The problem VitalSense AI solves

In emergency and high-pressure medical environments, the first few minutes decide survival. However, initial patient assessment (triage) is still largely manual, subjective, and time-consuming, creating critical delays and errors.

Key Challenges Today:

1. Overloaded medical staff
2. Delayed or inconsistent triage decisions
3. Unstructured patient communication
4. Lack of automated documentation
5. Patient feel uncomfortable sharing intimate health details.

**How It Makes Existing Tasks Easier & Safer:
**

1. Reduces time spent on initial assessment
2. Reduced Cognitive Load for Nurses
3. Safer Decision-Making
4. Works in places like rural clinics, disaster prone areas, mass casuality sites,etc.
5. Doctors receive clear, structured insights instead of raw data.

This system replaces chaotic, manual first-contact triage with a calm, consistent AI assistant that listens, observes, and summarizes patient conditions in real time helping clinicians act faster and safer.

Challenges we ran into

Patients may lie or exaggerate

Our Fix:
We don’t rely on words alone
We cross-validate using Voice stress
Emotional inconsistency sentiment trends over time

Emotion detection can be inaccurate

 Our Fix:

We use temporal emotion tracking
Emotions are averaged across the entire conversation
Sudden spikes are flagged separately

LLM hallucination

  Our Fix:

This issue is addressed using a RAG-based architecture, where the LLM generates responses strictly grounded in verified medical guidelines and predefined safety constraints, minimizing hallucinations and preventing unauthorized medical advice