Xuanyou Liu (Zed)

Inertial odometry (IO) using only Inertial Measurement Units (IMUs) offers a lightweight solution for human motion tracking in augmented reality and wearable devices. While recent learning-based IO methods have improved generalizability through large-scale pretraining, they remain prone to drift due to missing spatio-temporal human motion dynamics. We propose grounding inertial odometry in human kinematics through a learned pose prior inferred from IMU data, promoting physically consistent motion constraints during state propagation. Integrating this prior into existing IO architectures reduces positional drift by up to 36% on the challenging Nymeria dataset (5x larger than prior works). We further develop a sensor-fusion framework incorporating auxiliary signals from lightweight sensors already available on commercial AR glasses, including a magnetometer, barometer, and secondary IMU. With this fusion strategy, drift is reduced by up to 42%, improving robustness across diverse motion conditions. Together, our results establish a new paradigm for lightweight, camera-free human tracking that unifies human motion kinematics with multimodal sensing.

Sensory substitution devices enable users to perceive visual information through other modalities, such as touch. However, most existing devices place the camera at the user's eyes (head-mounted), which limits the ability to coordinate manual interactions. We propose "seeing and feeling" from the hand's perspective to enhance the flexibility and expressivity of sensory substitution. To this end, we engineered a back-of-the-hand electrotactile display that renders tactile images from a wrist-mounted camera, allowing users to feel objects while reaching and hovering. In a user study with sighted and blind or low-vision participants, we compared our hand-centered perspective against traditional head-mounted views in manipulation tasks (e.g., handling bottles, soldering). Results indicate that while both perspectives yield comparable performance, participants preferred the flexibility of the hand's perspective, which supported more ergonomic object manipulation strategies.

Electrotactile stimulation offers a promising path for high-resolution wearable haptics but has traditionally struggled with integration into soft, everyday textiles. We present TacTex, a textile interface that seamlessly integrates high-density haptic feedback and touch sensing. By employing a novel multi-layer woven structure that separates conductive electrodes with non-conductive yarns, TacTex achieves a sensing and actuation resolution of 512 × 512 with electrode spacing as small as 2mm. The system includes a custom driving board that enables precise spatial and temporal control of electrical stimuli while simultaneously monitoring voltage changes for touch tracking. Our technical evaluation and user studies demonstrate that TacTex can render a wide range of haptic effects, including complex static and dynamic patterns, effectively bringing high-fidelity haptic feedback to everyday clothing.