ManoBal
A conceptual agentic-AI framework exploring how LLM questionnaires, behavioural indicators and wearable-data concepts might support child-development assessment.
Overview
Developed during the 5th Annual Nepal AI School (ANAIS), ManoBal proposes an agentic AI framework for supporting assessment of children’s emotional, cognitive and behavioural development.
Design
- LLM-based questionnaires combined with behavioural indicators and wearable-data concepts
- A multimodal pipeline design for synthesising developmental signals
- Human-centred and responsible-AI considerations throughout
This is a conceptual prototype only — it has not been clinically validated or deployed and uses no clinical data.