Google Research· ResearchResearch paper

Unlocking health insights: Estimating advanced walking metrics with smartwatches

Google Research published a blog post introducing a deep learning model for estimating spatio-temporal gait metrics (e.g., walking speed, step length) from smartwatch IMU data. The model uses a temporal convolutional network with multi-head output and was validated on 246 participants with ~70,000 walking segments, showing strong correlation (Pearson r>0.80) and excellent reliability (ICC>0.80) for most metrics compared to a lab-grade system. This is primarily a research paper sharing findings.

From the source

In our work, "Smartwatch-Based Walking Metrics Estimation", we sought to bridge this gap. We demonstrated that consumer smartwatches are a highly viable, accurate, and reliable platform for estimating a comprehensive suite of spatio-temporal gait metrics, with performance comparable to smartphone-based methods.

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