Turning sensor data into
evidence you can act on.
I help teams turn wearable sensor data into evidence they can act on — whether that's a validation claim, a clinical endpoint, or a product decision. My background spans clinical practice, study design, multi-sensor data collection, and building the analysis tools to make it all reproducible. I've worked across IMU, EMG, PPG, and accelerometry systems, from single-patient assessments to 10,000-participant cohorts.
Multi-Sensor Measurement Systems
IMU, EMG, PPG/ECG, and accelerometry — from single-device setups to synchronized multi-sensor protocols. Practical experience with placement, synchronization, artifacts, drift, and emerging form factors including earables and smart glasses.
Evidence Generation & Study Design
End-to-end study execution: protocols, endpoints, feasibility, adherence, and data-quality checks. Experience across observational studies, RCTs, and longitudinal designs, translating questions into testable, defensible outcomes.
Human Movement & Clinical Domain
Five years of clinical physiotherapy plus a PhD in biomedical engineering. Deep knowledge of gait, functional movement, neuromuscular physiology, and what sensor signals can (and cannot) tell you about real humans.
Real-World Data & Population Analytics
Working with large wearable datasets (10,000+ participants) to derive interpretable activity-pattern metrics — bouts, fragmentation, transitions, intensity distribution — and relate them to health outcomes.
Validation & Regulatory-Ready Measurement
Gold-standard comparisons, reliability testing, synchronization, artifact handling, and transparent error reporting. Building the evidence base so performance claims are defensible for product and regulatory decisions.
Clinical-Technical Translation
Bridging clinical needs and technical implementation. Previously embedded in a product team as clinical consultant, translating end-user requirements into engineering specifications. Comfortable in both languages.