Issue

Vol. 15 (2023)

Machine Learning-Enhanced Flexible Mechanical Sensing

https://doi.org/10.1007/s40820-023-01013-9
Yuejiao Wang
Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, People’s Republic of China
Mukhtar Lawan Adam
Materials Interfaces Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People’s Republic of China
Yunlong Zhao
Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361102, People’s Republic of China
Weihao Zheng
School of Mechano‑Electronic Engineering, Xidian University, Xi’an 710071, People’s Republic of China
Libo Gao
Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361102, People’s Republic of China
Zongyou Yin
Research School of Chemistry, Australian National University, Canberra, ACT 2601, Australia
Haitao Zhao
Materials Interfaces Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People’s Republic of China

Corresponding Author: Zongyou Yin

zongyou.yin@anu.edu.au

Nano-Micro Letters, Vol. 15 (2023), Article Number: 55

Abstract

To realize a hyperconnected smart society with high productivity, advances in flexible sensing technology are highly needed. Nowadays, flexible sensing technology has witnessed improvements in both the hardware performances of sensor devices and the data processing capabilities of the device’s software. Significant research efforts have been devoted to improving materials, sensing mechanism, and configurations of flexible sensing systems in a quest to fulfill the requirements of future technology. Meanwhile, advanced data analysis methods are being developed to extract useful information from increasingly complicated data collected by a single sensor or network of sensors. Machine learning (ML) as an important branch of artificial intelligence can efficiently handle such complex data, which can be multi-dimensional and multi-faceted, thus providing a powerful tool for easy interpretation of sensing data. In this review, the fundamental working mechanisms and common types of flexible mechanical sensors are firstly presented. Then how ML-assisted data interpretation improves the applications of flexible mechanical sensors and other closely-related sensors in various areas is elaborated, which includes health monitoring, human–machine interfaces, object/surface recognition, pressure prediction, and human posture/motion identification. Finally, the advantages, challenges, and future perspectives associated with the fusion of flexible mechanical sensing technology and ML algorithms are discussed. These will give significant insights to enable the advancement of next-generation artificial flexible mechanical sensing.


Highlights:


1 The latest progress on the integration of flexible mechanical sensing platforms with machine learning (ML) is reviewed.
2 The advantages, challenges, and future perspectives of the application of ML to intelligent flexible mechanical sensing technology are discussed.
3 The fundamental working mechanisms and common types of flexible mechanical sensors are reviewed.

Keywords

Flexible mechanical sensors Machine learning Artificial intelligence Data processing
Wang, Yuejiao, Mukhtar Lawan Adam, Yunlong Zhao, Weihao Zheng, Libo Gao, Zongyou Yin, and Haitao Zhao. 2023. “Machine Learning-Enhanced Flexible Mechanical Sensing”. Nano-Micro Letters 15 (February):55. https://doi.org/10.1007/s40820-023-01013-9.
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References
  1. Z.X. Zhang, Q.F. Shi, T.Y.Y. He, X.G. Guo, B.W. Dong et al., Artificial intelligence of toilet (ai-toilet) for an integrated health monitoring system (ihms) using smart triboelectric pressure sensors and image sensor. Nano Energy 90, 106517 (2021). https://doi.org/10.1016/j.nanoen.2021.106517
  2. Z.D. Sun, M.L. Zhu, Z.X. Zhang, Z.C. Chen, Q.F. Shi et al., Artificial intelligence of things (aiot) enabled virtual shop applications using self-powered sensor enhanced soft robotic manipulator. Adv. Sci. 8(14), 2100230 (2021). https://doi.org/10.1002/advs.202100230
  3. Q.F. Shi, B.W. Dong, T.Y.Y. He, Z.D. Sun, J.X. Zhu et al., Progress in wearable electronics/photonics-moving toward the era of artificial intelligence and internet of things. Infomat 2(6), 1131–1162 (2020). https://doi.org/10.1002/inf2.12122
  4. Y.P. Zang, F.J. Zhang, C.A. Di, D.B. Zhu, Advances of flexible pressure sensors toward artificial intelligence and health care applications. Mater. Horiz. 2(2), 140–156 (2015). https://doi.org/10.1039/c4mh00147h
  5. C. Pang, C. Lee, K.Y. Suh, Recent advances in flexible sensors for wearable and implantable devices. J. Appl. Polym. Sci. 130(3), 1429–1441 (2013). https://doi.org/10.1002/app.39461
  6. J.C. Kenry, C.T. Yeo, Lim, Emerging flexible and wearable physical sensing platforms for healthcare and biomedical applications. Microsyst. Nanoeng. 2, 16043 (2016). https://doi.org/10.1038/micronano.2016.43
  7. D. Choi, S. Jang, J.S. Kim, H.J. Kim, D.H. Kim et al., A highly sensitive tactile sensor using a pyramid-plug structure for detecting pressure, shear force, and torsion. Adv. Mater. Technol. 4(3), 1800284 (2019). https://doi.org/10.1002/admt.201800284
  8. O.A. Moses, L. Gao, H. Zhao, Z. Wang, M. Lawan Adam et al., 2d materials inks toward smart flexible electronics. Mater. Today 50, 116–148 (2021). https://doi.org/10.1016/j.mattod.2021.08.010
  9. D. Kim, J. Kwon, J. Jung, K. Kim, H. Lee et al., A transparent and flexible capacitive-force touch pad from high-aspect-ratio copper nanowires with enhanced oxidation resistance for applications in wearable electronics. Small Methods 2(7), 1800077 (2018). https://doi.org/10.1002/smtd.201800077
  10. K.K. Kim, I. Ha, P. Won, D.G. Seo, K.J. Cho et al., Transparent wearable three-dimensional touch by self-generated multiscale structure. Nat Commun. (2019). https://doi.org/10.1038/s41467-019-10736-6
  11. P. Won, J.J. Park, T. Lee, I. Ha, S. Han et al., Stretchable and transparent kirigami conductor of nanowire percolation network for electronic skin applications. Nano Lett. 19(9), 6087–6096 (2019). https://doi.org/10.1021/acs.nanolett.9b02014
  12. P. Won, K.K. Kim, H. Kim, J.J. Park, I. Ha et al., Transparent soft actuators/sensors and camouflage skins for imperceptible soft robotics. Adv. Mater. 33(19), 2002397 (2021). https://doi.org/10.1002/adma.202002397
  13. Y. Chu, J.W. Zhong, H.L. Liu, Y. Ma, N. Liu et al., Human pulse diagnosis for medical assessments using a wearable piezoelectret sensing system. Adv. Funct. Mater. 28(40), 1803413 (2018). https://doi.org/10.1002/adfm.201803413
  14. Y.S. Fang, Y.J. Zou, J. Xu, G.R. Chen, Y.H. Zhou et al., Ambulatory cardiovascular monitoring via a machine-learning-assisted textile triboelectric sensor. Adv. Mater. 33(41), 2104178 (2021). https://doi.org/10.1002/adma.202104178
  15. K.H. Huang, F. Tan, T.D. Wang, Y.J. Yang, A highly sensitive pressure-sensing array for blood pressure estimation assisted by machine-learning techniques. Sensors 19(4), 848 (2019). https://doi.org/10.3390/s19040848
  16. J. Ramirez, D. Rodriquez, F. Qiao, J. Warchall, J. Rye et al., Metallic nanoislands on graphene for monitoring swallowing activity in head and neck cancer patients. ACS Nano 12(6), 5913–5922 (2018). https://doi.org/10.1021/acsnano.8b02133
  17. B. Polat, L.L. Becerra, P.Y. Hsu, V. Kaipu, P.P. Mercier et al., Epidermal graphene sensors and machine learning for estimating swallowed volume. ACS Appl. Nano Mater. 4(8), 8126–8134 (2021). https://doi.org/10.1021/acsanm.1c01378
  18. J.H. Han, K.M. Bae, S.K. Hong, H. Park, J.H. Kwak et al., Machine learning-based self-powered acoustic sensor for speaker recognition. Nano Energy 53, 658–665 (2018). https://doi.org/10.1016/j.nanoen.2018.09.030
  19. H.S. Wang, S.K. Hong, J.H. Han, Y.H. Jung, H.K. Jeong et al., Biomimetic and flexible piezoelectric mobile acoustic sensors with multiresonant ultrathin structures for machine learning biometrics. Sci. Adv. 7(7), eabe5683 (2021). https://doi.org/10.1126/sciadv.abe5683
  20. Z.W. Lin, G.Q. Zhang, X. Xiao, C. Au, Y.H. Zhou et al., A personalized acoustic interface for wearable human-machine interaction. Adv. Funct. Mater. 32(9), 2109430 (2022). https://doi.org/10.1002/adfm.202109430
  21. Q.F. Shi, Z.X. Zhang, T.Y.Y. He, Z.D. Sun, B.J. Wang et al., Deep learning enabled smart mats as a scalable floor monitoring system. Nat. Commun. 11(1), 4609 (2020). https://doi.org/10.1038/s41467-020-18471-z
  22. H.C. Yao, W.D. Yang, W. Cheng, Y.J. Tan, H.H. See et al., Near-hysteresis-free soft tactile electronic skins for wearables and reliable machine learning. Proc. Natl. Acad. Sci. USA 117(41), 25352–25359 (2020). https://doi.org/10.1073/pnas.2010989117
  23. Z.H. Zhou, K. Chen, X.S. Li, S.L. Zhang, Y.F. Wu et al., Sign-to-speech translation using machine-learning-assisted stretchable sensor arrays. Nat. Electron. 3(9), 571–578 (2020). https://doi.org/10.1038/s41928-020-0428-6
  24. A. Moin, A. Zhou, A. Rahimi, A. Menon, S. Benatti et al., A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition. Nat. Electron. 4(1), 54–63 (2021). https://doi.org/10.1038/s41928-020-00510-8
  25. A. Alagumalai, W. Shou, O. Mahian, M. Aghbashlo, M. Tabatabaei et al., Self-powered sensing systems with learning capability. Joule 6(7), 1475–1500 (2022). https://doi.org/10.1016/j.joule.2022.06.001
  26. M. Wang, T. Wang, Y.F. Luo, K. He, L. Pan et al., Fusing stretchable sensing technology with machine learning for human-machine interfaces. Adv. Funct. Mater. 31(39), 2008807 (2021). https://doi.org/10.1002/adfm.202008807
  27. Y.H. Jung, S.K. Hong, H.S. Wang, J.H. Han, T.X. Pham et al., Flexible piezoelectric acoustic sensors and machine learning for speech processing. Adv. Mater. 32(35), 1904020 (2020). https://doi.org/10.1002/adma.201904020
  28. S.H. Kwon, L. Dong, Flexible sensors and machine learning for heart monitoring. Nano Energy 102, 107632 (2022). https://doi.org/10.1016/j.nanoen.2022.107632
  29. M.L. Zhu, T.Y.Y. He, C.K. Lee, Technologies toward next generation human machine interfaces: from machine learning enhanced tactile sensing to neuromorphic sensory systems. Appl. Phys. Rev. 7(3), 031305 (2020). https://doi.org/10.1063/5.0016485
  30. B. Shih, D. Shah, J.X. Li, T.G. Thuruthel, Y.L. Park et al., Electronic skins and machine learning for intelligent soft robots. Sci. Robot. 5(41), aaz9239 (2020). https://doi.org/10.1126/scirobotics.aaz9239
  31. S. Gao, C. Zheng, Y. Zhao, Z. Wu, J. Li et al., Comparison of enhancement techniques based on neural networks for attenuated voice signal captured by flexible vibration sensors on throats. Nanotechnol. Precis. Eng. 5(1), 013001 (2022). https://doi.org/10.1063/10.0009187
  32. H.C. Yao, P.J. Li, W. Cheng, W.D. Yang, Z.J. Yang et al., Environment-resilient graphene vibrotactile sensitive sensors for machine intelligence. ACS Mater. Lett. 2(8), 986–992 (2020). https://doi.org/10.1021/acsmaterialslett.0c00160
  33. W.D. Li, K. Ke, J. Jia, J.H. Pu, X. Zhao et al., Recent advances in multiresponsive flexible sensors towards e-skin: a delicate design for versatile sensing. Small 18(7), 2103734 (2022). https://doi.org/10.1002/smll.202103734
  34. S. Sundaram, P. Kellnhofer, Y.Z. Li, J.Y. Zhu, A. Torralba et al., Learning the signatures of the human grasp using a scalable tactile glove. Nature 569(7758), 698 (2019). https://doi.org/10.1038/s41586-019-1234-z
  35. H. Jeong, J.A. Rogers, S. Xu, Continuous on-body sensing for the covid-19 pandemic: gaps and opportunities. Sci. Adv. 6(36), eabd4794 (2020). https://doi.org/10.1126/sciadv.abd4794
  36. J.H. Lee, J.S. Heo, Y.J. Kim, J. Eom, H.J. Jung et al., A behavior-learned cross-reactive sensor matrix for intelligent skin perception. Adv. Mater. 32(22), 2000969 (2020). https://doi.org/10.1002/adma.202000969
  37. H. Xu, W. Zheng, Y. Wang, D. Xu, N. Zhao et al., Flexible tensile strain-pressure sensor with an off-axis deformation-insensitivity. Nano Energy 107, 384 (2022). https://doi.org/10.1016/j.nanoen.2022.107384
  38. A.A. Barlian, W.T. Park, J.R. Mallon, A.J. Rastegar, B.L. Pruitt, Review: semiconductor piezoresistance for microsystems. Proc. IEEE 97(3), 513–552 (2009). https://doi.org/10.1109/Jproc.2009.2013612
  39. A.S. Fiorillo, C.D. Critello, S.A. Pullano, Theory, technology and applications of piezoresistive sensors: a review. Sensor Actuat. A-Phys. 281, 156–175 (2018). https://doi.org/10.1016/j.sna.2018.07.006
  40. F. Li, T. Shen, C. Wang, Y. Zhang, J. Qi et al., Recent advances in strain-induced piezoelectric and piezoresistive effect-engineered 2d semiconductors for adaptive electronics and optoelectronics. Nano-Micro Lett. 12(1), 106 (2020). https://doi.org/10.1007/s40820-020-00439-9
  41. S.C. Kim, K.D. Wise, Temperature sensitivity in silicon piezoresistive pressure transducers. IEEE Trans. Electron. Dev. 30(7), 802–810 (1983). https://doi.org/10.1109/T-Ed.1983.21213
  42. M. Akbar, M.A. Shanblatt, Temperature compensation of piezoresistive pressure sensors. Sensor Actuat. A-Phys. 33(3), 155–162 (1992). https://doi.org/10.1016/0924-4247(92)80161-U
  43. J. Oh, J.O. Kim, Y. Kim, H.B. Choi, J.C. Yang et al., Highly uniform and low hysteresis piezoresistive pressure sensors based on chemical grafting of polypyrrole on elastomer template with uniform pore size. Small 15(33), 1901744 (2019). https://doi.org/10.1002/smll.201901744
  44. M. Amjadi, K.U. Kyung, I. Park, M. Sitti, Stretchable, skin-mountable, and wearable strain sensors and their potential applications: a review. Adv. Funct. Mater. 26(11), 1678–1698 (2016). https://doi.org/10.1002/adfm.201504755
  45. D. Kang, P.V. Pikhitsa, Y.W. Choi, C. Lee, S.S. Shin et al., Ultrasensitive mechanical crack-based sensor inspired by the spider sensory system. Nature 516(7530), 222–226 (2014). https://doi.org/10.1038/nature14002
  46. A. de la Vega, J. Sumfleth, H. Wittich, K. Schulte, Time and temperature dependent piezoresistance of carbon nanofiller/polymer composites under dynamic load. J. Mater. Sci. 47(6), 2648–2657 (2012). https://doi.org/10.1007/s10853-011-6090-7
  47. W.P. Mason, Crystal Physics of Interaction Processes (Academic Press, Cambridge, 1966)
  48. R. Zallen, The Physics of Amorphous Solids (Wiley, New York, 2008)
  49. D. Stauffer, A. Aharony, Introduction to Percolation Theory (Taylor & Francis, Abingdon-on-Thames, 2018)
  50. K.K. Kim, S. Hong, H.M. Cho, J. Lee, Y.D. Suh et al., Highly sensitive and stretchable multidimensional strain sensor with prestrained anisotropic metal nanowire percolation networks. Nano Lett. 15(8), 5240–5247 (2015). https://doi.org/10.1021/acs.nanolett.5b01505
  51. H. Jeong, S. Park, J. Lee, P. Won, S.H. Ko et al., Fabrication of transparent conductive film with flexible silver nanowires using roll-to-roll slot-die coating and calendering and its application to resistive touch panel. Adv. Electron. Mater. 4(11), 1800243 (2018). https://doi.org/10.1002/aelm.201800243
  52. I. Hong, S. Lee, D. Kim, H. Cho, Y. Roh et al., Study on the oxidation of copper nanowire network electrodes for skin mountable flexible, stretchable and wearable electronics applications. Nanotechnology 30(7), 074001 (2019). https://doi.org/10.1088/1361-6528/aaf35c
  53. Z. Chen, T. Ming, M.M. Goulamaly, H.M. Yao, D. Nezich et al., Enhancing the sensitivity of percolative graphene films for flexible and transparent pressure sensor arrays. Adv. Funct. Mater. 26(28), 5061–5067 (2016). https://doi.org/10.1002/adfm.201503674
  54. T. Yamada, Y. Hayamizu, Y. Yamamoto, Y. Yomogida, A. Izadi-Najafabadi et al., A stretchable carbon nanotube strain sensor for human-motion detection. Nat. Nanotechnol. 6(5), 296–301 (2011). https://doi.org/10.1038/Nnano.2011.36
  55. Y. Huang, X.Y. He, L. Gao, Y. Wang, C.X. Liu et al., Pressure-sensitive carbon black/graphene nanoplatelets-silicone rubber hybrid conductive composites based on a three-dimensional polydopamine-modified polyurethane sponge. J. Mater. Sci. Mater. El. 28(13), 9495–9504 (2017). https://doi.org/10.1007/s10854-017-6693-0
  56. S.H. Munsonmcgee, Estimation of the critical concentration in an anisotropic percolation network. Phys. Rev. B 43(4), 3331–3336 (1991). https://doi.org/10.1103/PhysRevB.43.3331
  57. D.S. Mclachlan, M. Blaszkiewicz, R.E. Newnham, Electrical-resistivity of composites. J. Am. Ceram. Soc. 73(8), 2187–2203 (1990). https://doi.org/10.1111/j.1151-2916.1990.tb07576.x
  58. Y. Gao, G.H. Yu, T. Shu, Y.Q. Chen, W.Z. Yang et al., 3d-printed coaxial fibers for integrated wearable sensor skin. Adv. Mater. Technol. 4(10), 1900504 (2019). https://doi.org/10.1002/admt.201900504
  59. P.D. Feng, Y. Zheng, K. Li, W.W. Zhao, Highly stretchable and sensitive strain sensors with ginkgo-like sandwich architectures. Nanoscale Adv. 4(6), 1681–1693 (2022). https://doi.org/10.1039/d1na00817j
  60. C.C. Li, B.Z. Zhou, Y.F. Zhou, J.W. Ma, F.L. Zhou et al., Carbon nanotube coated fibrous tubes for highly stretchable strain sensors having high linearity. Nanomaterials 12(14), 2458 (2022). https://doi.org/10.3390/nano12142458
  61. Y. Gao, T. Xiao, Q. Li, Y. Chen, X.L. Qiu et al., Flexible microstructured pressure sensors: design, fabrication and applications. Nanotechnology 33(32), 322002 (2022). https://doi.org/10.1088/1361-6528/ac6812
  62. Y. Gao, M.D. Xu, G.H. Yu, J.P. Tan, F.Z. Xuan, Extrusion printing of carbon nanotube-coated elastomer fiber with microstructures for flexible pressure sensors. Sensor Actuat. A-Phys. 299, 111625 (2019). https://doi.org/10.1016/j.sna.2019.111625
  63. G. Yang, L. Cong, G.H. Yu, S. Jin, J.P. Tan et al., Laser micro-structured pressure sensor with modulated sensitivity for electronic skins. Nanotechnology 30(32), 325502 (2019). https://doi.org/10.1088/1361-6528/ab1a86
  64. J.A. Greenwood, Constriction resistance and the real area of contact. Br. J. Appl. Phys. 17(12), 1621 (1966). https://doi.org/10.1088/0508-3443/17/12/310
  65. T.T. Yang, X.M. Li, X. Jiang, S.Y. Lin, J.C. Lao et al., Structural engineering of gold thin films with channel cracks for ultrasensitive strain sensing. Mater. Horiz. 3(3), 248–255 (2016). https://doi.org/10.1039/c6mh00027d
  66. B. Park, J. Kim, D. Kang, C. Jeong, K.S. Kim et al., Dramatically enhanced mechanosensitivity and signal-to-noise ratio of nanoscale crack-based sensors: effect of crack depth. Adv. Mater. 28(37), 8130–8137 (2016). https://doi.org/10.1002/adma.201602425
  67. J. Lee, S. Kim, J. Lee, D. Yang, B.C. Park et al., A stretchable strain sensor based on a metal nanop thin film for human motion detection. Nanoscale 6(20), 11932–11939 (2014). https://doi.org/10.1039/c4nr03295k
  68. C.J. Lee, K.H. Park, C.J. Han, M.S. Oh, B. You et al., Crack-induced ag nanowire networks for transparent, stretchable, and highly sensitive strain sensors. Sci. Rep. 7, 7959 (2017). https://doi.org/10.1038/s41598-017-08484-y
  69. Y.Y. Xin, J. Zhou, X.Z. Xu, G. Lubineau, Laser-engraved carbon nanotube paper for instilling high sensitivity, high stretchability, and high linearity in strain sensors. Nanoscale 9(30), 10897–10905 (2017). https://doi.org/10.1039/c7nr01626c
  70. S.J. Chen, R.Y. Wu, P. Li, Q. Li, Y. Gao et al., Acid-interface engineering of carbon nanotube/elastomers with enhanced sensitivity for stretchable strain sensors. ACS Appl. Mater. Interfaces 10(43), 37760–37766 (2018). https://doi.org/10.1021/acsami.8b16591
  71. Q. Li, K. Wang, Y. Gao, J.P. Tan, R.Y. Wu et al., Highly sensitive wearable strain sensor based on ultra-violet/ozone cracked carbon nanotube/elastomer. Appl. Phys. Lett. 112(26), 263501 (2018). https://doi.org/10.1063/1.5029391
  72. X.X. Gong, G.T. Fei, W.B. Fu, M. Fang, X.D. Gao et al., Flexible strain sensor with high performance based on pani/pdms films. Org. Electron. 47, 51–56 (2017). https://doi.org/10.1016/j.orgel.2017.05.001
  73. Y.X. Qin, H.C. Xu, S.Y. Li, D.D. Xu, W.H. Zheng et al., Dual-mode flexible capacitive sensor for proximity-tactile interface and wireless perception. IEEE Sens J. 22(11), 10446–10453 (2022). https://doi.org/10.1109/JSEN.2022.3171218
  74. H.C. Guo, Y.J. Tan, G. Chen, Z.F. Wang, G.J. Susanto et al., Artificially innervated self-healing foams as synthetic piezo-impedance sensor skins. Nat. Commun. (2020). https://doi.org/10.1038/s41467-020-19531-0
  75. B. Zhang, Z.M. Xiang, S.W. Zhu, Q.Y. Hu, Y.Z. Cao et al., Dual functional transparent film for proximity and pressure sensing. Nano Res. 7(10), 1488–1496 (2014). https://doi.org/10.1007/s12274-014-0510-3
  76. S.C. Chen, Y.F. Wang, L. Yang, F. Karouta, K. Sun, Electron-induced perpendicular graphene sheets embedded porous carbon film for flexible touch sensors. Nano-Micro Lett. 12(1), 136 (2020). https://doi.org/10.1007/s40820-020-00480-8
  77. G. Libo, M. Wang, W.D. Wang, H.C. Xu, Y.J. Wang et al., Highly sensitive pseudocapacitive iontronic pressure sensor with broad sensing range. Nano-Micro Lett. 13(1), 140 (2021). https://doi.org/10.1007/s40820-021-00664-w
  78. H.C. Xu, L.B. Gao, H.T. Zhao, H.L. Huang, Y.J. Wang et al., Stretchable and anti-impact iontronic pressure sensor with an ultrabroad linear range for biophysical monitoring and deep learning-aided knee rehabilitation. Microsyst. Nanoeng. 7(1), 92 (2021). https://doi.org/10.1038/s41378-021-00318-2
  79. B.Q. Nie, S.Y. Xing, J.D. Brandt, T.R. Pan, Droplet-based interfacial capacitive sensing. Lab. Chip 12(6), 1110–1118 (2012). https://doi.org/10.1039/c2lc21168h
  80. N.N. Bai, L. Wang, Q. Wang, J. Deng, Y. Wang et al., Graded intrafillable architecture-based iontronic pressure sensor with ultra-broad-range high sensitivity. Nat. Commun. 11(1), 209 (2020). https://doi.org/10.1038/s41467-019-14054-9
  81. Q. Liu, Y. Liu, J. Shi, Z. Liu, Q. Wang et al., High-porosity foam-based iontronic pressure sensor with superhigh sensitivity of 9280 kPa−1. Nano-Micro Lett. 14(1), 21 (2022). https://doi.org/10.1007/s40820-021-00770-9
  82. Y. Chang, L. Wang, R.Y. Li, Z.C. Zhang, Q. Wang et al., First decade of interfacial iontronic sensing: from droplet sensors to artificial skins. Adv. Mater. 33(7), 2003464 (2021). https://doi.org/10.1002/adma.202003464
  83. Z.J. Zhu, R.Y. Li, T.R. Pan, Imperceptible epidermal-iontronic interface for wearable sensing. Adv. Mater. 30(6), 1705122 (2018). https://doi.org/10.1002/adma.201705122
  84. G. Zhu, C.F. Pan, W.X. Guo, C.Y. Chen, Y.S. Zhou et al., Triboelectric-generator-driven pulse electrodeposition for micropatterning. Nano Lett. 12(9), 4960–4965 (2012). https://doi.org/10.1021/nl302560k
  85. F.R. Fan, Z.Q. Tian, Z.L. Wang, Flexible triboelectric generator! Nano Energy 1(2), 328–334 (2012). https://doi.org/10.1016/j.nanoen.2012.01.004
  86. Z.L. Wang, Triboelectric nanogenerators as new energy technology for self-powered systems and as active mechanical and chemical sensors. ACS Nano 7(11), 9533–9557 (2013). https://doi.org/10.1021/nn404614z
  87. L. Lin, Y.N. Xie, S.H. Wang, W.Z. Wu, S.M. Niu et al., Triboelectric active sensor array for self-powered static and dynamic pressure detection and tactile imaging. ACS Nano 7(9), 8266–8274 (2013). https://doi.org/10.1021/nn4037514
  88. Y. Wu, Y. Ma, H. Zheng, S.J.M. Ramakrishna, Design Piezoelectric materials for flexible and wearable electronics: a review. Mater. Des. 211, 110164 (2021). https://doi.org/10.1016/j.matdes.2021.110164
  89. C. Yan, W.L. Deng, L. Jin, T. Yang, Z.X. Wang et al., Epidermis-inspired ultrathin 3d cellular sensor array for self-powered biomedical monitoring. ACS Appl. Mater. Interfaces 10(48), 41070–41075 (2018). https://doi.org/10.1021/acsami.8b14514
  90. L. Persano, C. Dagdeviren, Y.W. Su, Y.H. Zhang, S. Girardo et al., High performance piezoelectric devices based on aligned arrays of nanofibers of poly(vinylidenefluoride-co-trifluoroethylene). Nat. Commun. 4, 1633 (2013). https://doi.org/10.1038/ncomms2639
  91. J. Tao, M. Dong, L. Li, C.F. Wang, J. Li et al., Real-time pressure mapping smart insole system based on a controllable vertical pore dielectric layer. Microsyst. Nanoeng. 6(1), 1–10 (2020). https://doi.org/10.1038/s41378-020-0171-1
  92. X. Chen, B. Assadsangabi, Y. Hsiang, K. Takahata, Enabling angioplasty-ready “smart” stents to detect in-stent restenosis and occlusion. Adv. Sci. 5(5), 1700560 (2018). https://doi.org/10.1002/advs.201700560
  93. H.C. Xu, L.B. Gao, Y.J. Wang, K. Cao, X.K. Hu et al., Flexible waterproof piezoresistive pressure sensors with wide linear working range based on conductive fabrics. Nano-Micro Lett. 12(1), 159 (2020). https://doi.org/10.1007/s40820-020-00498-y
  94. E. Roh, B.U. Hwang, D. Kim, B.Y. Kim, N.E. Lee, Stretchable, transparent, ultrasensitive, and patchable strain sensor for human-machine interfaces comprising a nanohybrid of carbon nanotubes and conductive elastomers. ACS Nano 9(6), 6252–6261 (2015). https://doi.org/10.1021/acsnano.5b01613
  95. S. Wang, Y.L. Fang, H. He, L. Zhang, C.A. Li et al., Wearable stretchable dry and self-adhesive strain sensors with conformal contact to skin for high-quality motion monitoring. Adv. Funct. Mater. 31(5), 2007495 (2021). https://doi.org/10.1002/adfm.202007495
  96. Y.H. Liu, J.J.S. Norton, R. Qazi, Z.N. Zou, K.R. Ammann et al., Epidermal mechano-acoustic sensing electronics for cardiovascular diagnostics and human-machine interfaces. Sci. Adv. 2(11), e1601185 (2016). https://doi.org/10.1126/sciadv.1601185
  97. S. Lee, J. Kim, I. Yun, G.Y. Bae, D. Kim et al., An ultrathin conformable vibration-responsive electronic skin for quantitative vocal recognition. Nat. Commun. 10, 2468 (2019). https://doi.org/10.1038/s41467-019-10465-w
  98. M.L. Liu, Z.H. Zeng, H. Xu, Y.Z. Liao, L.M. Zhou et al., Applications of a nanocomposite-inspired in-situ broadband ultrasonic sensor to acousto-ultrasonics-based passive and active structural health monitoring. Ultrasonics 78, 166–174 (2017). https://doi.org/10.1016/j.ultras.2017.03.007
  99. W.N. Xiong, C. Zhu, D.L. Guo, C. Hou, Z.X. Yang et al., Bio-inspired, intelligent flexible sensing skin for multifunctional flying perception. Nano Energy 90, 106550 (2021). https://doi.org/10.1016/j.nanoen.2021.106550
  100. S.M. Won, H.L. Wang, B.H. Kim, K. Lee, H. Jang et al., Multimodal sensing with a three-dimensional piezoresistive structure. ACS Nano 13(10), 10972–10979 (2019). https://doi.org/10.1021/acsnano.9b02030
  101. S. Gong, W. Schwalb, Y.W. Wang, Y. Chen, Y. Tang et al., A wearable and highly sensitive pressure sensor with ultrathin gold nanowires. Nat. Commun. 5, 3132 (2014). https://doi.org/10.1038/ncomms4132
  102. K.Y. Shin, J.S. Lee, J. Jang, Highly sensitive, wearable and wireless pressure sensor using free-standing ZnO nanoneedle/PVDF hybrid thin film for heart rate monitoring. Nano Energy 22, 95–104 (2016). https://doi.org/10.1016/j.nanoen.2016.02.012
  103. Y. Gao, G.H. Yu, J.P. Tan, F.Z. Xuan, Sandpaper-molded wearable pressure sensor for electronic skins. Sensor Actuat. A-Phys. 280, 205–209 (2018). https://doi.org/10.1016/j.sna.2018.07.048
  104. Y. Lee, J. Park, S. Cho, Y.E. Shin, H. Lee et al., Flexible ferroelectric sensors with ultrahigh pressure sensitivity and linear response over exceptionally broad pressure range. ACS Nano 12(4), 4045–4054 (2018). https://doi.org/10.1021/acsnano.8b01805
  105. A.H.A. Razak, A. Zayegh, R.K. Begg, Y. Wahab, Foot plantar pressure measurement system: a review. Sensors 12(7), 9884–9912 (2012). https://doi.org/10.3390/s120709884
  106. L.J. Pan, A. Chortos, G.H. Yu, Y.Q. Wang, S. Isaacson et al., An ultra-sensitive resistive pressure sensor based on hollow-sphere microstructure induced elasticity in conducting polymer film. Nat. Commun. 5, 3002 (2014). https://doi.org/10.1038/ncomms4002
  107. L.B. Gao, Y.J. Wang, X.K. Hu, W.Z. Zhou, K. Cao et al., Cellular carbon-film-based flexible sensor and waterproof supercapacitors. ACS Appl. Mater. Interfaces 11(29), 26288–26297 (2019). https://doi.org/10.1021/acsami.9b09438
  108. L.B. Gao, K. Cao, X.K. Hu, R. Xiao, B. Gan et al., Nano electromechanical approach for flexible piezoresistive sensor. Appl. Mater. Today 18, 100475 (2020). https://doi.org/10.1016/j.apmt.2019.100475
  109. L.B. Gao, N.J. Zhao, H.C. Xu, X.K. Hu, D.D. Xu et al., Flexible pressure sensor with wide linear sensing range for human-machine interaction. IEEE Trans. Electron. Dev. 69(7), 3901–3907 (2022). https://doi.org/10.1109/Ted.2022.3173916
  110. L.B. Gao, Y. Han, J.U. Surjadi, K. Cao, W.Z. Zhou et al., Magnetically induced micropillar arrays for an ultrasensitive flexible sensor with a wireless recharging system. Sci. China Mater. 64(8), 1977–1988 (2021). https://doi.org/10.1007/s40843-020-1637-9
  111. Y.J. Wang, X. Li, S.F. Fan, X.B. Feng, K. Cao et al., Three-dimensional stretchable microelectronics by projection microstereolithography (PμSL). ACS Appl. Mater. Interfaces 13(7), 8901–8908 (2021). https://doi.org/10.1021/acsami.0c20162
  112. C.-Z. Hang, X.-F. Zhao, S.-Y. Xi, Y.-H. Shang, K.-P. Yuan et al., Highly stretchable and self-healing strain sensors for motion detection in wireless human-machine interface. Nano Energy 76, 105064 (2020). https://doi.org/10.1016/j.nanoen.2020.105064
  113. J. Eom, R. Jaisutti, H. Lee, W. Lee, J.S. Heo et al., Highly sensitive textile strain sensors and wireless user-interface devices using all-polymeric conducting fibers. ACS Appl. Mater. Interfaces 9(11), 10190–10197 (2017). https://doi.org/10.1021/acsami.7b01771
  114. M. Wang, Z. Yan, T. Wang, P.Q. Cai, S.Y. Gao et al., Gesture recognition using a bioinspired learning architecture that integrates visual data with somatosensory data from stretchable sensors. Nat. Electron. 3(9), 563 (2020). https://doi.org/10.1038/s41928-020-0422-z
  115. H. Zhang, D. Liu, J.H. Lee, H.M. Chen, E. Kim et al., Anisotropic, wrinkled, and crack-bridging structure for ultrasensitive, highly selective multidirectional strain sensors. Nano-Micro Lett. 13(1), 122 (2021). https://doi.org/10.1007/s40820-021-00615-5
  116. X. Wang, X.H. Liu, D.W. Schubert, Highly sensitive ultrathin flexible thermoplastic polyurethane/carbon black fibrous film strain sensor with adjustable scaffold networks. Nano-Micro Lett. 13(1), 64 (2021). https://doi.org/10.1007/s40820-021-00592-9
  117. Z.K. Liu, T.X. Zhu, J.R. Wang, Z.J. Zheng, Y. Li et al., Functionalized fiber-based strain sensors: Pathway to next-generation wearable electronics. Nano-Micro Lett. 14(1), 61 (2022). https://doi.org/10.1007/s40820-022-00806-8
  118. Y. Wang, L. Wang, T.T. Yang, X. Li, X.B. Zang et al., Wearable and highly sensitive graphene strain sensors for human motion monitoring. Adv. Funct. Mater. 24(29), 4666–4670 (2014). https://doi.org/10.1002/adfm.201400379
  119. S.Q. Liu, R.M. Zheng, S. Chen, Y.H. Wu, H.Z. Liu et al., A compliant, self-adhesive and self-healing wearable hydrogel as epidermal strain sensor. J. Mater. Chem. C 6(15), 4183–4190 (2018). https://doi.org/10.1039/c8tc00157j
  120. N. Qaiser, F. Al-Modaf, S.M. Khan, S.F. Shaikh, N. El-Atab et al., A robust wearable point-of-care cnt-based strain sensor for wirelessly monitoring throat-related illnesses. Adv. Funct. Mater. 31(29), 2103375 (2021). https://doi.org/10.1002/adfm.202103375
  121. T.Q. Trung, N.E. Lee, Flexible and stretchable physical sensor integrated platforms for wearable human-activity monitoring and personal healthcare. Adv. Mater. 28(22), 4338–4372 (2016). https://doi.org/10.1002/adma.201504244
  122. C.Y. Yan, J.X. Wang, W.B. Kang, M.Q. Cui, X. Wang et al., Highly stretchable piezoresistive graphene-nanocellulose nanopaper for strain sensors. Adv. Mater. 26(13), 2022–2027 (2014). https://doi.org/10.1002/adma.201304742
  123. M. Amjadi, A. Pichitpajongkit, S. Lee, S. Ryu, I. Park, Highly stretchable and sensitive strain sensor based on silver nanowire-elastomer nanocomposite. ACS Nano 8(5), 5154–5163 (2014). https://doi.org/10.1021/nn501204t
  124. Z.C. Yan, T.S. Pan, D.K. Wang, J.C. Li, L. Jin et al., Stretchable micromotion sensor with enhanced sensitivity using serpentine layout. Acs Appl Mater Inter. 11(13), 12261–12271 (2019). https://doi.org/10.1021/acsami.8b22613
  125. Y. Jiang, Z.Y. Liu, N. Matsuhisa, D.P. Qi, W.R. Leow et al., Auxetic mechanical metamaterials to enhance sensitivity of stretchable strain sensors. Adv Mater. 30(12), 1706589 (2018). https://doi.org/10.1002/adma.201706589
  126. J. Rostami, P.W. Tse, M.D. Yuan, Detection of broken wires in elevator wire ropes with ultrasonic guided waves and tone-burst wavelet. Struct. Health Monit. 19(2), 481–494 (2020). https://doi.org/10.1177/1475921719855915
  127. A. Awwad, M. Yahyia, L. Albasha, M.M. Mortula, T. Ali, Communication network for ultrasonic acoustic water leakage detectors. IEEE Access. 8, 29954–29964 (2020). https://doi.org/10.1109/Access.2020.2972648
  128. Z.W. Lin, C.C. Sun, G.Q. Zhang, E.D. Fan, Z.H. Zhou et al., Flexible triboelectric nanogenerator toward ultrahigh-frequency vibration sensing. Nano Res. 15, 7484–7491 (2022). https://doi.org/10.1007/s12274-022-4363-x
  129. X.L. Chen, Q. Zeng, J.Y. Shao, S. Li, X.M. Li et al., Channel-crack-designed suspended sensing membrane as a fully flexible vibration sensor with high sensitivity and dynamic range. ACS Appl. Mater. Interfaces 13(29), 34637–34647 (2021). https://doi.org/10.1021/acsami.1c09963
  130. Q.L. Wang, P. Xiao, W. Zhou, Y. Liang, G.Q. Yin et al., Bioinspired adaptive, elastic, and conductive graphene structured thin-films achieving high-efficiency underwater detection and vibration perception. Nano-Micro Lett. 14(1), 62 (2022). https://doi.org/10.1007/s40820-022-00799-4
  131. K. Zhou, C. Zhang, Z.Y. Xiong, H.Y. Chen, T. Li et al., Template-directed growth of hierarchical mof hybrid arrays for tactile sensor. Adv. Funct. Mater. 30(38), 2001296 (2020). https://doi.org/10.1002/adfm.202001296
  132. Z. Liu, S. Zhang, Y.M. Jin, H. Ouyang, Y. Zou et al., Flexible piezoelectric nanogenerator in wearable self-powered active sensor for respiration and healthcare monitoring. Semicond. Sci. Tech. 32(6), 064004 (2017). https://doi.org/10.1088/1361-6641/aa68d1
  133. Z. Zhang, Q.L. Liao, X.Q. Yan, Z.L. Wang, W.D. Wang et al., Functional nanogenerators as vibration sensors enhanced by piezotronic effects. Nano Res. 7(2), 190–198 (2014). https://doi.org/10.1007/s12274-013-0386-7
  134. Y.F. Liu, Q. Liu, Y.Q. Li, P. Huang, J.Y. Yao et al., Spider-inspired ultrasensitive flexible vibration sensor for multifunctional sensing. ACS Appl. Mater. Interfaces 12(27), 30871–30881 (2020). https://doi.org/10.1021/acsami.0c08884
  135. K. Lee, X.Y. Ni, J.Y. Lee, H. Arafa, D.J. Pe et al., Mechano-acoustic sensing of physiological processes and body motions via a soft wireless device placed at the suprasternal notch. Nat. Biomed. Eng. 4(2), 148–158 (2020). https://doi.org/10.1038/s41551-019-0480-6
  136. J.H. Han, J.H. Kwak, D.J. Joe, S.K. Hong, H.S. Wang et al., Basilar membrane-inspired self-powered acoustic sensor enabled by highly sensitive multi tunable frequency band. Nano Energy 53, 198–205 (2018). https://doi.org/10.1016/j.nanoen.2018.08.053
  137. Y.Z. Liao, F. Duan, H.T. Zhang, Y. Lu, Z.H. Zeng et al., Ultrafast response of spray-on nanocomposite piezoresistive sensors to broadband ultrasound. Carbon 143, 743–751 (2019). https://doi.org/10.1016/j.carbon.2018.11.074
  138. F. Duan, Y.Z. Liao, Z.H. Zeng, H. Jin, L.M. Zhou et al., Graphene-based nanocomposite strain sensor response to ultrasonic guided waves. Compos. Sci. Technol. 174, 42–49 (2019). https://doi.org/10.1016/j.compscitech.2019.02.011
  139. Y.H. Li, Y.Z. Liao, Z.Q. Su, Graphene-functionalized polymer composites for self-sensing of ultrasonic waves: an initiative towards “sensor-free” structural health monitoring. Compos. Sci. Technol. 168, 203–213 (2018). https://doi.org/10.1016/j.compscitech.2018.09.021
  140. S. Kang, S. Cho, R. Shanker, H. Lee, J. Park et al., Transparent and conductive nanomembranes with orthogonal silver nanowire arrays for skin-attachable loudspeakers and microphones. Sci. Adv. 4(8), eaas8772 (2018). https://doi.org/10.1126/sciadv.aas8772
  141. Y. Xu, F. Jiang, S. Newbern, A. Huang, C.M. Ho et al., Flexible shear-stress sensor skin and its application to unmanned aerial vehicles. Sensor Actuat. A-dPhys. 105(3), 321–329 (2003). https://doi.org/10.1016/S0924-4247(03)00230-9
  142. Y. Xu, Y.C. Tai, A. Huang, C.M. Ho, Ic-integrated flexible shear-stress sensor skin. J. Microelectromech. Syst. 12(5), 740–747 (2003). https://doi.org/10.1109/Jmems.2003.815831
  143. F.K. Jiang, G.B. Lee, Y.C. Tai, C.M. Ho, A flexible micromachine-based shear-stress sensor array and its application to separation-point detection. Sensor Actuat. A-Phys. 79(3), 194–203 (2000). https://doi.org/10.1016/S0924-4247(99)00277-0
  144. J. Missinne, E. Bosman, B. Van Hoe, G. Van Steenberge, S. Kalathimekkad et al., Flexible shear sensor based on embedded optoelectronic components. IEEE Photon. Techn. Lett. 23(12), 771–773 (2011). https://doi.org/10.1109/Lpt.2011.2134844
  145. H.Y. Yu, L.S. Ai, M. Rouhanizadeh, D. Patel, E.S. Kim et al., Flexible polymer sensors for in vivo intravascular shear stress analysis. J. Microelectromech. Syst. 17(5), 1178–1186 (2008). https://doi.org/10.1109/JMEMS.2008.927749
  146. M.Y. Xie, Y. Zhang, M.J. Krasny, C. Bowen, H. Khanbareh et al., Flexible and active self-powered pressure, shear sensors based on freeze casting ceramic-polymer composites. Energ. Environ. Sci. 11(10), 2919–2927 (2018). https://doi.org/10.1039/c8ee01551a
  147. E.-S. Hwang, J.-H. Seo, Y.-J. Kim, A polymer-based flexible tactile sensor for both normal and shear load detections and its application for robotics. J. Microelectromech. Syst. 16(3), 556–563 (2007). https://doi.org/10.1109/JMEMS.2007.896716
  148. H.K. Lee, J. Chung, S.I. Chang, E. Yoon, Normal and shear force measurement using a flexible polymer tactile sensor with embedded multiple capacitors. J. Microelectromech. Syst. 17(4), 934–942 (2008). https://doi.org/10.1109/JMEMS.2008.921727
  149. J.Z. Yin, V.J. Santos, J.D. Posner, Bioinspired flexible microfluidic shear force sensor skin. Sensor Actuat. A-Phys. 264, 289–297 (2017). https://doi.org/10.1016/j.sna.2017.08.001
  150. C.H. Mu, Y.Q. Song, W.T. Huang, A. Ran, R.J. Sun et al., Flexible normal-tangential force sensor with opposite resistance responding for highly sensitive artificial skin. Adv. Funct. Mater. 28(18), 1707503 (2018). https://doi.org/10.1002/adfm.201707503
  151. J. Park, Y. Lee, J. Hong, Y. Lee, M. Ha et al., Tactile-direction-sensitive and stretchable electronic skins based on human-skin-inspired interlocked microstructures. ACS Nano 8(12), 12020–12029 (2014). https://doi.org/10.1021/nn505953t
  152. S. Pyo, J.I. Lee, M.O. Kim, H.K. Lee, J. Kim, Polymer-based flexible and multi-directional tactile sensor with multiple nicr piezoresistors. Micro Nano Syst. Lett. 7(1), 5 (2019). https://doi.org/10.1186/s40486-019-0085-6
  153. C. Pang, G.Y. Lee, T.I. Kim, S.M. Kim, H.N. Kim et al., A flexible and highly sensitive strain-gauge sensor using reversible interlocking of nanofibres. Nat. Mater. 11(9), 795–801 (2012). https://doi.org/10.1038/Nmat3380
  154. C.M. Boutry, M. Negre, M. Jorda, O. Vardoulis, A. Chortos et al., A hierarchically patterned, bioinspired e-skin able to detect the direction of applied pressure for robotics. Sci. Robot. 3(24), aau6914 (2018). https://doi.org/10.1126/scirobotics.aau6914
  155. F. Yuan, W.H. Wang, S. Liu, J.Y. Zhou, S. Wang et al., A self-powered three-dimensional integrated e-skin for multiple stimuli recognition. Chem. Eng. J. 451, 138522 (2023). https://doi.org/10.1016/j.cej.2022.138522
  156. H.T. Chen, Y. Song, H. Guo, L.M. Miao, X.X. Chen et al., Hybrid porous micro structured finger skin inspired self-powered electronic skin system for pressure sensing and sliding detection. Nano Energy 51, 496–503 (2018). https://doi.org/10.1016/j.nanoen.2018.07.001
  157. Z.Y. Wang, T.Z. Bu, Y.Y. Li, D.Y. Wei, B. Tao et al., Multidimensional force sensors based on triboelectric nanogenerators for electronic skin. ACS Appl. Mater. Interfaces 13(47), 56320–56328 (2021). https://doi.org/10.1021/acsami.1c17506
  158. Y.C. Yan, Z. Hu, Z.B. Yang, W.Z. Yuan, C.Y. Song et al., Soft magnetic skin for super-resolution tactile sensing with force self-decoupling. Sci. Robot. 6(51), eabc8801 (2021). https://doi.org/10.1126/scirobotics.abc8801
  159. J. Park, M. Kim, Y. Lee, H.S. Lee, H. Ko, Fingertip skin-inspired microstructured ferroelectric skins discriminate static/dynamic pressure and temperature stimuli. Sci. Adv. 1(9), e1500661 (2015). https://doi.org/10.1126/sciadv.1500661
  160. J. Missinne, E. Bosman, B. Van Hoe, G. Van Steenberge, P. Van Daele et al., Embedded flexible optical shear sensor. IEEE Sensors (2010). https://doi.org/10.1109/Icsens.2010.5690919
  161. K.K. Kim, I. Ha, P. Won, D.G. Seo, K.J. Cho et al., Transparent wearable three-dimensional touch by self-generated multiscale structure. Nat. Commun. (2019). https://doi.org/10.1038/s41467-019-10736-6
  162. H.B. Liu, H.C. Xiang, Y. Wang, Z.J. Li, L.W. Qian et al., A flexible multimodal sensor that detects strain, humidity, temperature, and pressure with carbon black and reduced graphene oxide hierarchical composite on paper. ACS Appl. Mater. Interfaces 11(43), 40613–40619 (2019). https://doi.org/10.1021/acsami.9b13349
  163. Y.Y. Lu, K.C. Xu, L.S. Zhang, M. Deguchi, H. Shishido et al., Multimodal plant healthcare flexible sensor system. ACS Nano 14(9), 10966–10975 (2020). https://doi.org/10.1021/acsnano.0c03757
  164. I. You, D.G. Mackanic, N. Matsuhisa, J. Kang, J. Kwon et al., Artificial multimodal receptors based on ion relaxation dynamics. Science 370(6519), 961 (2020). https://doi.org/10.1126/science.aba5132
  165. M. Cai, Z.D. Jiao, S. Nie, C.J. Wang, J. Zou et al., A multifunctional electronic skin based on patterned metal films for tactile sensing with a broad linear response range. Sci. Adv. 7(52), eabl8313 (2021). https://doi.org/10.1126/sciadv.abl8313
  166. Z. Yang, S. Lv, Y. Zhang, J. Wang, L. Jiang et al., Self-assembly 3d porous crumpled mxene spheres as efficient gas and pressure sensing material for transient all-mxene sensors. Nano-Micro Lett. 14(1), 56 (2022). https://doi.org/10.1007/s40820-022-00796-7
  167. R.X. Yang, W.Q. Zhang, N. Tiwari, H. Yan, T.J. Li et al., Multimodal sensors with decoupled sensing mechanisms. Adv. Sci. 9(26), 202202470 (2022). https://doi.org/10.1002/advs.202202470
  168. F.Y. Cui, Y. Yue, Y. Zhang, Z.M. Zhang, H.S. Zhou, Advancing biosensors with machine learning. ACS Sensors 5(11), 3346–3364 (2020). https://doi.org/10.1021/acssensors.0c01424
  169. Y. Fang, J. Xu, X. Xiao, Y. Zou, X. Zhao et al., A deep-learning assisted on-mask sensor network for adaptive respiratory monitoring. Adv. Mater. (2022). https://doi.org/10.1002/adma.202200252
  170. Z.K. Zeng, Z. Huang, K.M. Leng, W.X. Han, H. Niu et al., Nonintrusive monitoring of mental fatigue status using epidermal electronic systems and machine-learning algorithms. ACS Sensors 5(5), 1305–1313 (2020). https://doi.org/10.1021/acssensors.9b02451
  171. N. Bokka, V. Selamneni, P. Sahatiya, A water destructible SnS2 QD/PVA film based transient multifunctional sensor and machine learning assisted stimulus identification for non-invasive personal care diagnostics. Mater. Adv. 1(8), 2818–2830 (2020). https://doi.org/10.1039/d0ma00573h
  172. T. Kim, Y. Shin, K. Kang, K. Kim, G. Kim et al., Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces. Nat. Commun. (2022). https://doi.org/10.1038/s41467-022-33457-9
  173. Y. Long, P.S. He, R.X. Xu, T. Hayasaka, Z.C. Shao et al., Molybdenum-carbide-graphene composites for paper-based strain and acoustic pressure sensors. Carbon 157, 594–601 (2020). https://doi.org/10.1016/j.carbon.2019.10.083
  174. Y.H. Wang, T.Y. Tang, Y. Xu, Y.Z. Bai, L. Yin et al., All-weather, natural silent speech recognition via machine-learning-assisted tattoo-like electronics. Npj Flex. Electron. 5(1), 20 (2021). https://doi.org/10.1038/s41528-021-00119-7
  175. F. Wen, Z.D. Sun, T.Y.Y. He, Q.F. Shi, M.L. Zhu et al., Machine learning glove using self-powered conductive superhydrophobic triboelectric textile for gesture recognition in Vr/Ar applications. Adv. Sci. 7(14), 2000261 (2020). https://doi.org/10.1002/advs.202000261
  176. S. Oh, J.I. Cho, B.H. Lee, S. Seo, J.H. Lee et al., Flexible artificial Si–In–Zn–O/ion gel synapse and its application to sensory-neuromorphic system for sign language translation. Sci. Adv. 7(44), eabg9450 (2021). https://doi.org/10.1126/sciadv.abg9450
  177. K.K. Kim, I. Ha, M. Kim, J. Choi, P. Won et al., A deep-learned skin sensor decoding the epicentral human motions. Nat. Commun. 11, 2149 (2020). https://doi.org/10.1038/s41467-020-16040-y
  178. P.C. Tan, X. Han, Y. Zou, X.C. Qu, J.T. Xue et al., Self-powered gesture recognition wristband enabled by machine learning for full keyboard and multicommand input. Adv. Mater. 34(21), 2200793 (2022). https://doi.org/10.1002/adma.202200793
  179. T. Jin, Z.D. Sun, L. Li, Q. Zhang, M.L. Zhu et al., Triboelectric nanogenerator sensors for soft robotics aiming at digital twin applications. Nat. Commun. 11(1), 5381 (2020). https://doi.org/10.1038/s41467-020-19059-3
  180. G.Z. Li, S.Q. Liu, L.Q. Wang, R. Zhu, Skin-inspired quadruple tactile sensors integrated on a robot hand enable object recognition. Sci. Robot. 5(49), eabc8134 (2020). https://doi.org/10.1126/scirobotics.abc8134
  181. S. Chun, W. Son, H. Kim, S.K. Lim, C. Pang et al., Self-powered pressure- and vibration-sensitive tactile sensors for learning technique-based neural finger skin. Nano Lett. 19(5), 3305–3312 (2019). https://doi.org/10.1021/acs.nanolett.9b00922
  182. S. Chun, J.S. Kim, Y. Yoo, Y. Choi, S.J. Jung et al., An artificial neural tactile sensing system. Nat. Electron. 4(6), 429 (2021). https://doi.org/10.1038/s41928-021-00585-x
  183. G.H. Lee, J.K. Park, J. Byun, J.C. Yang, S.Y. Kwon et al., Parallel signal processing of a wireless pressure-sensing platform combined with machine-learning-based cognition, inspired by the human somatosensory system. Adv. Mater. 32(8), 1906269 (2020). https://doi.org/10.1002/adma.201906269
  184. K. Bae, J. Jeong, J. Choi, S. Pyo, J. Kim, Large-area, crosstalk-free, flexible tactile sensor matrix pixelated by mesh layers. ACS Appl. Mater. Interfaces 13(10), 12259–12267 (2021). https://doi.org/10.1021/acsami.0c21671
  185. K.S. Sohn, J. Chung, M.Y. Cho, S. Timilsina, W.B. Park et al., An extremely simple macroscale electronic skin realized by deep machine learning. Sci. Rep. 7, 11061 (2017). https://doi.org/10.1038/s41598-017-11663-6
  186. J.W. Lee, J. Chung, M.Y. Cho, S. Timilsina, K. Sohn et al., Deep-learning technique to convert a crude piezoresistive carbon nanotube-ecoflex composite sheet into a smart, portable, disposable, and extremely flexible keypad. ACS Appl. Mater. Interfaces 10(24), 20862–20868 (2018). https://doi.org/10.1021/acsami.8b04914
  187. Y.Y. Luo, Y.Z. Li, P. Sharma, W. Shou, K. Wu et al., Learning human-environment interactions using conformal tactile textiles. Nat. Electron. 4(3), 193 (2021). https://doi.org/10.1038/s41928-021-00558-0
  188. G. Loke, T. Khudiyev, B. Wang, S. Fu, S. Payra et al., Digital electronics in fibres enable fabric-based machine-learning inference. Nat. Commun. 12(1), 3317 (2021). https://doi.org/10.1038/s41467-021-23628-5
  189. H.J. Lee, J.C. Yang, J. Choi, J. Kim, G.S. Lee et al., Hetero-dimensional 2D Ti3C2Tx Mxene and 1D graphene nanoribbon hybrids for machine learning-assisted pressure sensors. ACS Nano 15(6), 10347–10356 (2021). https://doi.org/10.1021/acsnano.1c02567
  190. H. Qiu, M.K. Qiu, Z.H. Lu, Selective encryption on ecg data in body sensor network based on supervised machine learning. Inform. Fusion. 55, 59–67 (2020). https://doi.org/10.1016/j.inffus.2019.07.012
  191. H.C. Liu, W. Dong, Y.F. Li, F.Q. Li, J.J. Geng et al., An epidermal semg tattoo-like patch as a new human-machine interface for patients with loss of voice. Microsyst. Nanoeng. 6(1), 16 (2020). https://doi.org/10.1038/s41378-019-0127-5
  192. Y.X. Peng, J.X. Wang, K. Pang, W.M. Liu, J. Meng et al., A physiology-based flexible strap sensor for gesture recognition by sensing tendon deformation. IEEE Sens. J. 21(7), 9449–9456 (2021). https://doi.org/10.1109/sen.2021.3054562
  193. J.M. Pan, Y.D. Li, Y.X. Luo, X.Y. Zhang, X.H. Wang et al., Hybrid-flexible bimodal sensing wearable glove system for complex hand gesture recognition. ACS Sensors 6(11), 4156–4166 (2021). https://doi.org/10.1021/acssensors.1c01698
  194. J. Hughes, A. Spielberg, M. Chounlakone, G. Chang, W. Matusik et al., A simple, inexpensive, wearable glove with hybrid resistive-pressure sensors for computational sensing, proprioception, and task identification. Adv. Intell. Syst. Ger. 2(6), 2000002 (2020). https://doi.org/10.1002/aisy.202000002
  195. C.M. Oddo, M. Controzzi, L. Beccai, C. Cipriani, M.C. Carrozza, Roughness encoding for discrimination of surfaces in artificial active-touch. IEEE Trans. Robot. 27(3), 522–533 (2011). https://doi.org/10.1109/Tro.2011.2116930
  196. N. Jamali, C. Sammut, Majority voting: Material classification by tactile sensing using surface texture. IEEE Trans. Robot. 27(3), 508–521 (2011). https://doi.org/10.1109/Tro.2011.2127110
  197. J.A. Fishel, G.E. Loeb, Bayesian exploration for intelligent identification of textures. Front. Neurorobot. 6, 4 (2012). https://doi.org/10.3389/fnbot.2012.00004
  198. Z.K. Yi, Y.L. Zhang, J. Peters, Bioinspired tactile sensor for surface roughness discrimination. Sensor Actuat. A-Phys. 255, 46–53 (2017). https://doi.org/10.1016/j.sna.2016.12.021
  199. M. Jung, S.K. Vishwanath, J. Kim, D.K. Ko, M.J. Park et al., Transparent and flexible mayan-pyramid-based pressure sensor using facile-transferred indium tin oxide for bimodal sensor applications. Sci. Rep. 9, 14040 (2019). https://doi.org/10.1038/s41598-019-50247-4
  200. Y. Luo, X. Xiao, J. Chen, Q. Li, H.Y. Fu, Machine-learning-assisted recognition on bioinspired soft sensor arrays. ACS Nano 16(4), 6734–6743 (2022). https://doi.org/10.1021/acsnano.2c01548
  201. H. Chen, X. Yang, P. Wang, J. Geng, G. Ma et al., A large-area flexible tactile sensor for multi-touch and force detection using electrical impedance tomography. IEEE Sens. J. 22(7), 7119–7129 (2022). https://doi.org/10.1109/JSEN.2022.3155125
  202. W.Z. Heng, G.Y. Pang, F.H. Xu, X.Y. Huang, Z.B. Pang et al., Flexible insole sensors with stably connected electrodes for gait phase detection. Sensors 19(23), 5197 (2019). https://doi.org/10.3390/s19235197
  203. D. Kobsar, R. Ferber, Wearable sensor data to track subject-specific movement patterns related to clinical outcomes using a machine learning approach. Sensors 18(9), 2828 (2018). https://doi.org/10.3390/s18092828
  204. Y.W. Jiang, A. Sadeqi, E.L. Miller, S. Sonkusale, Head motion classification using thread-based sensor and machine learning algorithm. Sci. Rep. 11(1), 2646 (2021). https://doi.org/10.1038/s41598-021-81284-7
  205. Q.S. Hu, X.C. Tang, W. Tang, A smart chair sitting posture recognition system using flex sensors and fpga implemented artificial neural network. IEEE Sens. J. 20(14), 8007–8016 (2020). https://doi.org/10.1109/Jsen.2020.2980207
  206. J. Meyer, B. Arnrich, J. Schumm, G. Troster, Design and modeling of a textile pressure sensor for sitting posture classification. IEEE Sens. J. 10(8), 1391–1398 (2010). https://doi.org/10.1109/Jsen.2009.2037330
  207. C.C. Ma, W.F. Li, R. Gravina, G. Fortino, Posture detection based on smart cushion for wheelchair users. Sensors 17(4), 719 (2017). https://doi.org/10.3390/s17040719
  208. H.Z. Tan, L.A. Slivovsky, A. Pentland, A sensing chair using pressure distribution sensors. IEEE-ASME Trans. Mech. 6(3), 261–268 (2001). https://doi.org/10.1109/3516.951364
  209. K. Bourahmoune, T. Amagasa, Ai-powered posture training: Application of machine learning in sitting posture recognition using the lifechair smart cushion. J ASME Trans Mech (2019). https://doi.org/10.24963/ijcai.2019/805
  210. C. Ma, G. Li, L.H. Qin, W.C. Huang, H.R. Zhang et al., Analytical model of micropyramidal capacitive pressure sensors and machine-learning-assisted design. Adv. Mater. Technol. 6(12), 2100634 (2021). https://doi.org/10.1002/admt.202100634
  211. Z. Wang, Z. Sun, H. Yin, X. Liu, J. Wang et al., Data-driven materials innovation and applications. Adv. Mater. 34(36), 2104113 (2022). https://doi.org/10.1002/adma.202104113
  212. M.Y. Zhang, J. Li, L. Kang, N. Zhang, C. Huang et al., Machine learning-guided design and development of multifunctional flexible ag/poly (amic acid) composites using the differential evolution algorithm. Nanoscale 12(6), 3988–3996 (2020). https://doi.org/10.1039/C9NR09146G
  213. J. Cao, X.X. Zhang, Modulating the percolation network of polymer nanocomposites for flexible sensors. J. Appl. Phys. 128(22), 220901 (2020). https://doi.org/10.1063/5.0033652
  214. Z. Ballard, C. Brown, A.M. Madni, A. Ozcan, Machine learning and computation-enabled intelligent sensor design. Nat. Mach. Intell. 3(7), 556–565 (2021). https://doi.org/10.1038/s42256-021-00360-9
  215. N. Yi, Y.Y. Gao, A. Lo Verso, J. Zhu, D. Erdely et al., Fabricating functional circuits on 3d freeform surfaces via intense pulsed light-induced zinc mass transfer. Mater. Today. 50, 24–34 (2021). https://doi.org/10.1016/j.mattod.2021.07.002
  216. S.H. Zhang, J. Zhu, Y.Y. Zhang, Z.S. Chen, C.Y. Song et al., Standalone stretchable rf systems based on asymmetric 3d microstrip antennas with on-body wireless communication and energy harvesting. Nano Energy 96, 107069 (2022). https://doi.org/10.1016/j.nanoen.2022.107069
  217. L. Yang, C. Liu, W. Yuan, C. Meng, A. Dutta et al., Fully stretchable, porous mxene-graphene foam nanocomposites for energy harvesting and self-powered sensing. Nano Energy 103, 107807 (2022). https://doi.org/10.1016/j.nanoen.2022.107807
  218. J. Zhu, Z.H. Hu, S.H. Zhang, X.Z. Zhang, H.L. Zhou et al., Stretchable 3d wideband dipole antennas from mechanical assembly for on-body communication. ACS Appl. Mater. Interfaces 14(10), 12855–12862 (2022). https://doi.org/10.1021/acsami.1c24651
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