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KiD A low cost KInematic Detector to assist early diagnosis and objective profi...

KiD A low cost KInematic Detector to assist early diagnosis and objective profiling of ASD Autism spectrum disorders (ASDs) are a heterogeneous set of neurodevelopmental disorders characterized by deficits in social communication and reciprocal interactions, as well as stereotypic behaviours. Although early diagnosis f... see more

31/12/2019

IIT

148K€

Project Budget: 148K€

Project leader

FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

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Financing granted El organismo H2020 notifico la concesión del proyecto The day 2019-12-31

ERC-2017-PoC: ERC-Proof of Concept Scope:Scope:

I+D

Cerrada does 8 years

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characteristics of the participant

Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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2 Participantes

IIT

148.41K€ | Leader

GENMEDICA

300.00K€ | participant

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Project duration: 19 months Date Start: 2018-05-25
End date: 2019-12-31

Project leader

FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Project Budget 148K€

participation deadline Sin fecha límite de participación.

Project description Autism spectrum disorders (ASDs) are a heterogeneous set of neurodevelopmental disorders characterized by deficits in social communication and reciprocal interactions, as well as stereotypic behaviours. Although early diagnosis followed by appropriate intervention appears to offer the best chance for significant health improvement and economic gain, diagnosis of autism remains complex and often difficult to obtain. Recent identification of atypical kinematic patterns in children and infants at increased risk for ASDs provides new insights into autism diagnostic and objective profiling. KiD intends to help move these insights into the development of a low cost, easy-to-use, yet reliable wearable tracking system, designed to assist detection and classification of ASDs. The novelty of KiD is to combine informed development of machine learning methods to classify kinematic data with a co-design human factor engineering. KiD holds great potential for translational possibilities into autism clinical practice. The main use of the device will be to assist clinicians to achieve expedited diagnosis, ensuring early and timely access of children at risk of autism to evidence-based intervention programs. Another use will be to examine the quantitative nature of autistic traits, enabling new forms of precision-phenotyping, which is potentially useful for stratifying patients with ASD and developing individualized treatment approaches.

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