Summary
Autism Spectrum Disorder (ASD) is a severe permanent neurodevelopmental disorder, affecting 1 in 59 children, worldwide. Researchers have reported a markedly increased prevalence of ASD in preterm populations. Performing early screening of ASD in Neonatal Intensive Care Units (NICUs) would be a unique opportunity to provide a prompt and proper intervention. However, no quantitative solutions are present in the literature. The project “Crib with ARtificial InteLLigence fOr ASD diagnosis in Neonatal intensive care units” (ASD-carillon) aims to design, implement and validate a smart crib for analyzing visual preference and motor patterns in preterm infants in NICUs for early ASD screening. The smart crib integrates a Monitoring Framework, consisting of RGB-D and thermal cameras, and sensors already available in NICUs (e.g., those in the cardiomonitor) for collecting infants data. The smart crib is equipped with an Artificial Intelligence (AI) engine, for processing these data and providing healthcare professionals with quantitative parameters for early ASD screening in NICUs. During the outgoing phase of the fellowship, the ER will benefit from the experience of Prof Zuomin Dong, from University of Victoria (UVic), in the field of sensors and intelligent system, to develop the Monitoring Framework and build the prototype of the smart crib. During the incoming phase, she will collaborate with her main mentor, Prof Emanuele Frontoni from Università Politecnica delle Marche (UNIVPM), to refine the AI Engine. Expert neonatologists as well as neuropsychiatrists from UNIVPM and UVic will be involved as clinical collaborators of ASD-carillon. In the last decades, there has been an increasingly growing number of manuscripts dealing with AI in medicine, but the AI potential in the field of ASD screening in NICUs has not being unlocked, yet. With ASD-carillon, the ER aims to fill this gap, while building the basis for a solid career in the field of AI in neonatology and ASD.
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| Web resources: | https://cordis.europa.eu/project/id/101031553 |
| Start date: | 01-03-2022 |
| End date: | 31-08-2024 |
| Total budget - Public funding: | 214 760,16 Euro - 214 760,00 Euro |
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Original description
Autism Spectrum Disorder (ASD) is a severe permanent neurodevelopmental disorder, affecting 1 in 59 children, worldwide. Researchers have reported a markedly increased prevalence of ASD in preterm populations. Performing early screening of ASD in Neonatal Intensive Care Units (NICUs) would be a unique opportunity to provide a prompt and proper intervention. However, no quantitative solutions are present in the literature. The project “Crib with ARtificial InteLLigence fOr ASD diagnosis in Neonatal intensive care units” (ASD-carillon) aims to design, implement and validate a smart crib for analyzing visual preference and motor patterns in preterm infants in NICUs for early ASD screening. The smart crib integrates a Monitoring Framework, consisting of RGB-D and thermal cameras, and sensors already available in NICUs (e.g., those in the cardiomonitor) for collecting infants data. The smart crib is equipped with an Artificial Intelligence (AI) engine, for processing these data and providing healthcare professionals with quantitative parameters for early ASD screening in NICUs. During the outgoing phase of the fellowship, the ER will benefit from the experience of Prof Zuomin Dong, from University of Victoria (UVic), in the field of sensors and intelligent system, to develop the Monitoring Framework and build the prototype of the smart crib. During the incoming phase, she will collaborate with her main mentor, Prof Emanuele Frontoni from Università Politecnica delle Marche (UNIVPM), to refine the AI Engine. Expert neonatologists as well as neuropsychiatrists from UNIVPM and UVic will be involved as clinical collaborators of ASD-carillon. In the last decades, there has been an increasingly growing number of manuscripts dealing with AI in medicine, but the AI potential in the field of ASD screening in NICUs has not being unlocked, yet. With ASD-carillon, the ER aims to fill this gap, while building the basis for a solid career in the field of AI in neonatology and ASD.Status
TERMINATEDCall topic
MSCA-IF-2020Update Date
28-04-2024
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