Clinical trial NCT05149144: Comutti - A Research Project Dedicated to Finding Smart Ways of Using Technology for a Better Tomorrow for Everyone, Everywhere.
Official title: Comutti - A Research Project Dedicated to Finding Smart Ways of Using Technology for a Better Tomorrow for Everyone, Everywhere.
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Autism Spectrum Disorder
Keywords: non-verbal autistic children
minimally-verbal autistic children
Lead sponsor: IRCCS Eugenio Medea
Sponsor class: OTHER
Collaborators: name: Politecnico di Milano
name: Massachusetts Institute of Technology
First posted: 2021-12-08
Enrollment: 33
Sex: ALL
Minimum age (years): 2
Maximum age (years): 10
Standard ages: CHILD
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: BASIC_SCIENCE

Brief summary: According to World Health Organization, worldwide one in 160 children has an ASD. About around 25% to 30% of children are unable to use verbal language to communicate (non-verbal ASD) or are minimally verbal, i.e., use fewer than 10 words (mv-ASD). The ability to communicate is a crucial life skill, and difficulties with communication can have a range of negative consequences such as poorer quality of life and behavioural difficulties. Communication interventions generally aim to improve children's ability to communicate either through speech or by supplementing speech with other means (e.g., sign language, pictures, or AAC - Advanced Augmented Communication tools). Individuals with non- verbal ASD or mv-ASD often communicate with people through vocalizations that in some cases have a self-consistent phonetic association to concepts (e.g., "ba" to mean "bathroom") or are onomatopoeic expressions (e.g., "woof" to refer to a dog). In most cases vocalizations sound arbitrary; even if they vary in tone, pitch, and duration depending it is extremely difficult to interpret the intended message or the individual's emotional or physical state they would convey, creating a barrier between the persons with ASD and the rest of the world that originate stress and frustration. Only caregivers who have long term acquaintance with the subjects are able to decode such wordless sounds and assign them to unique meanings.

This project aims at defining algorithms, methods, and technologies to identify the communicative intent of vocal expressions generated by children with mv-ASD, and to create tools that help people who are not familiar with the subjects to understand these individuals during spontaneous conversations.


Eligibility criteria: Inclusion Criteria:

* having a clinical diagnosis of autism spectrum disorder according to DSM-5 criteria
* use fewer than 10 words

Exclusion Criteria:

* using any stimulant or non-stimulant medication affecting the central nervous system
* having an identified genetic disorder
* having vision or hearing problems
* suffering from chronic or acute medical illness

Primary outcomes:
measure: Frequency of audio signal samples and their associated labels
timeFrame: immediately after the intervention
measure: Participant-specific harmonic features derived by the audio signal samples
timeFrame: immediately after the intervention
measure: Accuracy of machine learning prediction
timeFrame: immediately after the intervention
Secondary outcomes:
Other outcomes:
Locations:
city: Bosisio Parini
country: Italy
facility: Scientific Institute, IRCCS Eugenio Medea
state: Lecco
Study officials:
affiliation: IRCCS Eugenio Medea
name: Alessandro Crippa, Ph.D.
role: PRINCIPAL_INVESTIGATOR
References: