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Convolutional Neural Network for Stereotypical Motor Movement Detection in Autism [article]

Nastaran Mohammadian Rad, Andrea Bizzego, Seyed Mostafa Kia, Giuseppe Jurman, Paola Venuti, Cesare Furlanello
2016 arXiv   pre-print
Autism Spectrum Disorders (ASDs) are often associated with specific atypical postural or motor behaviors, of which Stereotypical Motor Movements (SMMs) have a specific visibility.  ...  Wireless accelerometer sensing technology can provide a valid infrastructure for real-time SMM detection, however such variability remains a problem also for machine learning methods, in particular whenever  ...  Stereotypical Motor Movements (SMMs) in autism (such as body rocking, mouthing, and complex hand movements) [10] can significantly restrict the learning and social interactions.  ... 
arXiv:1511.01865v3 fatcat:64dumjm42vdntdg6ya5wqiseeq

Activity Recognition with Moving Cameras and Few Training Examples: Applications for Detection of Autism-Related Headbanging [article]

Peter Washington, Aaron Kline, Onur Cezmi Mutlu, Emilie Leblanc, Cathy Hou, Nate Stockham, Kelley Paskov, Brianna Chrisman, Dennis P. Wall
2021 arXiv   pre-print
We create a computer vision classifier for detecting head banging in home videos using a time-distributed convolutional neural network (CNN) in which a single CNN extracts features from each frame in the  ...  the train set was in the test set for all folds.  ...  ACKNOWLEDGMENTS This work was supported in part by funds to DPW from the National Institutes of Health (1R01EB025025-01, 1R21HD091500-01, 1R01LM013083), the National Science Foundation  ... 
arXiv:2101.03478v1 fatcat:vqevbhu4ojenbgmfzjbbyro7ni

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  
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  ...  Also, medical assisting computer vision-based framework is proposed to detect observable autism symptoms.  ...  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

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  
For this purpose, specialists seek the so-called "red-flags" of motor signature of ASD for more precise diagnostic tests.  ...  Observing how children manipulate objects while they are playing can help detect possible autism spectrum disorders (ASD) at an early stage.  ...  Neural Network Models Training and Validation As discussed in the previous section, we considered two neural network models, namely TDNN and RNN, to implement the classification of the movements of the  ... 
doi:10.3390/s21061971 pmid:33799643 fatcat:ahqk7bmkszahjf2blec6kx4ah4

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  
In this context, we propose a deep learning approach for SMM recognition, namely, convolutional neural networks (CNN) in time and frequency-domains.  ...  Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by persistent difficulties including repetitive patterns of behavior known as stereotypical motor movements (SMM).  ...  Research Background on Convolutional Neural Networks.  ... 
doi:10.1155/2018/7186762 pmid:30111994 pmcid:PMC6077579 fatcat:dvbc3z3p4feuxb4i4cbmo62cce

Machine learning applications to recognize autism and Alzheimer's disease [chapter]

Saman Sarraf
2019 Neurological Disorders and Imaging Physics, Volume 3  
On the stability of the rectilinear motions in the sextupole rf trap C. M.  ...  A simple deposition method for self-assembling single crystalline hybrid perovskite nanostructures Wen-Rong Xie, Bin Liu, Tao Tao et al.  ...  The proposed architecture for stereotypical motor movement detection in the static feature space utilized a three-layer CNN.  ... 
doi:10.1088/978-0-7503-1793-1ch1 fatcat:hoi4lebxzbexzitq3fxkmw7pci

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 use a convolutional neural network (CNN) to learn a discriminative feature space from raw data.  ...  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

WearSense: Detecting Autism Stereotypic Behaviors through Smartwatches

Amir Amiri, Nicholas Peltier, Cody Goldberg, Yan Sun, Anoo Nathan, Shivayogi Hiremath, Kunal Mankodiya
2017 Healthcare  
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.  ...  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  ...  Mohammadian Rad [5] presented a wireless inertial sensing technology that offers an infrastructure for real-time Stereotypical Motor Movements (SMM) detection.  ... 
doi:10.3390/healthcare5010011 pmid:28264474 pmcid:PMC5371917 fatcat:qsj55hl3nndevm44ykm2rfokje

Automated Detection of Autism Spectrum Disorder Using a Convolutional Neural Network

Zeinab Sherkatghanad, Mohammadsadegh Akhondzadeh, Soorena Salari, Mariam Zomorodi-Moghadam, Moloud Abdar, U. Rajendra Acharya, Reza Khosrowabadi, Vahid Salari
2020 Frontiers in Neuroscience  
Convolutional neural networks (CNN) have enabled significant progress in speech recognition, image classification, automotive software engineering, and neuroscience.  ...  Method: In this paper, we focus on the automated detection of autism spectrum disorder (ASD) using CNN with a brain imaging dataset.  ...  The stereotypical motor movements (SMM) in autism patients are body rocking and complex hand movements, which will affect learning and social skills.  ... 
doi:10.3389/fnins.2019.01325 pmid:32009868 pmcid:PMC6971220 fatcat:r5x54ufskffyvpdwswa6fpvzyy

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  ...  abnormal movements in patients with PD and ASD in a novelty detection framework.  ...  Spectrum Disorder FOG Freezing Of Gait SMM Stereotypical Motor Movements DAE Denoising Autoencoder GEVD Generalized Extreme Value Distribution CNN Convolutional Neural Network ReLU Rectified  ... 
doi:10.3390/s18103533 fatcat:il3crauryfct7ogsn7xflypnfy

Using 2D Video-based Pose Estimation for Automated Prediction of Autism Spectrum Disorders in Preschoolers [article]

Nada Kojovic, Shreyasvi Natraj, Sharada Prasanna Mohanty, Thomas Maillart, Marie Schaer
2021 medRxiv   pre-print
For instance, the atypical nonverbal behaviors manifest through global patterns of atypical postures and movements, fewer gestures used and often decoupled from visual contact, facial affect, speech.  ...  Here, we tested the hypothesis that a deep neural network trained on the non-verbal aspects of social interaction can effectively differentiate between children with ASD and their typically developing  ...  Acknowledgments We express our utmost gratitude to all families that took part in this study. We thank our colleagues for their precious contribution to data collection.  ... 
doi:10.1101/2021.04.01.21254463 fatcat:qj4yhsydrvbphhik56ywncwbty

Hybrid Feature Vector for Screening of Autistic People using Deep Learning

2022 International Journal of Intelligent Engineering and Systems  
FER2013 dataset to train the emotion recognition model using Convolutional Neural Network (CNN).  ...  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

Using 2D video-based pose estimation for automated prediction of autism spectrum disorders in young children

Nada Kojovic, Shreyasvi Natraj, Sharada Prasanna Mohanty, Thomas Maillart, Marie Schaer
2021 Scientific Reports  
For instance, the atypical nonverbal behaviors manifest through global patterns of atypical postures and movements, fewer gestures used and often decoupled from visual contact, facial affect, speech.  ...  Here, we tested the hypothesis that a deep neural network trained on the non-verbal aspects of social interaction can effectively differentiate between children with ASD and their typically developing  ...  Acknowledgements We express our utmost gratitude to all families that took part in this study. We thank our colleagues for their precious contribution to data collection.  ... 
doi:10.1038/s41598-021-94378-z pmid:34301963 pmcid:PMC8302646 fatcat:s7flfjtnrndcjmjn6eeipwbciu

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 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  ...  The primary objective of this systematic review is to examine how computer vision analysis has been useful in ASD diagnosis, therapy and autism research in general.  ...  A deep convolutional neural network (DCNN) for feature extraction followed by an SVM for classification has been trained by Shukla et al. 60 to detect whether a person in an image has ASD, cerebral palsy  ... 
doi:10.1038/s41398-020-01015-w pmid:32999273 fatcat:7sfld3ry2baznav5c7ztwxhxkq

Wearable-Sensors-Based Platform for Gesture Recognition of Autism Spectrum Disorder Children Using Machine Learning Algorithms

Uzma Abid Siddiqui, Farman Ullah, Asif Iqbal, Ajmal Khan, Rehmat Ullah, Sheroz Paracha, Hassan Shahzad, Kyung-Sup Kwak
2021 Sensors  
The main objective of this work is to develop a wearable-sensor-based IoT platform for gesture recognition in children with autism spectrum disorder (ASD).  ...  Time- and frequency-domain features are extracted from the sensors' data, which are classified using k-nearest neighbor (KNN), decision tree, neural network, and random forest models.  ...  Rad used a convolutional neural network for the detection of SMM using a accelerometer sensor [20] .  ... 
doi:10.3390/s21103319 pmid:34064750 fatcat:lfzytqzy6vbn7pufuohgogife4
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