← 研踪 PaperTrailarXiv:2611.07087 · v1
WAVES: Wearable Active Vibroacoustic Elasticity Sensing for Low-Cost and Non-Invasive Muscle Stiffness Monitoring
首次提交 2026-11-05 03:50
版本更新 2026-11-05 03:50
雷达观测 2026-11-06 10:04
摘要
Muscle stiffness is a physiologically meaningful biomarker associated with a wide range of musculoskeletal and neurological conditions. However, existing muscle stiffness assessment methods, such as shear wave elastography (SWE), manual palpation, and handheld mechanical probes, remain impractical for continuous, everyday monitoring due to bulky hardware, operator dependence, and limited self-use. Meanwhile, wearable muscle-sensing modalities such as Electromyography (EMG) and Mechanomyography (MMG) primarily capture muscle activation rather than passive mechanical properties of tissue at rest, leaving a critical gap in portable monitoring of resting muscle stiffness. In this work, we present WAVES, a wearable system for continuous monitoring of muscle stiffness via active vibroacoustic sensing. WAVES injects controlled vibroacoustic excitation into soft tissue and estimates muscle stiffness by measuring shear-wave propagation velocity through Time-Difference-of-Arrival (TDoA) analysis across spatially distributed wearable sensors. To achieve accurate TDoA estimation with low-cost wearable hardware, we develop a physiology- and quality-guided vibroacoustic sensing framework that effectively screens and refines TDoA for accurate stiffness estimation. We evaluate WAVES through characterization experiments using ballistic jelly and end-to-end on-body evaluation with human participants. Results demonstrate that WAVES can robustly estimate muscle stiffness across multiple users and different superficial muscles while enabling lightweight, wearable deployment for everyday use. WAVES is able to achieve a muscle stiffness estimation error of 13.1% or less across multiple users and multiple muscle groups.
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v1 · 2026-11-05 03:50 · 最新观测版本
WAVES: Wearable Active Vibroacoustic Elasticity Sensing for Low-Cost and Non-Invasive Muscle Stiffness Monitoring
Muscle stiffness is a physiologically meaningful biomarker associated with a wide range of musculoskeletal and neurological conditions. However, existing muscle stiffness assessment methods, such as shear wave elastography (SWE), manual palpation, and handheld mechanical probes, remain impractical for continuous, everyday monitoring due to bulky hardware, operator dependence, and limited self-use. Meanwhile, wearable muscle-sensing modalities such as Electromyography (EMG) and Mechanomyography (MMG) primarily capture muscle activation rather than passive mechanical properties of tissue at rest, leaving a critical gap in portable monitoring of resting muscle stiffness. In this work, we present WAVES, a wearable system for continuous monitoring of muscle stiffness via active vibroacoustic sensing. WAVES injects controlled vibroacoustic excitation into soft tissue and estimates muscle stiffness by measuring shear-wave propagation velocity through Time-Difference-of-Arrival (TDoA) analysis across spatially distributed wearable sensors. To achieve accurate TDoA estimation with low-cost wearable hardware, we develop a physiology- and quality-guided vibroacoustic sensing framework that effectively screens and refines TDoA for accurate stiffness estimation. We evaluate WAVES through characterization experiments using ballistic jelly and end-to-end on-body evaluation with human participants. Results demonstrate that WAVES can robustly estimate muscle stiffness across multiple users and different superficial muscles while enabling lightweight, wearable deployment for everyday use. WAVES is able to achieve a muscle stiffness estimation error of 13.1% or less across multiple users and multiple muscle groups.
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