Detection and Tracking of Anxiety Related Diseases for Autism Spectrum Disorder Using ECG

This literature review examines the past and recent relevant research on autism disorder. As undergoing many changes in the whole world, especially after the deadly effect of the COVID-19 widespread in the year 2020, has led to drastic adoption of more intelligent devices for quicker detection of certain human diseases and delivering the results quicker via electronic media, the research will focus on the autism disorder intelligent device detection and feed these data to machine learning models to predict the issues without human intervention. Based on the outcome of the results, the diseases can be treated accordingly in an appropriate manner. The individual suffering from autism disorder can be detected early using AI or machine learning, and this domain can be integrated with the IoT sensors. Such sensors can be combined with the human body, and this sensor will extract the data and send it to the centralized healthcare system. Such data will be removed from the data storage and processed using the AI algorithm to get the desirable results to give an appropriate treatment at the correct stages.

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Detection and Tracking of Anxiety Related Diseases for Autism Spectrum Disorder Using ECG

Cited by 3 publications

References 8 publications

A Survey on Affective Computing for Psychological Emotion Recognition

A Survey on Affective Computing for Psychological Emotion Recognition

Detection of Autism Spectrum Disorder using Deep Learning Models

The Influence of Artificial Intelligence on People With Autism Spectrum Disorder

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