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RESEARCH PAPER / 2025-10-15

Highly Adaptive Conductive Polymer Electronics Enhance Neural Data and Learning Accuracy

Mottini, V., Xing, L., Meilinger, C., Inamdar, S., Chen, X. C., Wang, J., Xing, Y., Darbonne, J., Tang, Z., Zhang, Y., Contag, C. H., Zhang, M., Li, J.

Michigan State UniversityMichigan State University · biorxiv

Abstract

Human skin, the body\'s largest organ, plays a vital role in sensing and transmitting neuronal, mechanical, and biochemical signals, making it an essential non invasive interface for health monitoring, rehabilitation, and human machine interaction. However, aging related changes, including thinning, increased wrinkling, dryness, and altered collagen structure, significantly impact electrical impedance, conductance, and contact stability, challenging the fidelity and consistency of bioelectronic signal acquisition. Here, we address this gap by developing AdapSkin, an age adaptive, skin mimicking, bio adhesive, and stretchable polymeric electronic skin interface that seamlessly conforms to diverse skin properties, enabling high fidelity and high density electrophysiological recording. The soft electrodes of AdapSkin are composed of an aqueously processed, homogeneously mixed organic nanocomposite with a conductive polymer percolation network, forming a gel like interface that reduces modulus and enhances skin electrode contact. The materials platform achieves extraordinary softness and electrical stretchability of up to 1200% through a double network composite structure. AdapSkin significantly minimizes age induced variations in interfacial impedance and signal to noise ratio (SNR), improving signal consistency for neuromuscular assessment, prosthetic control, and rehabilitation applications. Scalable fabrication enables the creation of large area electrode arrays, which reduces motion artifacts, improves sEMG mapping reliability, and ensures long-term signal stability across various age groups. Machine learning analysis further demonstrates AdapSkin\'s superior accuracy in gesture classification for elderly users, highlighting its potential to enhance prosthetic control, assistive robotics, and rehabilitation for individuals with sarcopenia and neuromuscular decline. By improving signal quality and adaptability in aging populations, AdapSkin advances fair bioelectronic interfaces, fostering more equitable and effective healthcare technologies for age related conditions.

The following analysis is generated by AI and may contain errors. It is separate from the authors’ abstract and is not peer review.

Research summary

The paper claims that the AdapSkin interface improves signal consistency for neuromuscular assessment in aging populations. The research addresses the challenges posed by age-related changes in skin properties, which is directly relevant to enhancing healthcare technologies for age-related conditions.

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