Skin-Friendly Electronics for Acquiring Human Physiological Signatures
Abstract
Epidermal sensing devices offer great potential for real-time health and fitness monitoring via continuous characterization of the skin for vital morphological, physiological, and metabolic parameters. However, peeling them off can be difficult and sometimes painful especially when these skin-mounted devices are applied on sensitive or wounded regions of skin due to their strong adhesion. A set of biocompatible and water-decomposable "skin-friendly" epidermal electronic devices fabricated on flexible, stretchable, and degradable protein-based substrates are reported. Strong adhesion and easy detachment are achieved concurrently through an environmentally benign, plasticized protein platform offering engineered mechanical properties and water-triggered, on-demand decomposition lifetime (transiency). Human experiments show that multidimensional physiological signals can be measured using these innovative epidermal devices consisting of electro- and biochemical sensing modules and analyzed for important physiological signatures using an artificial neural network. The advances provide unique, versatile capabilities and broader applications for user- and environmentally friendly epidermal devices.
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An ANN for these important physiology signatures could make almost individual differences negligible.
“Thus, an ANN for these important physiology signatures could make almost individual differences negligible [237].”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [237]
Multimodal sensing, combining ECG data with other physiological and environmental parameters, such as EOG, EMG, temperature, strain, humidity, and bacterial infection, facilitated a comprehensive health profile.
“Additionally, multimodal sensing, combining ECG data with other physiological and environmental parameters, such as EOG, EMG, temperature, strain, humidity, and bacterial infection, facilitated a comprehensive health profile [8,181,237] (Figure 7c).”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [237]
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References 49 · Cited by 140
- Authors
- Zhang, Y., & Tao, T. H.
- Affiliations
- Chinese Academy of Sciences (CN)
- Corresponding author
- Tao, Tiger H.
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2019-10-17
- Volume
- 31
- Issue
- 49
- Pages
- e1905767-e1905767
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- OpenAlex
- W2981153486
- Cited by
- 140
- References
- 49
- Citations by year
- 2026: 13 · 2025: 18 · 2024: 24 · 2023: 26 · 2022: 22 · 2021: 21 · 2020: 16
- FWCI
- 5.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Advanced Materials (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministry of Science and Technology of the People's Republic of China (2018AAA0103100)
- National Outstanding Youth Science Fund Project of National Natural Science Foundation of China (61822406)
- National Natural Science Foundation of China (61574156)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Advanced Sensor and Energy Harvesting Materials
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Nanomaterials and Printing Technologies
- Keywords
- epidermal electronics, stretchable electronics, flexible electronics, physiological signal detection, electrochemical sensing, biochemical sensing, health monitoring, wearable sensors
- MeSH terms
- Wearable Electronic Devices, Biocompatible Materials, Electronics, Equipment Design, Humans, Skin Physiological Phenomena, Biosensing Techniques, Neural Networks, Computer
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