Silk Fabric Functionalized by Nanosilver Enabling the Wearable Sensing for Biomechanics and Biomolecules

Integrating biomechanical and biomolecular sensing mechanisms into wearable devices is a formidable challenge and key to acquiring personalized health management. To address this, we have developed an innovative multifunctional sensor enabled by plasma functionalized silk fabric, which possesses multimodal sensing capabilities for biomechanics and biomolecules. A seed-mediated <i>in situ</i> growth method was employed to coat silver nanoparticles (AgNPs) onto silk fibers, resulting in silk fibers functionalized with AgNPs (SFs@Ag) that exhibit both piezoresistive response and localized surface plasmon resonance effects. The SFs@Ag membrane enables accurate detection of mechanical pressure and specific biomolecules during wearable sensing, offering a versatile solution for comprehensive personalized health monitoring. Additionally, a machine learning algorithm has been established to specifically recognize muscle strain signals, potentially extending to the diagnosis and monitoring of neuromuscular disorders such as amyotrophic lateral sclerosis (ALS). Unlike electromyography, which detects large muscles in clinical medicine, sensing data for tiny muscles enhance our understanding of muscle coordination using the SFs@Ag sensor. This detection model provides feasibility for the early detection and prevention of neuromuscular diseases. Beyond muscle stress and strain sensing, biomolecular detection is a critical addition to achieving effective health management. In this study, we developed highly sensitive surface-enhanced Raman scattering (SERS) detection for wearable health monitoring. Finite-difference time-domain numerical simulations ware utilized to analyze the efficacy of the SFs@Ag sensor for wearable SERS sensing of biomolecules. Based on the specific SERS spectra, automatic extraction of signals of sweat molecules was also achieved. In summary, the SFs@Ag sensor bridges the gap between biomechanical and biomolecular sensing in wearable applications, providing significant value for personalized health management.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2024-09-13
DOI
https://doi.org/10.1021/acsami.4c10253
Citations
18
Primary Topic
Silk-based biomaterials and applications
Type
article
Field-Weighted Citation Impact
3.12

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Silk Fabric Functionalized by Nanosilver Enabling the Wearable Sensing for Biomechanics and Biomolecules

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18 citations
ACS Applied Materials & Interfaces
Silk-based biomaterials and applications
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article

Silk Fabric Functionalized by Nanosilver Enabling the Wearable Sensing for Biomechanics and Biomolecules

Dongzhen Chen, Zhichao Zhu, Jian Feng Huang, Wei Fan, Ming Luo, Dan He, Meng Zhang, Dan Yu, Qiuhui Sheng, Canglong Xing
article en
18 citations

Abstract

Integrating biomechanical and biomolecular sensing mechanisms into wearable devices is a formidable challenge and key to acquiring personalized health management. To address this, we have developed an innovative multifunctional sensor enabled by plasma functionalized silk fabric, which possesses multimodal sensing capabilities for biomechanics and biomolecules. A seed-mediated <i>in situ</i> growth method was employed to coat silver nanoparticles (AgNPs) onto silk fibers, resulting in silk fibers functionalized with AgNPs (SFs@Ag) that exhibit both piezoresistive response and localized surface plasmon resonance effects. The SFs@Ag membrane enables accurate detection of mechanical pressure and specific biomolecules during wearable sensing, offering a versatile solution for comprehensive personalized health monitoring. Additionally, a machine learning algorithm has been established to specifically recognize muscle strain signals, potentially extending to the diagnosis and monitoring of neuromuscular disorders such as amyotrophic lateral sclerosis (ALS). Unlike electromyography, which detects large muscles in clinical medicine, sensing data for tiny muscles enhance our understanding of muscle coordination using the SFs@Ag sensor. This detection model provides feasibility for the early detection and prevention of neuromuscular diseases. Beyond muscle stress and strain sensing, biomolecular detection is a critical addition to achieving effective health management. In this study, we developed highly sensitive surface-enhanced Raman scattering (SERS) detection for wearable health monitoring. Finite-difference time-domain numerical simulations ware utilized to analyze the efficacy of the SFs@Ag sensor for wearable SERS sensing of biomolecules. Based on the specific SERS spectra, automatic extraction of signals of sweat molecules was also achieved. In summary, the SFs@Ag sensor bridges the gap between biomechanical and biomolecular sensing in wearable applications, providing significant value for personalized health management.

ACS Applied Materials & InterfacesVol. 16(38)
Xi'an Shiyou University (CN), Xi'an Polytechnic University (CN), First Affiliated Hospital of Xi'an Jiaotong University (CN), Institute of New Materials (CN), Xi'an Jiaotong University (CN)
Education Department of Shaanxi Province
Openalex Percentile: Top 8%
Silk-based biomaterials and applications
3.12
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