ReviewAdvanced healthcare materials2026
Flexible and Self-Powered Wearable Sensors for Tremor Monitoring in Parkinson'S Disease: Recent Advances in Materials and Device Architectures.
Review in Advanced healthcare materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
7 authors.
Funding
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disorder where tremor remains one of the most prominent and disabling motor symptoms. Traditional clinical rating scales for disease severity rely on clinician observation and patient self-report, often failing to capture the dynamic and continuous nature of tremors in daily life. This drives the development of objective monitoring technologies, such as wearable sensors, for more accurate evaluation of PD severity. However, many existing systems use rigid materials that lack the mechanical compliance and skin conformability required for stable biointegration. This review summarizes advances in flexible wearable sensors for PD tremor assessment from material innovations to a device engineering perspective, covering inertial measurement units (IMUs), electromyography (EMG), and emerging self-powered systems such as triboelectric (TENG) and piezoelectric nanogenerators (PENG). This review highlightshow functional materials, microstructural design, and device architectures govern sensing mechanisms and performance, with particular emphasis on the transition from rigid components to soft, skin-interfaced technologies. Recent patent activity reflects a shift toward multimodal, wireless, and clinically integrated platforms. Despite progress, challenges remain, including motion artifacts, durability, and limited large-scale clinical validation. Integration of flexible materials, self-powered designs, and AI-driven analytics enables continuous, personalized monitoring, moving closer to real-world clinical deployment and improved patient care.
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Registered trials
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