L2M – Artificial intelligence based system to improve quality of life of sound sensitive individual on the autism spectrum

Individuals with autism spectrum disorder (ASD) often experience sound sensitivity, leading to distress, anxiety, and difficulties in daily life. The challenges for youth experiencing sound sensitivity can be both acute and downstream. This ongoing stress leads to avoidance behaviours, reduced social and community engagement, and distractions that impact performance at school or work and engagement at home.
Approaches for accommodating children with sound sensitivity include avoiding noisy settings or allowing them to leave to take breaks in a quiet area. Many children make use of wearable devices to block sound, like earplugs, earmuffs or noise cancelling headphones. As such strategies block or avoid all sounds indiscriminately, they interfere with the child’s full participation in family, community, and school. Our project aims to develop a mobile application to help autistic youth cope with DST. The goal is to increase youth’s comfort level and their engagement in the community. Using AI, the software intelligently detects environmental sounds that the youth find distressing, and then manages these sounds for them through headphones with different options available to the user. This is a unique, innovative, and individualized solution for increasing comfort in the presence of distressing sounds.

Faculty Supervisor:

Elina Birmingham;Siamak Arzanpour

Student:

Partner:

I-INC Foundation for Business Development

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program: