<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Wenbo Zhang</title><link>https://wenbozhangcn.github.io/</link><atom:link href="https://wenbozhangcn.github.io/index.xml" rel="self" type="application/rss+xml"/><description>Wenbo Zhang</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Tue, 06 Oct 2026 00:00:00 +0000</lastBuildDate><image><url>https://wenbozhangcn.github.io/media/sharing.jpg</url><title>Wenbo Zhang</title><link>https://wenbozhangcn.github.io/</link></image><item><title>Beyond Sensor Streams: HALO-Agent as a Body-State Representation Layer for Wearable Agents</title><link>https://wenbozhangcn.github.io/publications/halo-agent/</link><pubDate>Thu, 01 Oct 2026 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/publications/halo-agent/</guid><description>&lt;p&gt;HALO-Agent explores how structured representations of physical and physiological state can bridge continuous wearable sensing and higher-level agent reasoning. The workshop paper positions body-state representations as an interface for context-aware, personalized wearable agents.&lt;/p&gt;</description></item><item><title>WatchForce: Wearables Can Tell How Strong You Grasp From Your Wrist</title><link>https://wenbozhangcn.github.io/publications/watchforce/</link><pubDate>Wed, 01 Jul 2026 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/publications/watchforce/</guid><description>&lt;p&gt;WatchForce explores whether everyday wearable signals from the wrist can reveal grasp force, supporting unobtrusive assessment of hand-object interaction.&lt;/p&gt;</description></item><item><title>MuscleSense: Making Muscle Effort Audible for Eyes-Free In-the-Loop Regulation</title><link>https://wenbozhangcn.github.io/publications/musclesense/</link><pubDate>Mon, 01 Jun 2026 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/publications/musclesense/</guid><description>&lt;p&gt;MuscleSense explores how wearable physiological sensing can turn muscle effort into actionable, eyes-free feedback for movement awareness, training, and rehabilitation. It emphasizes feedback-oriented state inference, mobile deployment, and closed-loop user regulation during lower-limb exercise.&lt;/p&gt;</description></item><item><title>MuscleSense</title><link>https://wenbozhangcn.github.io/projects/musclesense/</link><pubDate>Tue, 12 May 2026 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/projects/musclesense/</guid><description>&lt;p&gt;MuscleSense is a real-time auditory biofeedback system that uses sparse thigh-worn IMU and sEMG to infer feedback-oriented muscle-effort states and support eyes-free regulation during lower-limb exercise.&lt;/p&gt;
&lt;p&gt;The project connects wearable physiological sensing, on-device inference, and closed-loop user feedback, making muscle effort easier to perceive and regulate during training, rehabilitation, and everyday movement.&lt;/p&gt;</description></item><item><title>HALO</title><link>https://wenbozhangcn.github.io/projects/halo/</link><pubDate>Mon, 11 May 2026 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/projects/halo/</guid><description>&lt;p&gt;HALO studies hidden activation-loading organization: how motion, contact pressure, biomechanical loading, and muscle activation interact beneath observable movement.&lt;/p&gt;
&lt;p&gt;The project aims to infer these latent structures from practical sparse wearable signals, making biomechanical organization more accessible outside the lab and easier to connect with feedback-driven mobile health applications.&lt;/p&gt;</description></item><item><title>Wearable Movement Understanding</title><link>https://wenbozhangcn.github.io/projects/wearable-movement-understanding/</link><pubDate>Sun, 10 May 2026 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/projects/wearable-movement-understanding/</guid><description>&lt;p&gt;This project line studies how sparse wearable sensors can move from tracking observable body motion to inferring deeper biomechanical and physiological signals such as plantar pressure, ground reaction force, kinetics, muscle activation, and physical interaction.&lt;/p&gt;
&lt;p&gt;It connects systems including PressInPose, Motion2Press, KineticsSense, MuscleSense, HALO, and WatchForce into a coherent research route for everyday hidden-state understanding, mobile deployment, and closed-loop wearable feedback.&lt;/p&gt;</description></item><item><title>HALO: Inferring Hidden Activation-Loading Organization from Sparse Wearables</title><link>https://wenbozhangcn.github.io/publications/halo/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/publications/halo/</guid><description>&lt;p&gt;HALO studies how practical wearable signals can reveal latent relationships between movement, loading, and muscle activation that are usually hidden outside laboratory measurement setups. It extends the research line from motion and pressure estimation toward interpretable hidden-state organization.&lt;/p&gt;</description></item><item><title>PPGSpeech: A Wearable Silent Speech Interface Leveraging Neck-Worn Photoplethysmography</title><link>https://wenbozhangcn.github.io/publications/ppgspeech/</link><pubDate>Sun, 01 Feb 2026 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/publications/ppgspeech/</guid><description>&lt;p&gt;PPGSpeech investigates how neck-worn PPG signals can support silent speech interaction, extending wearable sensing beyond motion and biomechanics into subtle physiological signals for human-computer interaction.&lt;/p&gt;</description></item><item><title>KineticsSense: A Multimodal Wearable Sensor Framework for Modeling Lower-Limb Motion Kinetics</title><link>https://wenbozhangcn.github.io/publications/kineticssense/</link><pubDate>Wed, 03 Sep 2025 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/publications/kineticssense/</guid><description>&lt;p&gt;KineticsSense extends wearable movement analysis beyond surface kinematics by modeling lower-limb kinetics and muscle activation from sparse wearable signals.&lt;/p&gt;</description></item><item><title>Motion2Press: Cross-Modal Learning from IMU to Plantar Pressure for Gait Analysis</title><link>https://wenbozhangcn.github.io/publications/motion2press/</link><pubDate>Wed, 03 Sep 2025 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/publications/motion2press/</guid><description>&lt;p&gt;Motion2Press connects inertial motion sensing with plantar pressure understanding, supporting portable gait analysis beyond laboratory pressure platforms.&lt;/p&gt;</description></item><item><title>A Full-Body Pose Estimation Method and System Based on Pressure and Inertial Sensors</title><link>https://wenbozhangcn.github.io/publications/pressure-inertial-patent/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/publications/pressure-inertial-patent/</guid><description>&lt;p&gt;This granted patent covers a full-body pose estimation method and system based on pressure and inertial sensors. Inventors are listed as Wenbo Zhang et al.&lt;/p&gt;</description></item><item><title>A Survey on Brain Decoding: Reconstruction of Audio-Visual Perception</title><link>https://wenbozhangcn.github.io/publications/brain-decoding-survey/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/publications/brain-decoding-survey/</guid><description>&lt;p&gt;This survey reviews brain decoding methods for reconstructing audio-visual perception, connecting neural representation learning with multimodal perception.&lt;/p&gt;</description></item><item><title>PressInPose: Integrating Pressure and Inertial Sensors for Full-Body Pose Estimation in Activities</title><link>https://wenbozhangcn.github.io/publications/pressinpose/</link><pubDate>Thu, 21 Nov 2024 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/publications/pressinpose/</guid><description>&lt;p&gt;PressInPose explores how plantar pressure and sparse inertial sensors can support robust full-body pose estimation for sports, rehabilitation, and interactive applications.&lt;/p&gt;</description></item><item><title>Spatial-Temporal Transformer for End-to-End Sign Language Recognition</title><link>https://wenbozhangcn.github.io/publications/sign-language-transformer/</link><pubDate>Tue, 01 Aug 2023 00:00:00 +0000</pubDate><guid>https://wenbozhangcn.github.io/publications/sign-language-transformer/</guid><description>&lt;p&gt;This work studies spatial-temporal transformer modeling for end-to-end sign language recognition.&lt;/p&gt;</description></item></channel></rss>