# From Neck to Head: Bio-Impedance Sensing for Head Pose Estimation

arXiv: https://arxiv.org/abs/2507.12884 · HTML: https://mlsanity.com/paper/2507.12884/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 43 references that are in the map.
- First posted on arXiv 17 Jul 2025.

## Builds on (most cited first, 9 of 9)

- [One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer](https://mlsanity.com/paper/2303.16160/) (2023)
- [IMUPoser: Full-Body Pose Estimation using IMUs in Phones, Watches, and Earbuds](https://mlsanity.com/paper/2304.12518/) (2023)
- [3D Human Pose Estimation in RGBD Images for Robotic Task Learning](https://mlsanity.com/paper/1803.02622/) (2018)
- [MobilePoser: Real-Time Full-Body Pose Estimation and 3D Human Translation from IMUs in Mobile Consumer Devices](https://mlsanity.com/paper/2504.12492/) (2025)
- [iMove: Exploring Bio-impedance Sensing for Fitness Activity Recognition](https://mlsanity.com/paper/2402.09445/) (2024)
- [Origami Single-end Capacitive Sensing for Continuous Shape Estimation of Morphing Structures](https://mlsanity.com/paper/2307.05370/) (2023)
- [iFace: Hand-Over-Face Gesture Recognition Leveraging Impedance Sensing](https://mlsanity.com/paper/2403.18433/) (2024)
- [UbiHR: Resource-efficient Long-range Heart Rate Sensing on Ubiquitous Devices](https://mlsanity.com/paper/2410.19279/) (2024)
- [iBreath: Usage Of Breathing Gestures as Means of Interactions](https://mlsanity.com/paper/2507.04162/) (2025)

## Abstract (arXiv)

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.