Visitar URL original
Skin-Inspired Controllable Microcrack Electronic Skin with High Signal-to-Noise Ratio for High-Fidelity Pulse Wave Monitoring | Advanced Fiber Materials | Springer Nature Link Skip to main content
Springer Nature Link
Log in

Skin-Inspired Controllable Microcrack Electronic Skin with High Signal-to-Noise Ratio for High-Fidelity Pulse Wave Monitoring

  • Research Article
  • Published:
View saved research
Advanced Fiber Materials Aims and scope Submit manuscript

Abstract

Wearable electronic skin (E-skin) with high sensitivity and stable response characteristics holds significant promise for human body monitoring. To address the critical bottleneck of stochastic microcrack morphology and poor structural controllability inherent in conventional MXene-based microcrack sensors, we present a skin-inspired, hierarchically structured E-skin in which ordered regulation of MXene microcracks is achieved through a pre-stretching–spray-coating coupling strategy. Benefiting from the synergistic interplay between structural engineering and conductive pathway modulation, the device achieves a sensitivity of 6.17 kPa–1 over a pressure range of 0–60 kPa, along with a cycling stability exceeding 12000 loading–unloading cycles, a rapid response time of 40 ms, and a high signal-to-noise ratio (SNR) of 30.64 dB. By combining discrete wavelet transform (DWT) and continuous wavelet transform (CWT) for multi-scale analysis of radial and carotid arterial pulse signals, a dominant frequency of approximately 1.3 Hz (78 bpm) was extracted, validating the device’s high-resolution capability for detecting subtle physiological signals. This MXene-based microcrack E-skin offers a novel technical approach for the controllable fabrication of microcracks and demonstrates considerable potential for applications in wearable medical monitoring.

Graphical Abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+
from $39.99 /Month
  • Starting from 10 chapters or articles per month
  • Access and download chapters and articles from more than 300k books and 2,500 journals
  • Cancel anytime
View plans

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Explore related subjects

Discover the latest articles, books and news in related subjects, suggested using machine learning.

Data Availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Yang CW, Wang BZ, Wan J, Kamath A, You FQ, Tian BZ. Quantifying the global eco-footprint of wearable healthcare electronics. Nature. 2026;649:73.

    Article  PubMed  CAS  Google Scholar 

  2. Wang W, Jiang Y, Zhong D, Zhang Z, Choudhury S, Lai JC, Gong H, Niu S, Yan X, Zheng Y, Shih CC, Ning R, Lin Q, Li D, Kim YH, Kim J, Wang YX, Zhao C, Xu C, Ji X, Nishio Y, Lyu H, Tok JBH, Bao Z. Neuromorphic sensorimotor loop embodied by monolithically integrated, low-voltage, soft e-skin. Science. 2023;380:735.

    Article  PubMed  CAS  Google Scholar 

  3. Liu Y, Xu Z, Ji X, Xu X, Chen F, Pan X, Fu Z, Chen Y, Zhang Z, Liu H, Cheng B, Liang J. Ag–thiolate interactions to enable an ultrasensitive and stretchable MXene strain sensor with high temporospatial resolution. Nat Commun. 2024;15:5354.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Liu S, Zhang J, Zhang Y, Zhu R. A wearable motion capture device able to detect dynamic motion of human limbs. Nat Commun. 2020;11:5615.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Tan CX, Dong ZG, Li YH, Zhao HG, Huang XY, Zhou ZC, Jiang JW, Long YZ, Jiang PK, Zhang TY, Sun B. A high performance wearable strain sensor with advanced thermal management for motion monitoring. Nat Commun. 2020;11:3530.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Wei YX, Hao R, Hong XH, Guo S, Lu D, Li H, Zhao WL, Tang ZG, Zhou C, Cao WT, Zheng XH, Hu PP, Yu Z, Niu SC, Han ZW, Ren LQ, Xu WL, Tan SC. Intelligent temperature and pressure sensing decoupling systems in multimodal nanonetwork-based electronic textiles. ACS Nano. 2026;20:16216.

    Article  PubMed  CAS  Google Scholar 

  7. Jiang Y, Ji SB, Sun J, Huang JP, Li YH, Zou GJ, Salim T, Wang CX, Li WL, Jin HR, Xu J, Wang SH, Lei T, Yan XZ, Peh WYX, Yen SC, Liu ZH, Yu M, Zhao H, Lu ZC, Li GL, Gao HJ, Liu ZY, Bao ZA, Chen XD. A universal interface for plug-and-play assembly of stretchable devices. Nature. 2023;614:456.

    Article  PubMed  CAS  Google Scholar 

  8. Wang H, Ding Q, Luo Y, Wu Z, Yu J, Chen H, Zhou Y, Zhang H, Tao K, Chen X, Fu J, Wu J. High-performance hydrogel sensors enabled multimodal and accurate human–machine interaction system for active rehabilitation. Adv Mater. 2023;36:2309868.

    Article  Google Scholar 

  9. Zhao Y, Wu R, Hao Y, Zhao Y, Zhang X, Liu H, Zhai W, Dai K, Pan C, Liu C, Shen C. Eco-friendly multifunctional hydrogel sensors enabled sustainable and accurate human-machine interaction system. Adv Mater. 2025;37:2507127.

    Article  CAS  Google Scholar 

  10. Liu Z, Hu XN, Bo RH, Yang YZ, Cheng X, Pang WB, Liu Q, Wang YJ, Wang SH, Xu SW, Shen ZM, Zhang YH. A three-dimensionally architected electronic skin mimicking human mechanosensation. Science. 2024;384:987.

    Article  PubMed  CAS  Google Scholar 

  11. Zhang S, Yang Y, Sun Y, Liu N, Sun F, Fang B. Artificial skin based on visuo-tactile sensing for 3D shape reconstruction: material, method, and evaluation. Adv Funct Mater. 2024;35:2411686.

    Article  Google Scholar 

  12. Cianchetti M, Laschi C, Menciassi A, Dario P. Biomedical applications of soft robotics. Nat Rev Mater. 2018;3:143.

    Article  Google Scholar 

  13. Laschi C, Mazzolai B, Cianchetti M. Soft robotics: Technologies and systems pushing the boundaries of robot abilities. Sci Robot. 2016;1:3690.

    Article  Google Scholar 

  14. Kim J, Lee JP, Jang Y, Jeong JH, Baek YK, Kim J. Material-level integration of magnetic actuation and triboelectric sensing for adaptive soft robotic platforms. Adv Mater. 2025;38:e72539.

    Article  Google Scholar 

  15. Zhao WL, Trung VD, Li F, Zhang YJ, Li HY, Natsuki J, Tan J, Yang WM, Natsuki T. Hierarchical synergistic engineering for machine learning-assisted gesture recognition and integrated thermal management. Adv Fiber Mater. 2025;7:1495.

    Article  Google Scholar 

  16. Zhao WL, Trung VD, Natsuki J, Tan J, Yang WM, Natsuki T. Arterial pulse dynamics monitoring via ultrasensitive sandwich soft electronics. Adv Fiber Mater. 2025;7:1615.

    Article  Google Scholar 

  17. Zhao WL, Natsuki J, Trung VD, Li HY, Tan J, Yang WM, Natsuki T. AgNPs/CNTs modified nonwoven fabric for PET-based flexible interdigitated electrodes in pressure sensor applications. Chem Eng J. 2024;499:156252.

    Article  CAS  Google Scholar 

  18. Lee S, Lee Y, Park C, Ro YG, Kwak MS, Jeong G, Park J, Lee H, Kim PK, Chung SI, Ko H. Shape-reconfigurable crack-based strain sensor with ultrahigh and tunable sensitivity. Adv Funct Mater. 2025;35:2421812.

    Article  CAS  Google Scholar 

  19. Lee JH, Kim YN, Lee JS, Jeon J, Bae JY, Lee JY, Kim KS, Chae M, Park H, Kim JH, Lee KS, Kim J, Hyun JK, Kang DS, Kang SK. Hypersensitive meta-crack strain sensor for real-time biomedical monitoring. Sci Adv. 2024;10:9258.

    Article  Google Scholar 

  20. Park B, Kim JU, Kim J, Tahk D, Jeong C, Ok J, Shin JH, Kang D, Kim Ti. Strain-visualization with ultrasensitive nanoscale crack-based sensor assembled with hierarchical thermochromic membrane. Adv Funct Mater. 2019;29:1903360.

    Article  Google Scholar 

  21. Peng Y, Wang Z, Wu H, Luo J, Chang X, Wang Y, Zhang S, Feng Z, Jeong U, Wang H. Magnetic crack-based piezoinductive mechanical sensors: way to extreme robustness and ultra-sensitivity. Nat Commun. 2025;16:6370.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Wang X, Huang Y, Wang H, Yin S, Xu C, Wang Z, Chen Y. A rubber-based sensor with over 100 million-level ultra-sensitivity (0–10% strain range) via 3D super-interface. Nat Commun. 2026;17:3547.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Zhou TZ, Yan J, Cao C, He Q, Li WL, Chen L, Wu C, Feng YQ, Lau D, Cheng QF, Wei L. Ultrastrong MXene composite fibers through static-dynamic densification for wireless electronic textiles. Nat Commun. 2025;16:10968.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Zhou T, Yu R, Bai X, Yang Y, Fan Z, Du X, Chen Y, Wang Y, Yang Z, Sun X, Zhu M, Pan S. Tissue-adaptive bioelectronic fibers with temperature-induced self-tightening enable ultrastable neural interface. Nat Commun. 2026;17:4857.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Kang D, Pikhitsa PV, Choi YW, Lee C, Shin SS, Piao LF, Park B, Suh KY, Kim TI, Choi M. Ultrasensitive mechanical crack-based sensor inspired by the spider sensory system. Nature. 2014;516:222.

    Article  PubMed  CAS  Google Scholar 

  26. Park B, Lee S, Choi H, Kim JU, Hong H, Jeong C, Kang D, Kim TI. A semi-permanent and durable nanoscale-crack-based sensor by on-demand healing. Nanoscale. 2018;10:4354.

    Article  PubMed  CAS  Google Scholar 

  27. Pan S, Liu Z, Wang M, Jiang Y, Luo Y, Wan C, Qi D, Wang C, Ge X, Chen X. Mechanocombinatorially screening sensitivity of stretchable strain sensors. Adv Mater. 2019;31:1903130.

    Article  Google Scholar 

  28. Yu RH, Wang CX, Du XH, Bai XW, Tong YZ, Chen HF, Sun XM, Yang J, Matsuhisa N, Peng HS, Zhu MF, Pan SW. In-situ forming ultra-mechanically sensitive materials for high-sensitivity stretchable fiber strain sensors. Natl Sci Rev. 2024;11:nwae158.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Kim SW, Lee J-H, Ko HJ, Lee S, Bae GY, Kim D, Lee G, Lee SG, Cho K. Mechanically robust and linearly sensitive soft piezoresistive pressure sensor for a wearable human–robot interaction system. ACS Nano. 2024;18:3151.

    Article  PubMed  CAS  Google Scholar 

  30. Wu GC, Li X, Bao RR, Pan CF. Innovations in tactile sensing: microstructural designs for superior flexible sensor performance. Adv Funct Mater. 2024;34:2405722.

    Article  CAS  Google Scholar 

  31. Zhao X, Guo H, Ding P, Zhai W, Liu C, Shen C, Dai K. Hollow-porous fiber-shaped strain sensor with multiple wrinkle-crack microstructure for strain visualization and wind monitoring. Nano Energy. 2023;108:108197.

    Article  CAS  Google Scholar 

  32. Dong M, Tomes O, Soul A, Hu Y, Bilotti E, Zhang H, Papageorgiou DG. Hybrid Ti3C2Tx MXene and carbon nanotube reinforced epoxy nanocomposites for self-sensing and structural health monitoring. ACS Appl Nano Mater. 2024;7:3314.

    Article  CAS  Google Scholar 

  33. Gong S, Yap LW, Zhu B, Zhai Q, Liu Y, Lyu Q, Wang K, Yang M, Ling Y, Lai DTH, Marzbanrad F, Cheng W. Local crack-programmed gold nanowire electronic skin tattoos for in-plane multisensor integration. Adv Mater. 2019;31:1903789.

    Article  CAS  Google Scholar 

  34. Pu J-H, Zhao X, Zha X-J, Li W-D, Ke K, Bao R-Y, Liu Z-Y, Yang M-B, Yang W. A strain localization directed crack control strategy for designing MXene-based customizable sensitivity and sensing range strain sensors for full-range human motion monitoring. Nano Energy. 2020;74:104814.

    Article  CAS  Google Scholar 

  35. Wang S, Deng W, Huang H, Yan Z, Wang Y, Zhou T, Ao Y, Wang Z, Zhang J, Tian G, Lan B, Sun Y, Xu T, Yang T, Huang L, Jin L, Lu J, Yang W. Strain-invariant omnidirectional stretchable MXetronics. Nat Commun. 2026;17:2471.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Abraira VE, Ginty DD. The sensory neurons of touch. Neuron. 2013;79:618.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Sun Z, Zheng B, Chen C, Dong Z, Ma P. Synergistically enhancing weavability and interface behavior by applying PDMS/MXene on carbon fiber surface through ultrasound assistance. Compos Part B-Eng. 2023;267:111071.

    Article  CAS  Google Scholar 

  38. Yan Y, Shen C, Huang J, Zhang W, Wang X, Xu S, Lu J, Yang Y. Dynamic molecular isocyanate-modified PDMS/MXene composite coatings: exploring photothermal-responsiveness and mechanical-durability for enhanced self-healing and anti/de-icing. Chem Eng J. 2025;515:163752.

    Article  CAS  Google Scholar 

  39. Duan Y, Xu P, Liu T, Wang Z, Yan X, Yang W, Niu D, Ma P. Design of PDMS/SiO2@MXene composites with “Floatable Interlayer” structure for the electromagnetic shielding behavior improvement. Chem Eng J. 2023;461:141853.

    Article  CAS  Google Scholar 

  40. Halim J, Cook KM, Naguib M, Eklund P, Gogotsi Y, Rosen J, Barsoum MW. X-ray photoelectron spectroscopy of select multi-layered transition metal carbides (MXenes). Appl Surf Sci. 2016;362:406.

    Article  CAS  Google Scholar 

  41. Brette F, Célérier S, Canaff C, Loupias L, Paris M, Habrioux A, Boucher F, Mauchamp V. XPS Binding Energy Shifts in 2D Ti3C2Tz MXene go largely beyond intuitive explanations: rationalization from DFT simulations and experiments. Small Methods. 2024;9:2400848.

    Article  Google Scholar 

  42. Jia ZX, Li ZJ, Ma SF, Zhang WQ, Chen YJ, Luo YF, Jia DM, Zhong BC, Razal JM, Wang XG, Kong LX. Constructing conductive titanium carbide nanosheet (MXene) network on polyurethane/polyacrylonitrile fibre framework for flexible strain sensor. J Colloid Interface Sci. 2021;584:1.

    Article  PubMed  CAS  Google Scholar 

  43. Näslund L-Å, Persson I. XPS spectra curve fittings of Ti3C2Tx based on first principles thinking. Appl Surf Sci. 2022;593:153442.

    Article  Google Scholar 

  44. Mashtalir O, Naguib M, Mochalin VN, Dall’Agnese Y, Heon M, Barsoum MW, Gogotsi Y. Intercalation and delamination of layered carbides and carbonitrides. Nat Commun. 2013;9:2400848.

    Google Scholar 

  45. Chen W, Liu LX, Zhang HB, Yu ZZ. Kirigami-inspired highly stretchable, conductive, and hierarchical Ti3C2Tx MXene films for efficient electromagnetic interference shielding and pressure sensing. ACS Nano. 2021;15:7668.

    Article  PubMed  CAS  Google Scholar 

  46. Liu Q, Zhang Y, Sun X, Liang C, Han Y, Wu X, Wang Z. All textile-based robust pressure sensors for smart garments. Chem Eng J. 2023;4:1716.

    Google Scholar 

  47. Kim K, Jung M, Jeon S, Bae J. Robust and scalable three-dimensional spacer textile pressure sensor for human motion detection. Smart Mater Struct. 2019;28:065019.

    Article  CAS  Google Scholar 

  48. Du Q, Liu L, Tang R, Ai J, Wang Z, Fu Q, Li C, Chen Y, Feng X. High-performance flexible pressure sensor based on controllable hierarchical microstructures by laser scribing for wearable electronics. Adv Mater Technol. 2021;6:2100122.

    Article  CAS  Google Scholar 

  49. Wen D-L, Pang Y-X, Huang P, Wang Y-L, Zhang X-R, Deng H-T, Zhang X-S. Silk fibroin-based wearable all-fiber multifunctional sensor for smart clothing. Adv Funct Mater. 2022;4:873.

    CAS  Google Scholar 

  50. Wei Z, Li X, Cai X, Zhuang X. A water-resistance and breathable fabric-based sensor with high sensitivity for air and underwater applications. Chem Eng J. 2024;487:150034.

    Article  CAS  Google Scholar 

  51. Pang Y, Xu X, Chen S, Fang Y, Shi X, Deng Y, Wang Z-L, Cao C. Skin-inspired textile-based tactile sensors enable multifunctional sensing of wearables and soft robots. Nano Energy. 2022;96:107137.

    Article  CAS  Google Scholar 

  52. Chen Y, Yan X, Zhu Y, Cui M, Kong L, Kuang M, Zhang X, Wang R. A carbon nanotube-based textile pressure sensor with high-temperature resistance. RSC Adv. 2022;12:23091.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Kang Z, Li X, Zhao X, Wang X, Shen J, Wei H, Zhu X. Piezo-resistive flexible pressure sensor by blade-coating graphene-silver nanosheet-polymer nanocomposite. Nanomaterials. 2022;13:4.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Miao Y, Wan L, Ling X, Chen B, Pan L, Gao Y. Mask-free preparation of patterned carbonized carboxymethyl cellulose on fabrics for flexible electronics. ACS Appl Electron Mater. 2020;2:855.

    Article  CAS  Google Scholar 

  55. Westerhof BE, Guelen I, Westerhof N, Karemaker JM, Avolio A. Quantification of wave reflection in the human aorta from pressure alone—a proof of principle. Hypertension. 2006;48:595.

    Article  PubMed  CAS  Google Scholar 

  56. Wang KL, Cheng HM, Sung SH, Chuang SY, Li CH, Spurgeon HA, Ting CT, Najjar SS, Lakatta EG, Yin FCP, Chou P, Chen CH. Wave reflection and arterial stiffness in the prediction of 15-year all-cause and cardiovascular mortalities a community-based study. Hypertension. 2010;55:799.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  57. Tokmakçı M, Erdoğan N. Denoising of arterial and venous Doppler signals using discrete wavelet transform: effect on clinical parameters. Contemp Clin Trials. 2009;30:192.

    Article  PubMed  Google Scholar 

  58. Chotirach M, Tantayanon S, Tungasmita DN, Sun J, Tungasmita S. Synthesis and characterizations of TiN–SBA-15 mesoporous materials for CO2 dry reforming enhancement. Pure Appl Chem. 2020;92:545.

    Article  CAS  Google Scholar 

  59. Lewis RP, Rittogers SE, Froester WF, Boudoulas H. A critical review of the systolic time intervals. Circulation. 1977;56:146.

    Article  PubMed  CAS  Google Scholar 

  60. Berntson GG, Cacioppo JT, Binkley PF, Uchino BN, Quigley KS, Fieldstone A. Autonomic cardiac control. III. Psychological stress and cardiac response in autonomic space as revealed by pharmacological blockades. Psychophysiology. 2007;31:599.

    Article  Google Scholar 

  61. Zhao W, Zheng Y, Qian J, Zhaofa Z, Jin Z, Qiu H, Zhu C, Hong X. AgNWs/MXene derived multifunctional knitted fabric capable of high electrothermal conversion efficiency, large strain and temperature sensing, and EMI shielding. J Alloys Compd. 2022;923:166471.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This research was financially supported by the Fujian Provincial Department of Industry and Information Technology, Project of Key Technology Research and Industrialization for Digital Transformation: Solution and Industrial Implementation of Real-Time Fabric Defect Monitoring in Textile Processes Using Galaxy Large Model-Based AI Technology (No. 03); Commissioned Project by Quanzhou Peak Shoes Co., Ltd. (CN) [2021KH20]; and The Open Competition Mechanism Project of Science and Technology Department of Quanzhou City [2022GZ4]. This work was also supported by the Technology Planning Project of Shaoxing (No. 2024A13003).

Author information

Authors and Affiliations

  1. State Key Laboratory of Bio-Based Fiber Materials, College of Textile Science and Engineering, Zhejiang Sci-Tech University, Hangzhou, 310018, China

    Weili Zhao & Xinghua Hong

  2. Center for Materials Innovation and Technology and College of Engineering and Computer Science, VinUniversity, Hanoi, 100000, Vietnam

    Vuong Dinh Trung

  3. Laboratory of Clothing Materials of Universities in Fujian, College of Textiles and Apparel, Quanzhou Normal University, Quanzhou, 362000, China

    Yinjia Zhang, Lina Cui & Xiangyang Liu

  4. College of Textile, Apparel and Art Design, Shaoxing Institute of Technology, Shaoxing, 312000, China

    Xiuping Su

  5. State Key Laboratory of Marine Environmental Science, Key Laboratory of Underwater Acoustic Communication and Marine Information Technology of the Ministry of Education, College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China

    Xiangyang Liu

Authors
  1. Weili Zhao
    View author publications

    Search author on:PubMed Google Scholar

  2. Vuong Dinh Trung
    View author publications

    Search author on:PubMed Google Scholar

  3. Yinjia Zhang
    View author publications

    Search author on:PubMed Google Scholar

  4. Xiuping Su
    View author publications

    Search author on:PubMed Google Scholar

  5. Xinghua Hong
    View author publications

    Search author on:PubMed Google Scholar

  6. Lina Cui
    View author publications

    Search author on:PubMed Google Scholar

  7. Xiangyang Liu
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Weili Zhao contributed to writing, original draft, conceptualization, investigation, methodology, visualization, and data curation. Vuong Dinh Trung contributed to investigation, methodology, and writing, review and editing. Yinjia Zhang contributed to investigation and methodology. Xinghua Hong performed formal analysis and validation. Xiuping Su contributed to writing, review and editing, supervision, and resources. Lina Cui contributed to supervision, investigation, and resources. Xiangyang Liu was involved in writing, review and editing, supervision, and funding acquisition.

Corresponding authors

Correspondence to Weili Zhao, Xinghua Hong, Lina Cui or Xiangyang Liu.

Ethics declarations

Conflict of Interest

The authors state that there are no conflicts of interest to disclose.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file 1 (AVI 9887 kb)

Supplementary file 2 (AVI 16609 kb)

Supplementary file 3 (DOCX 41889 kb) (download DOCX )

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, W., Trung, V.D., Zhang, Y. et al. Skin-Inspired Controllable Microcrack Electronic Skin with High Signal-to-Noise Ratio for High-Fidelity Pulse Wave Monitoring. Adv. Fiber Mater. (2026). https://doi.org/10.1007/s42765-026-00763-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • DOI: https://doi.org/10.1007/s42765-026-00763-6

Keywords

Profiles

  1. Weili Zhao View author profile
  2. Vuong Dinh Trung View author profile
  3. Xinghua Hong View author profile
  4. Xiangyang Liu View author profile