From Neck to Head: Bio-Impedance Sensing for Head Pose Estimation
This addresses head tracking for applications like VR/AR with a line-of-sight-free wearable, though it is incremental as it adapts existing sensing to a new form factor.
The paper tackles head pose estimation by introducing NeckSense, a wearable system using bio-impedance sensing, achieving a mean per-vertex error of 25.9 mm, comparable to state-of-the-art vision-based methods.
We present NeckSense, a novel wearable system for head pose tracking that leverages multi-channel bio-impedance sensing with soft, dry electrodes embedded in a lightweight, necklace-style form factor. NeckSense captures dynamic changes in tissue impedance around the neck, which are modulated by head rotations and subtle muscle activations. To robustly estimate head pose, we propose a deep learning framework that integrates anatomical priors, including joint constraints and natural head rotation ranges, into the loss function design. We validate NeckSense on 7 participants using the current SOTA pose estimation model as ground truth. Our system achieves a mean per-vertex error of 25.9 mm across various head movements with a leave-one-person-out cross-validation method, demonstrating that a compact, line-of-sight-free bio-impedance wearable can deliver head-tracking performance comparable to SOTA vision-based methods.