Symptom Tracker in Implant Contol App

Chronic pain and implant management require nuanced decision‑making, yet patients with implanted spinal cord stimulators often struggle to recall symptom patterns and optimal device settings between clinical visits. This gap limits patient empowerment and constrains clinicians’ ability to tailor therapy based on real‑world symptom feedback.

As Design Lead, I drove the strategy and experience design for an AI‑enabled symptom tracking system integrated with implant data. Working with cross‑functional partners including UI and interaction designers, I led discovery, defined key hypotheses, and facilitated a design sprint to prototype a solution blending self‑reported symptoms, passive health signals, and contextual environmental data.

The core challenge was to translate disparate data streams — from user‑entered symptom logs to biometric and environmental indicators — into meaningful pattern recognition that enhances clinical insights without overwhelming patients or providers. By emphasizing clarity, relevance, and predictive pattern cues, the experience aimed to increase patient adherence and enable better clinical decisions.

While full details and metrics remain confidential, this overview highlights the strategic framing, design trade‑offs, and systems thinking at the heart of delivering a responsible, data‑forward health experience under real clinical constraints.