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.

翻译：本文提出NeckSense，一种用于头部姿态跟踪的新型可穿戴系统，该系统利用多通道生物阻抗传感技术，将柔软、干燥的电极嵌入轻量化的项链式结构中。NeckSense通过捕捉颈部周围组织阻抗的动态变化来感知头部旋转及细微肌肉激活引起的调制信号。为鲁棒地估计头部姿态，我们提出一种深度学习框架，该框架将解剖学先验知识（包括关节约束与自然头部旋转范围）融入损失函数设计。我们在7名参与者身上以当前最先进的姿态估计模型为基准验证了NeckSense系统。采用留一法交叉验证的实验结果表明，该系统在各种头部运动下的平均逐顶点误差为25.9毫米，证明这种紧凑、无需视线追踪的生物阻抗可穿戴设备能够实现与最先进视觉方法相当的头部跟踪性能。