Italy (Block 2: n=60). Participants within each block were randomly assigned to the (1) Experimental Group (EG): n=40; B1=20, B2=20, which received a 5-week treatment based on the Interreality paradigm; (2) Control Group (CG): n=42; B1=22, B2=20, which received a 5-week traditional stress management training based on cognitive behavioral therapy (CBT); and (3) the Wait-List group (WL): n=39, B1=19, B2=20, which was reassessed and compared with the two other groups 5 weeks after the initial evaluation. Results Although both treatments were able to significantly reduce perceived stress better than WL, only EG participants reported a significant reduction (EG=12% vs CG=0.5%) in chronic “trait” anxiety. A similar pattern was found for coping skills: both treatments were able to significantly increase most coping skills, but only EG participants reported a significant increase (EG=14% vs CG=0.3%) in the Emotional Support skill. Conclusions Our findings provide initial evidence that the Interreality protocol yields better outcomes than the traditionally accepted gold standard for psychological stress treatment: CBT. Consequently, these findings constitute a sound foundation and rationale for the importance of continuing future research in technology-enhanced protocols for psychological stress management. Trial Registration ClinicalTrials.gov: NCT01683617; http://clinicaltrials.gov/show/NCT01683617 (Archived by WebCite at http://www.webcitation.org/6QnziHv3h).