ChatPPG

IMUDINO

self-distilled foundation model for inertial sensing

IMUGYRO
PaperOpenReview

Key facts

Pretraining Data
Not disclosed in abstract (multi-source IMU incl. HAR, health, motion-capture, robot odometry)
Venue
ICLR 2027 submission (under review)

Summary

DINO-style SSL adapted to inertial data via semantics-preserving motion transformations (simulated motion-pattern and sensor-setup variation); plain transformer with frequency-aware positional encoding supporting variable input length and sampling rate. Claims competitive results across HAR, health, motion capture and robot odometry (incl. cross-embodiment).