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Deep Learning for Automatic Stereotypical Motor Movement Detection using Wearable Sensors in Autism Spectrum Disorders [article]

Nastaran Mohammadian Rad, Seyed Mostafa Kia, Calogero Zarbo, Twan van Laarhoven, Giuseppe Jurman, Paola Venuti, Elena Marchiori, Cesare Furlanello
2017 arXiv   pre-print
Autism Spectrum Disorders are associated with atypical movements, of which stereotypical motor movements (SMMs) interfere with learning and social interaction.  ...  We propose a new application of the deep learning to facilitate automatic SMM detection using multi-axis IMUs.  ...  Acknowledgments The authors would like to thank the members of MPBA lab for their kind collaboration in collecting the simulated data.  ... 
arXiv:1709.05956v1 fatcat:uz3h6ctyrvhcfm32nhav72ako4

Computer Vision Techniques for Autism Symptoms Detection and Recognition: A Survey

Esraa Sadek, Noha AbdElSabour Seada, Said Ghoniemy
2020 International Journal of Intelligent Computing and Information Sciences  
This survey provides a comprehensive study of autism spectrum disorder, its types, symptoms, prevalence, and developments in its diagnosing.  ...  Computational technologies, especially computer-vision, machine learning and neural networks techniques have added great advances in detecting autism and these techniques are comprehensively reviewed in  ...  Stereotypical Motor Movements (SMM) in autism (for example, body shaking, mouthing, and hand flapping [23] ) can delays educational and social development.  ... 
doi:10.21608/ijicis.2020.46360.1034 fatcat:hn27qhwgsbeahbrnybemzmlwji

WearSense: Detecting Autism Stereotypic Behaviors through Smartwatches

Amir Amiri, Nicholas Peltier, Cody Goldberg, Yan Sun, Anoo Nathan, Shivayogi Hiremath, Kunal Mankodiya
2017 Healthcare  
Autism is a complex developmental disorder that affects approximately 1 in 68 children (according to the recent survey conducted by the Centers for Disease Control and Prevention-CDC) in the U.S., and  ...  We have designed an Internet-of-Things (IoT) framework named WearSense that leverages the sensing capabilities of modern smartwatches to detect stereotypic behaviors in children with autism.  ...  The authors developed automatic SMM detection systems based on a deep learning architecture.  ... 
doi:10.3390/healthcare5010011 pmid:28264474 pmcid:PMC5371917 fatcat:qsj55hl3nndevm44ykm2rfokje

Novelty Detection using Deep Normative Modeling for IMU-Based Abnormal Movement Monitoring in Parkinson's Disease and Autism Spectrum Disorders

Nastaran Mohammadian Rad, Twan van Laarhoven, Cesare Furlanello, Elena Marchiori
2018 Sensors  
Detecting and monitoring of abnormal movement behaviors in patients with Parkinson's Disease (PD) and individuals with Autism Spectrum Disorders (ASD) are beneficial for adjusting care and medical treatment  ...  In this paper, we propose deep normative modeling as a probabilistic novelty detection method, in which we model the distribution of normal human movements recorded by wearable sensors and try to detect  ...  Related Works Recent studies on automatic SMM and FOG detection using wearable sensors have mainly focused on applying supervised machine learning and deep learning approaches, such as Convolutional Neural  ... 
doi:10.3390/s18103533 fatcat:il3crauryfct7ogsn7xflypnfy

Computer vision in autism spectrum disorder research: a systematic review of published studies from 2009 to 2019

Ryan Anthony J. de Belen, Tomasz Bednarz, Arcot Sowmya, Dennis Del Favero
2020 Translational Psychiatry  
The current state of computer vision methods applied to autism spectrum disorder (ASD) research has not been well established.  ...  The findings in this review suggest that computer vision analysis is useful for the quantification of behavioural/biological markers which can further lead to a more objective analysis in autism research  ...  Introduction Visual observation and analysis of children's natural behaviours are instrumental to the early detection of developmental disorders, including autism spectrum disorder (ASD).  ... 
doi:10.1038/s41398-020-01015-w pmid:32999273 fatcat:7sfld3ry2baznav5c7ztwxhxkq

Hybrid Feature Vector for Screening of Autistic People using Deep Learning

2022 International Journal of Intelligent Engineering and Systems  
Screening tools play a vital role in Autism Spectrum Disorder (ASD) and in the detection of related Sensory Processing Disorder.  ...  For the purpose of experimentation, we have used Autism Spectrum Quotient AQ10 dataset using fully connected Deep Neural Network (DNN) to train the autism detection model and Facial Expression Recognition  ...  Acknowledgments The authors wish to thank the anonymous reviewers for their useful suggestions that helped in improving the quality of this paper.  ... 
doi:10.22266/ijies2022.0228.35 fatcat:jovtbopxcrbarbrjd2eemqhr2q

Artificial Intelligence in Autism Assessment

Panagiota Anagnostopoulou, Vasiliki Alexandropoulou, Georgia Lorentzou, Andriana Lykothanasi, Polyxeni Ntaountaki, Athanasios Drigas
2020 International Journal of Emerging Technologies in Learning (iJET)  
Thus, the research team of this paper presents some applications of artificial intelligence that are used already or are in a preliminary phase aiming to highlight the use of smart technology in the diagnosing  ...  process of autism.  ...  Following this direction, many studies focused on using accelerometer sensors for detecting the stereotypical behaviors of the children with ASD.  ... 
doi:10.3991/ijet.v15i06.11231 fatcat:djmgocpodbcvbpcajhrycpkov4

Pervasive Healthcare-A Comprehensive Survey of Tools and Techniques [article]

Deepak Uniyal, Vaskar Raychoudhury
2014 arXiv   pre-print
In this paper, we carry out a comprehensive coverage of several common disorders addressed by pervasive healthcare in recent years.  ...  Pervasive healthcare is an emerging technology that aims to provide round-the-clock monitoring of several vital signs of patients using various health sensors, specialized communication protocols, and  ...  Autism Autism is a group of lifelong complex disorders of brain development, collectively called Autism Spectrum Disorder (ASD) [Yates and Couteur 2013] .  ... 
arXiv:1411.1821v1 fatcat:woizkaerffep7meb7dltj7arwq

A Novel Deep Learning Approach for Recognizing Stereotypical Motor Movements within and across Subjects on the Autism Spectrum Disorder

Lamyaa Sadouk, Taoufiq Gadi, El Hassan Essoufi
2018 Computational Intelligence and Neuroscience  
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by persistent difficulties including repetitive patterns of behavior known as stereotypical motor movements (SMM).  ...  In this context, we propose a deep learning approach for SMM recognition, namely, convolutional neural networks (CNN) in time and frequency-domains.  ...  Supplementary Materials Values used to plot histograms of Figure  ... 
doi:10.1155/2018/7186762 pmid:30111994 pmcid:PMC6077579 fatcat:dvbc3z3p4feuxb4i4cbmo62cce

Towards Motor-Based Early Detection of Autism Red Flags: Enabling Technology and Exploratory Study Protocol

Mariasole Bondioli, Stefano Chessa, Antonio Narzisi, Susanna Pelagatti, Michele Zoncheddu
2021 Sensors  
Observing how children manipulate objects while they are playing can help detect possible autism spectrum disorders (ASD) at an early stage.  ...  For this purpose, specialists seek the so-called "red-flags" of motor signature of ASD for more precise diagnostic tests.  ...  Sensors 2021, 21, 1971  ... 
doi:10.3390/s21061971 pmid:33799643 fatcat:ahqk7bmkszahjf2blec6kx4ah4

Deep Learning for Neuroimaging-based Diagnosis and Rehabilitation of Autism Spectrum Disorder: A Review [article]

Marjane Khodatars, Afshin Shoeibi, Navid Ghassemi, Mahboobeh Jafari, Ali Khadem, Delaram Sadeghi, Parisa Moridian, Sadiq Hussain, Roohallah Alizadehsani, Assef Zare, Abbas Khosravi, Saeid Nahavandi (+2 others)
2020 arXiv   pre-print
Accurate diagnosis of Autism Spectrum Disorder (ASD) is essential for its management and rehabilitation.  ...  AI techniques comprise traditional machine learning (ML) approaches and deep learning (DL) techniques.  ...  Further, the keywords "ASD", "Autism Spectrum Disorder" and "Deep Learning" were used to select the papers. The papers are analyzed till June 03th, 2020 by the authors (AK, SN).  ... 
arXiv:2007.01285v3 fatcat:gtiblvspm5gn7kn2f7x4j474xm

Evaluating the autonomy of children with autism spectrum disorder in washing hands: a deep-learning approach

Daniele Berardini, Lucia Migliorelli, Sara Moccia, Marcello Naldini, Gioia De Angelis, Emanuele Frontoni
2020 2020 IEEE Symposium on Computers and Communications (ISCC)  
The experimental results are reported in Sec. IV and discussed in Sec. V, Sec. VI concludes the paper.  ...  In [6] and [7] , stereotypical motor movements of children with ASD, are detected by analysing data from wearable sensors (e.g., accelerometers data) via standard machine learning (ML) and DL meth-ods  ...  More in general, the use of wearable sensors may alter the behavior of the monitored child, especially for the youngest ones.  ... 
doi:10.1109/iscc50000.2020.9219648 dblp:conf/iscc/BerardiniMMNAF20 fatcat:j74d4sxk4fb7hhzvgqknv6toru

Requirements for Robotic Interpretation of Social Signals "in the Wild": Insights from Diagnostic Criteria of Autism Spectrum Disorder

Madeleine E Bartlett, Cristina Costescu, Paul Baxter, Serge Thill
2020 Information  
We do this by considering what it would entail to automate the diagnosis of Autism Spectrum Disorder (ASD).  ...  For ASD diagnosis, we provide a classification of criteria based on whether or not they depend on covert information and highlight present-day possibilities for supporting therapists in diagnosis through  ...  Here, we focus on the automation of the diagnosis of Autism Spectrum Disorder (ASD) for this purpose.  ... 
doi:10.3390/info11020081 fatcat:pwtplx2x2vco5i27rrvvkapp7q

An Observational Study With the Janssen Autism Knowledge Engine (JAKE®) in Individuals With Autism Spectrum Disorder

Seth L. Ness, Abigail Bangerter, Nikolay V. Manyakov, David Lewin, Matthew Boice, Andrew Skalkin, Shyla Jagannatha, Meenakshi Chatterjee, Geraldine Dawson, Matthew S. Goodwin, Robert Hendren, Bennett Leventhal (+8 others)
2019 Frontiers in Neuroscience  
Objective: The Janssen Autism Knowledge Engine (JAKE®) is a clinical research outcomes assessment system developed to more sensitively measure treatment outcomes and identify subpopulations in autism spectrum  ...  Lessons from the study will optimize JAKE for use in clinical trials to assess ASD interventions.  ...  The funder was not involved in the study design or collection, analysis, or interpretation of the data.  ... 
doi:10.3389/fnins.2019.00111 pmid:30872988 pmcid:PMC6402449 fatcat:35as3fegq5dnned2z5pena5fky

Chronic-Pain Protective Behavior Detection with Deep Learning [article]

Chongyang Wang, Temitayo A. Olugbade, Akhil Mathur, Amanda C. De C. Williams, Nicholas D. Lane, Nadia Bianchi-Berthouze
2020 arXiv   pre-print
In this paper, we investigate the use of deep learning to detect protective behavior across activity types, using wearable motion capture and surface electromyography data collected from healthy participants  ...  As rehabilitation moves outside the clinic, technology should automatically detect such behavior as to provide similar personalized support.  ...  wrists and chest of 6 people with autism spectrum disorder.  ... 
arXiv:1902.08990v3 fatcat:gay3udzddrgsta6l2zug5pc7ge
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