Objective
- To examine which parameters or combinations of parameters can differentiate different types of ADHD accurately
Project Description
Worldwide, the prevalence rate of ADHD children is 7.1%, and in India, it is around 12%. Diagnosis of ADHD in children aged <7 years presents significant challenges to clinicians because many behavioural manifestations of ADHD may be normative at such a young age (7-10). Therefore, accurate diagnosis of ADHD children is crucial.
ADHD children often have symptoms that overlap highly with other neurodevelopmental disorders. This may lead to an increase in their misdiagnosis which, in turn, can lead to life-impacting issues. A combination of some cognitive motivational functions and a computer-based classification system can classify ADHD-combined type with healthy controls as well as children with other neurodevelopmental disorders (e.g., ODD) with an accuracy of ~98%. The present proposal aims to test this.
Project Details
Principal Investigator: Prof. Rashmi Gupta
Cause Area/Theme: Empowering communities-Supporting
differently-abled
Budget: INR 30 Lakhs
Technology Readiness Level: 6
Project Duration: 2 Years
UN SDG No: 10
Expected Impact
This project will eliminate the problem of misdiagnosis of children suffering from ADHD significantly by implementing an affordable and scalable technology solution that can help clinicians diagnose these children accurately.