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Characterisation of Physiological Responses to Odours in Autism Spectrum Disorders: A Preliminary Study

doi: 10.3390/app13031970
handle: 10773/37310 , 10900/144394
Abnormal sensory perception is among the earliest symptoms of autism spectrum disorders (ASD). Despite mixed findings, olfactory perception seems to be altered in ASD. There is also evidence that automatic responses to odours can serve as biomarkers of ASD. However, this potential use of odour-based biomarkers for ASD is still underexplored. In this study, we aimed to investigate whether physiological responses to social and non-social odours, measured with electrocardiography (ECG) and facial electromyography (EMG), can be used to characterise and predict ASD in adults. For that, we extracted 32 signal features from a previously collected database of 11 adults with ASD and 48 adults with typical development (TD). Firstly, non-parametric tests were performed, showing significant differences between the ASD and the TD groups in 10 features. Secondly, a k-nearest-neighbour classifier with a leave-one-out strategy was employed, obtaining an F1-score of 67%. Although caution is needed due to the small sample size, this study provides preliminary evidence supporting the use of physiological responses to social and non-social odours as a potential diagnostic tool for ASD in adults.
- "UNIVERSIDADE DE AVEIRO Portugal
- University of Tübingen Germany
- Universidade de Aveiro
- Universidade de Aveiro Portugal
- University of Aveiro (UAVR) Portugal
Technology, QH301-705.5, autism spectrum disorders, QC1-999, 530, Machine learning, Biology (General), QD1-999, facial EMG, ECG, T, Physics, 600, Autism spectrum disorders, 540, Engineering (General). Civil engineering (General), Olfaction, Chemistry, machine learning, odours, TA1-2040, Facial EMG, Odours, olfaction
Technology, QH301-705.5, autism spectrum disorders, QC1-999, 530, Machine learning, Biology (General), QD1-999, facial EMG, ECG, T, Physics, 600, Autism spectrum disorders, 540, Engineering (General). Civil engineering (General), Olfaction, Chemistry, machine learning, odours, TA1-2040, Facial EMG, Odours, olfaction
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