Next Article in Journal
Outage Probability Performance Prediction for Mobile Cooperative Communication Networks Based on Artificial Neural Network
Next Article in Special Issue
Online Signature Verification Based on a Single Template via Elastic Curve Matching
Previous Article in Journal
SensorTalk: An IoT Device Failure Detection and Calibration Mechanism for Smart Farming
Previous Article in Special Issue
Superpixel-Based Temporally Aligned Representation for Video-Based Person Re-Identification
Open AccessReview

Sensor-Based Technology for Social Information Processing in Autism: A Review

by 1,2,3 and 1,2,3,4,5,*
1
Early Support and Counselling Center Jena, Herbert Feuchte Stiftungsverbund, 07743 Jena, Germany
2
Social Potential in Autism Research Unit, Friedrich Schiller University, 07743 Jena, Germany
3
Department of General Psychology and Cognitive Neuroscience, Friedrich Schiller University Jena, Am Steiger 3/Haus 1, 07743 Jena, Germany
4
Michael Stifel Center Jena for Data-Driven and Simulation Science, Friedrich Schiller University, 07743 Jena, Germany
5
Swiss Center for Affective Science, University of Geneva, 1202 Geneva, Switzerland
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(21), 4787; https://doi.org/10.3390/s19214787
Received: 11 October 2019 / Revised: 29 October 2019 / Accepted: 30 October 2019 / Published: 4 November 2019
(This article belongs to the Special Issue Biometric Systems)
The prevalence of autism spectrum disorders (ASD) has increased strongly over the past decades, and so has the demand for adequate behavioral assessment and support for persons affected by ASD. Here we provide a review on original research that used sensor technology for an objective assessment of social behavior, either with the aim to assist the assessment of autism or with the aim to use this technology for intervention and support of people with autism. Considering rapid technological progress, we focus (1) on studies published within the last 10 years (2009–2019), (2) on contact- and irritation-free sensor technology that does not constrain natural movement and interaction, and (3) on sensory input from the face, the voice, or body movements. We conclude that sensor technology has already demonstrated its great potential for improving both behavioral assessment and interventions in autism spectrum disorders. We also discuss selected examples for recent theoretical questions related to the understanding of psychological changes and potentials in autism. In addition to its applied potential, we argue that sensor technology—when implemented by appropriate interdisciplinary teams—may even contribute to such theoretical issues in understanding autism. View Full-Text
Keywords: automatic recognition; face; voice; body motion; autism spectrum disorder (ASD); assessment; intervention automatic recognition; face; voice; body motion; autism spectrum disorder (ASD); assessment; intervention
MDPI and ACS Style

Kowallik, A.E.; Schweinberger, S.R. Sensor-Based Technology for Social Information Processing in Autism: A Review. Sensors 2019, 19, 4787. https://doi.org/10.3390/s19214787

AMA Style

Kowallik AE, Schweinberger SR. Sensor-Based Technology for Social Information Processing in Autism: A Review. Sensors. 2019; 19(21):4787. https://doi.org/10.3390/s19214787

Chicago/Turabian Style

Kowallik, Andrea E.; Schweinberger, Stefan R. 2019. "Sensor-Based Technology for Social Information Processing in Autism: A Review" Sensors 19, no. 21: 4787. https://doi.org/10.3390/s19214787

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop