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Pre-Clinical ASD Screening Using Multi-Biometrics-Based Systems
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Author(s): Tanu Wadhera (Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, India), Deepti Kakkar (Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, India), Gurjot Kaur (Dr. B. R. Ambedkar National Institute of Technology Jalandhar, India)and Vasudha Menia (Dr. B. R. Ambedkar National Institute of Technology Jalandhar, India)
Copyright: 2019
Pages: 27
Source title:
Design and Implementation of Healthcare Biometric Systems
Source Author(s)/Editor(s): Dakshina Ranjan Kisku (National Institute of Technology Durgapur, India), Phalguni Gupta (National Institute of Technical Teachers Training and Research, India)and Jamuna Kanta Sing (Jadavpur University, India)
DOI: 10.4018/978-1-5225-7525-2.ch008
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Abstract
Autism Spectrum Disorder (ASD) screening is still an ongoing process due to few objective and effective screening approaches. The consideration of facial patterns, fingerprints, and other metrics such as footprints and ear size can well explain the ASD phenotypes. These physical anomalies provide a simpler and more objective approach to screen the disorder through rather than considering the complex biological factors. Moreover, it is very easy to acquire these metrics as compared to those lengthier and restrictive procedures. The screening engine in which both the biometrics are integrated has better and reliable outcomes as compared to singular approaches. The objective of this chapter is to present an ASD screening system based on the combination of biometrics of face and fingers. The novelty of the chapter is that the classifier-based matching and fusion of the modalities has been proposed. Hence, multi-biometric-based pre-clinical system has the potential to follow ASD-affected individuals continuously, objectively, and periodically.
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