Classifying Human Activity from Wearable Sensors with 1D CNN + LSTM
This story is from 2026-10-15. It is preserved in the archive; the latest stories are on the live feed.
The problem Activity recognition from wearables sounds solved until you look at raw accelerometer data. A tri-axial accelerometer on a smartwatch produces a violent, noisy signal: high-frequency motion artifacts, orientation shifts every time the wrist rotates, and baseline drift. Telling "walking"…
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- 2026-10-15 12:53 · DEV Community — Machine Learning
Classifying Human Activity from Wearable Sensors with 1D CNN + LSTM