Hi everyone, I’m an engineering graduate working independently on a self-initiated embedded + data collection project, and I’m looking for thoughtful feedback and discussion from people who’ve walked similar paths.

This is not a college project and not a hobby demo. It’s a long-term, staged system I’m building to deepen my understanding of embedded systems, signal acquisition, and ML-ready datasets.

What I’m doing (Stage-1) I built a simple but reliable embedded setup (ESP32 + optical sensor) to collect:

→ Heart rate (BPM) → SpO₂ levels

The goal at this stage is not diagnosis or prediction, but structured data collection.

I’m intentionally focusing on:

→ Clean signal acquisition → Repeated measurements → Structuring the data properly for future ML use

Why I’m doing it this way

Instead of jumping straight into “AI predicts X”, I’m starting with:

→ Baseline physiological patterns → Population diversity → Long-term data accumulation

I want to collect data across different demographics and lifestyles (children → elderly, sedentary → active, different daily routines, etc.), all anonymized and consent-based.

My belief is that good models come from disciplined data, not shortcuts.

Future direction (not current claims)

In later stages, I plan to:

→ Add richer sensors (ECG/HRV, etc.) → Expand feature space → Explore anomaly detection and risk indicators (not medical diagnosis)

This is a learning and research-oriented build, not a medical product. Why I’m posting here

I deliberately avoid asking “what project should I build” because I want to think independently. What I am looking for is:

→ Feedback on data-first approaches in biomedical/physiological ML → Common mistakes people make at the data collection stage → Advice on scaling datasets responsibly → Experiences from people who started with hardware + data before models

I value failures, slow progress, and foundational work more than flashy demos — and I’m okay with this taking years if it builds real understanding.

What I’m not asking for

→ Ready-made project ideas → “Just use a bigger model” answers → Hype or validation

I’m here to learn from people who care about depth, rigor, and long-term thinking.

Thanks for reading — any grounded insight or critique is welcome.