Project Overview
An IoT-based clinical walk-test platform for advanced COPD patients, using triangulation to precisely measure walking distance and step count in irregular hospital spaces where straight-line corridors are unavailable.
The Challenge
The walk test is a clinically important measure of mobility for advanced COPD patients — but most hospitals do not have a straight-line corridor of sufficient length to run the test in its standard form. Manual measurement was inaccurate and inconsistent across patients and visits.
Our Approach
We engineered an IoT-based walk-test platform. The patient wears a transmitter; receivers placed in the room triangulate position in real time, capturing both distance and path geometry. Clinicians get accurate step counts, distance, and pace — regardless of the room's shape. The structured longitudinal mobility data is precisely the kind of signal AI-driven respiratory analytics consume.
The Outcome
Clinicians gained a reliable, repeatable mobility assessment in clinical environments where the standard test was previously impossible. Patient progress on COPD therapies became measurable across visits.