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      Sensing Technologies for Autism Spectrum Disorder Screening and Intervention

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          Abstract

          This paper reviews the state-of-the-art in sensing technologies that are relevant for Autism Spectrum Disorder (ASD) screening and therapy. This disorder is characterized by difficulties in social communication, social interactions, and repetitive behaviors. It is diagnosed during the first three years of life. Early and intensive interventions have been shown to improve the developmental trajectory of the affected children. The earlier the diagnosis, the sooner the intervention therapy can begin, thus, making early diagnosis an important research goal. Technological innovations have tremendous potential to assist with early diagnosis and improve intervention programs. The need for careful and methodological evaluation of such emerging technologies becomes important in order to assist not only the therapists and clinicians in their selection of suitable tools, but to also guide the developers of the technologies in improving hardware and software. In this paper, we survey the literatures on sensing technologies for ASD and we categorize them into eye trackers, movement trackers, electrodermal activity monitors, tactile sensors, vocal prosody and speech detectors, and sleep quality assessment devices. We assess their effectiveness and study their limitations. We also examine the challenges faced by this growing field that need to be addressed before these technologies can perform up to their theoretical potential.

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          Most cited references108

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          Early behavioral intervention, brain plasticity, and the prevention of autism spectrum disorder.

          Advances in the fields of cognitive and affective developmental neuroscience, developmental psychopathology, neurobiology, genetics, and applied behavior analysis have contributed to a more optimistic outcome for individuals with autism spectrum disorder (ASD). These advances have led to new methods for early detection and more effective treatments. For the first time, prevention of ASD is plausible. Prevention will entail detecting infants at risk before the full syndrome is present and implementing treatments designed to alter the course of early behavioral and brain development. This article describes a developmental model of risk, risk processes, symptom emergence, and adaptation in ASD that offers a framework for understanding early brain plasticity in ASD and its role in prevention of the disorder.
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            Comparison of actigraphic, polysomnographic, and subjective assessment of sleep parameters in sleep-disordered patients.

            Comparison of polysomnography (PSG)-derived sleep parameters (total sleep time, sleep efficiency, and number of awakenings) to those derived from actigraphy and subjective questionnaires. Actigraphy is commonly used to assist sleep specialists in the diagnosis of various sleep and circadian-rhythm disorders. However, few validation studies incorporate large sample sizes, typical sleep clinic patients, or comparisons with subjective reports of sleep parameters. Clinical series with 100 consecutive sleep-disordered patients (69 men, 31 women, mean age of 49+/-14.7 years) at a tertiary sleep disorders center. Sensitivity, specificity, and accuracy measures were obtained from epoch-by-epoch comparison of PSG and actigraphic data. Subjective sleep parameter data were derived from questionnaires given to subjects in the morning following their recording night. We found that total sleep time and sleep efficiency did not significantly differ between PSG data and the combined data obtained from actigraphy and subjective reports. Using a high-threshold (low-wake-sensitivity) actigraphic algorithm, the number of awakenings was not significantly different from those detected by PSG. We recommend the use of subjective data as an adjunct to actigraphic data in estimating total sleep time and sleep efficiency in sleep-disordered patients, especially those with disorders of excessive somnolence.
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              Sleep problems in autism spectrum disorders: prevalence, nature, & possible biopsychosocial aetiologies.

              As considerably more people are diagnosed with an autism spectrum disorder (ASD), interest in the associated behaviours, including sleep problems has increased. This has resulted in a subsequent increase in the research related to the sleep problems occurring in people with an ASD. This article summarizes and evaluates the current literature related to a) the higher prevalence of a sleep problem compared to typically developing children, b) the specific types of sleep problems for people with an ASD, and c) the possible aetiology of sleep problems in the ASDs within a biopsychosocial framework. It is concluded that recent studies confirm that the majority of this population are likely to experience sleep difficulties, with settling issues in children with an ASD the most commonly reported. However, exploration of the types of sleep difficulties and associated aetiological factors in the ASDs is still in its infancy.
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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                27 December 2016
                January 2017
                : 17
                : 1
                : 46
                Affiliations
                [1 ]Mechanical and Industrial Engineering Department, Qatar University, Doha 2713, Qatar
                [2 ]Biomedical Engineering Department, George Washington University, Washington, DC 20052, USA; hifzajaved1@ 123456gmail.com
                [3 ]Center for Pediatric Neurology, Cleveland Clinic, and Case Western Reserve University, Cleveland, OH 44106, USA; ALDOSAM@ 123456ccf.org
                [4 ]Center for Autism Pediatric Institute, Cleveland Clinic and Cleveland Clinic Lerner College of Medicine, Cleveland, OH 44195, USA; FRAZIET2@ 123456ccf.org
                [5 ]Al Jalila Children’s Specialty Hospital, Dubai, United Arab Emirates; hoelbashir@ 123456gmail.com
                Author notes
                [* ]Correspondence: john.cabibihan@ 123456qu.edu.qa ; Tel.: +974-4403-4368
                [†]

                Current address: College of Engineering, Qatar University, Doha 2713, Qatar.

                Article
                sensors-17-00046
                10.3390/s17010046
                5298619
                28036004
                477ad211-151f-496c-adb8-eaa43e47e3f4
                © 2016 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 03 August 2016
                : 16 December 2016
                Categories
                Article

                Biomedical engineering
                autism spectrum disorder,eye trackers,movement trackers,electrodermal activity monitors,prosody and speech detectors,tactile sensing,social robotics,sleep quality assessment

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