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Artificial Hair-Like Sensors Inspired from Nature: A Review

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Abstract

Nature creatures have evolved excellent receptors, such as sensory hairs in arthropods, lateral line system of fishes. Researchers inspired by nature creatures have developed various mechanical sensors. Here, we provide an overview on the development of Artificial Hair-Like (AHL) sensors based on the inspiration of hair flow sensory receptors, especially sensory hairs in arthropods and lateral line systems of fishes. We classify the developed AHL sensors into several categories according to the operating principles they based on, for example, piezoresistive and piezoelectric effects. The current challenges and existing problems in the development of AHL sensors are also present, which were primarily restricted by the exploratory tools of sensing mechanism of creatures and current manufacturing technologies. In future, more efforts are required in order to further improve the performance of AHL sensors. We expect that intelligent multi-functional AHL sensors can be applied not only in applications like navigation of underwater automatic vehicles, underwater search and rescue, tap-water metering, air monitoring and even in medicare, but also potentially be used in space robots to detect complex topography.

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References

  1. Mukherjee T, Bhattacharyya T K. A miniature, high sensitivity, surface micro-machined displacement sensor with high resolution. International Conference on Advanced Intelligent Mechatronics, Kachsiung, Taiwan, 2012, 737–742.

    Google Scholar 

  2. Elmi I, Zampolli S, Cozzani E, Mancarella F, Cardinali G C. Development of ultra-low-power consumption MOX sensors with ppb-level VOC detection capabilities for emerging applications. Sensors and Actuators B: Chemical, 2008, 135, 342–351.

    Article  Google Scholar 

  3. Dijkstra M, Boer D M, Berenschot J W, Lammerink T S, Wiegerink R J, Elwenspoek M. Miniaturized thermal flow sensor with planar-integrated sensor structures on semicircular surface channels. Sensors and Actuators A: Physical, 2008, 143, 1–6.

    Article  Google Scholar 

  4. Kroetz G H, Eickhoff M H, Moeller H. Silicon compatible materials for harsh environment sensors. Sensors and Actuators A: Physical, 1999, 74, 182–189.

    Article  Google Scholar 

  5. Budelmann B U. Hydrodynamic Receptor Systems in Invertebrates, Springer Verlag, USA, 1989, 607–631.

    Google Scholar 

  6. Bleckmann H. Reception of hydrodynamic stimuli in aquatic and semiaquatic animals. Progress in Zoology, 1994, 44, 115.

    Google Scholar 

  7. Sane S P, McHenry M J. The biomechanics of sensory organs. Integrative and Comparative Biology, 2009, 49, 8–23.

    Article  Google Scholar 

  8. Tao J, Yu X. Hair flow sensors: From bio-inspiration to bio-mimicking–A review. Smart Materials and Structures, 2012, 21, 113001.

    Article  Google Scholar 

  9. Liu G, Wang A, Wang X, Liu P. A review of artificial lateral line in sensor fabrication and bionic applications for robot fish. Applied Bionics and Biomechanics, 2016, 2016, 4732703.

    Google Scholar 

  10. Casas J, Dangles O. Physical ecology of fluid flow sensing in arthropods. Annual Review of Entomology, 2010, 55, 505–520.

    Article  Google Scholar 

  11. Tauber E, Camhi J. The wind-evoked escape behavior of the cricket Gryllus bimaculatus: Integration of behavioral elements. The Journal of Experimental Biology, 1995, 198, 1895–1907.

    Google Scholar 

  12. Reissland A, Görner P. Trichobothria. In: Barth F G, eds., Neurobiology of Arachnids, Springer Berlin Heidelberg, Germany, 1985, 138–161.

    Chapter  Google Scholar 

  13. Hoffmann C. Bau und funktion der trichobothrien von euscorpius carpathicus. Zeitschrift Für Vergleichende Physiologie, 1967, 54, 290–352.

    Article  Google Scholar 

  14. Joshi K, Mian A, Mliier J. Model development and analysis of a cricket filiform hair socket under low velocity air currents. Proceedings of ASME International Mechanical Engineering Congress and Exposition, Texas, USA, 2012, 19–24.

    Google Scholar 

  15. Palka J, Olberg R. The cercus-to-giant interneuron system of crickets. Journal of Comparative Physiology, 1977, 119, 301–317.

    Article  Google Scholar 

  16. Shimozawa T, Kanou M. Varieties of filiform hairs: Range fractionation by sensory afferents and cereal interneurons of a cricket. Journal of Comparative Physiology A, 1984, 155, 485–493.

    Article  Google Scholar 

  17. Shimozawa T, Kumagai T, Baba Y. Structural scaling and functional design of the cercal wind-receptor hairs of cricket. Journal of Comparative Physiology A, 1998, 183, 171–186.

    Article  Google Scholar 

  18. McConney M E, Schaber C F, Julian M D, Eberhardt W C, Humphrey J A C, Barth F G, Tsukruk V V. Surface force spectroscopic point load measurements and viscoelastic modelling of the micromechanical properties of air flow sensitive hairs of a spider (Cupiennius salei). Journal of the Royal Society Interface, 2009, 6, 681–694.

    Article  Google Scholar 

  19. Barth F G. Spider senses–technical perfection and biology. Zoology, 2002, 105, 271–285.

    Article  Google Scholar 

  20. Barth F G. How to catch the wind: Spider hairs specialized for sensing the movement of air. Naturwissenschaften, 2000, 87, 51–58.

    Article  Google Scholar 

  21. Barth F G, Wastl U, Humphrey J A C, Devarakonda R. Dynamics of arthropod filiform hairs. II. Mechanical properties of spider trichobothria (Cupiennius salei Keys.). Philosophical Transactions of the Royal Society B, 1993, 340, 445–461.

    Google Scholar 

  22. Humphrey J A C, Barth F G. Medium flow-sensing hairs: Biomechanics and models. Advances in Insect Physiology, 2007, 34, 1–80.

    Article  Google Scholar 

  23. Devarakonda R, Barth F G, Humphrey J A C. Dynamics of arthropod filiform hairs. IV. Hair motion in air and water. Philosophical Transactions: Biological Sciences, 1996, 351, 933–946.

    Google Scholar 

  24. Barth F G. Spider mechanoreceptors. Current Opinion in Neurobiology, 2004, 14, 415–422.

    Article  Google Scholar 

  25. Shimozawa T, Kanou M. The aerodynamics and sensory physiology of range fractionation in the cereal filiform sensilla of the cricket Gryllus bimaculatus. Journal of Comparative Physiology A, 1984, 155, 495–505.

    Article  Google Scholar 

  26. Humphrey J A C, Devarakonda R, Iglesias I, Barth F G. Dynamics of arthropod filiform hairs. I. Mathematical modelling of the hair and air motions. Philosophical Transactions: Biological Sciences, 1993, 340, 423–444.

    Google Scholar 

  27. Humphrey J A C, Barth F G, Voss K. The Motion-Sensing Hairs of Arthropods: Using Physics to Understand Sensory Ecology and Adaptive Evolution, Springer Berlin Heidelberg, Berlin, Germany, 2001, 105–125.

    Google Scholar 

  28. Fletcher N H. Acoustical response of hair receptors in insects. Journal of Comparative Physiology A, 1978, 127, 185–189.

    Article  Google Scholar 

  29. Tautz J. Reception of particle oscillation in a medium—An unorthodox sensory capacity. Naturwissenschaften, 1979, 66, 452–461.

    Article  Google Scholar 

  30. Shimozawa T, Murakami J, Kumagai T. Cricket Wind Receptors: Thermal Noise for the Highest Sensitivity Known, Springer Vienna, Vienna, Austria, 2003, 145–157.

    Google Scholar 

  31. Shimozawa T, Murakami J, Kumagai T. Cricket wind receptor cell detects mechanical energy of the level of kT of thermal fluctuation. Proceedings of the 5th International Congress of Neuroethology, San Diego, USA, 1998.

    Google Scholar 

  32. Ko H, Song H, Im S, Kim H. Bioinspired piezoresistive acceleration sensor using artificial filiform sensillum structure. Sensors and Materials, 2015, 27, 437–445.

    Google Scholar 

  33. Maschmann M R, Ehlert G J, Dickinson B T, Phillips D M, Ray C W, Reich G W, Baur J W. Bioinspired carbon nanotube fuzzy fiber hair sensor for air-flow detection. Advanced Materials, 2014, 26, 3230–3234.

    Article  Google Scholar 

  34. Shi X M, Cheng C H. Artificial hair cell sensors using liquid metal alloy as piezoresistors. Proceedings of the 8th IEEE International Conference on Nano/Micro Engineered and Molecular Systems (NEMS), Suzhou, China, 2013, 978–981.

    Chapter  Google Scholar 

  35. Ehlert G J, Maschmann M R, Baur J W. Electromechanical behavior of aligned carbon nanotube arrays for bio-inspired fluid flow sensors. Proceedings of SPIE Active and Passive Smart Structures and Integrated Systems, San Diego, California, USA, 2011, 7977, 79771.

    Google Scholar 

  36. Suhr J, Victor P, Ci L, Sreekala S, Zhang X, Nalamasu O, Ajayan P M. Fatigue resistance of aligned carbon nanotube arrays under cyclic compression. Nature Nanotechnology, 2007, 2, 417–421.

    Article  Google Scholar 

  37. Slinker K, Maschmann M R, Kondash C, Severin B, Phillips D, Dickinson B T, Reich G, Baur J W. Variable deflection response of sensitive CNT-on-fiber artificial hair sensors from CNT synthesis in high aspect ratio microcavities. Proceedings of SPIE Bioinspiration, Biomimetics, and Bioreplication, San Diego, California, USA, 2015, 9429, 942917C.

    Google Scholar 

  38. Han J, Kim D, Yun K. All-polymer hair structure with embedded three-dimensional piezoresistive force sensors. Sensors & Actuators A: Physical, 2012, 188, 89–94.

    Article  Google Scholar 

  39. Bian Y, Qiu J, Wang X, Ji H, Zhu K. The constitutive equations of half coated metal core piezoelectric fiber. International Journal of Applied Electromagnetics and Mechanics, 2009, 29, 47–64.

    Google Scholar 

  40. Bian Y, Liu R, Hui S. Fabrication of a polyvinylidene difluoride fiber with a metal core and its application as directional air flow sensor. Functional Materials Letters, 2016, 9, 1650001.

    Article  Google Scholar 

  41. Bian Y, Zhang Y, Xia X. Design and fabrication of a multi- electrode metal-core piezoelectric fiber and its application as an airflow sensor. Journal of Bionic Engineering, 2016, 13, 416–425.

    Article  Google Scholar 

  42. Askari D, Asanuma H, Ghasemi-Nejhad M N. A comparative study on macrofiber composites and active fiber composites with metal-core piezoelectric actuators/sensors. Proceedings of SPIE Smart Structures and Materials, San Diego, California, USA, 2006, 61701I.

    Google Scholar 

  43. Droogendijk H. Improving the performance of biomimetic hair-flow sensors by electrostatic spring. Journal of Micromechanics and Microengineering, 2012, 22, 065026.

    Article  Google Scholar 

  44. Droogendijk H, Bruinink C M, Sanders R G P, Krijnen G J M. Tunable sensor response by voltage-control in biomimetic hair flow sensors. Micromachines, 2013, 4, 116–127.

    Article  Google Scholar 

  45. Droogendijk H, De Boer M J, Sanders R G P, Krijnen G J M. Advantages of electrostatic spring hardening in biomimetic hair flow sensors. Journal of Microelectromechanical Systems, 2015, 24, 1415–1425.

    Article  Google Scholar 

  46. Dagamseh A M K. Estimation of squeeze film damping in artificial hair-sensor towards the detection-limit of crickets’ hairs. Microsystem Technologies, 2014, 20, 963–970.

    Article  Google Scholar 

  47. Droogendijk H, De Boer M J, Sanders R G P, Krijnen G J M. A biomimetic accelerometer inspired by the cricket’s clavate hair. Journal of the Royal Society Interface, 2014, 11, 20140438.

    Article  Google Scholar 

  48. Droogendijk H, De Boer M J, Sanders R G P, Krijnen G J M. Bio-inspired hair-based inertial sensors. Biomimetic Technologies, 2015, 27, 93–119.

    Article  Google Scholar 

  49. Alfadhel A, Li B, Zaher A, Yassine O, Kosel J. A magnetic nanocomposite for biomimetic flow sensing. Lab on a Chip, 2014, 14, 4362–4369.

    Article  Google Scholar 

  50. Alfadhel A, Khan M A, Cardoso S, Leitao D, Kosel J. A magnetoresistive tactile sensor for harsh environment applications. Sensors, 2016, 16, 650.

    Article  Google Scholar 

  51. Alfadhel A, Kosel J. Magnetic micropillar sensors for force sensing. Proceedings of the IEEE Sensors Applications Symposium (SAS), Zadar, Croatia, 2015, 1–4.

    Google Scholar 

  52. Alfadhel A, Kosel J. Magnetic nanocomposite cilia tactile sensor. Advanced Materials, 2015, 27, 7888–7892.

    Article  Google Scholar 

  53. Ripka P, Janosek M. Advances in magnetic field sensors. IEEE Sensors Journal, 2010, 10, 1108–1116.

    Article  Google Scholar 

  54. Kurlyandskaya G V, Sanchez M L, Hernando B, Prida V M, Gorria P, Tejedor M. Giant-magnetoimpedance-based sensitive element as a model for biosensors. Applied Physics Letters, 2003, 82, 3053–3055.

    Article  Google Scholar 

  55. Panina L V, Mohri K. Magneto-impedance in multilayer films. Sensors and Actuators A: Physical, 2000, 81, 71–77.

    Article  Google Scholar 

  56. Phan M H, Peng H X. Giant magnetoimpedance materials: Fundamentals and applications. Progress in Materials Science, 2008, 53, 323–420.

    Article  Google Scholar 

  57. Hirota E, Sakakima H, Inomata K. Giant Magnetoresistance Devices, Springer-Verlag, Berlin, Germany, 2002, 40.

    Book  Google Scholar 

  58. Mogdans J, Bleckmann H. Coping with flow: Behavior, neurophysiology and modeling of the fish lateral line system. Biological Cybernetics, 2012, 106, 627–642.

    Article  Google Scholar 

  59. Maruska K P. Morphology of the mechanosensory lateral line system in elasmobranch fishes: Ecological and behavioral considerations. Environmental Biology of Fishes, 2001, 60, 47–75.

    Article  Google Scholar 

  60. Pahker G. The function of the lateral-line organs in fishes. Bull US Bureau Fish, 1904, 24, 185–207.

    Google Scholar 

  61. Hofer B. Studien über die Hautsinnesorgane der Fische I. Die Funktion Der Seitenorgane Bei Den Fischen. Ber Kgl Bayer Biol Versuchsstation München, 1908, 1, 115–168.

    Google Scholar 

  62. Summary V. Structure and development of the sense organs of the lateral canal system of selachians (Mustelus canis and Squalus acanthias). Journal of Comparative Neurology, 1917, 28, 1–74.

    Article  Google Scholar 

  63. Stone L S. Experiments on the development of the cranial ganglia and the lateral line sense organs in Amblystoma punctatum. Journal of Experimental Zoology, 1922, 35, 420–496.

    Article  Google Scholar 

  64. Landacre F L. The differentiation of the preauditory and postauditory primitive lines into preauditory and postauditory placodes, lateralis ganglia and migratory lateral-line placodes in Amblystoma jeffersonianum. Journal of Comparative Neurology, 1927, 44, 29–59.

    Article  Google Scholar 

  65. Sato A. Electron microscopic study of the developing lateral line organs in the embryo of Triturus pyrrhogaster. The Anatomical Record, 1976, 186, 565–583.

    Article  Google Scholar 

  66. Jiang Y, Fu J, Zhang D, Zhao Y. Investigation on the lateral line systems of two cavefish: Sinocyclocheilus Macrophthalmus and S. Microphthalmus (Cypriniformes: Cyprinidae). Journal of Bionic Engineering, 2016, 13, 108–114.

    Google Scholar 

  67. Liao J C. A review of fish swimming mechanics and behaviour in altered flows. Philosophical Transactions of the Royal Society B: Biological Sciences, 2007, 362, 1973–1993.

    Article  Google Scholar 

  68. Przybilla A, Kunze S, Rudert A, Bleckmann H, Brücker C. Entraining in trout: A behavioural and hydrodynamic analysis. Journal of Experimental Biology, 2010, 213, 2976–2986.

    Article  Google Scholar 

  69. Klein A, Bleckmann H. Function of lateral line canal morphology. Integrative Zoology, 2015, 10, 111–121.

    Article  Google Scholar 

  70. Northcutt R G. The Phylogenetic Distribution and Innervation of Craniate Mechanoreceptive Lateral Lines, Springer- verlag, New York, USA, 1989, 17–78.

    Google Scholar 

  71. Coombs S, Montgomery J C. The Enigmatic Lateral Line System. In: Fay R R, Popper A N eds, Comparative hearing: Fish and amphibians, Springer-Verlag, New York, USA, 1999, 319–362.

    Chapter  Google Scholar 

  72. Coombs S, Janssen J, Webb J F. Diversity of Lateral Line Systems: Evolutionary and Functional Considerations. In: Atema J, Fay R R, Popper A N, Tavolga W N eds, Sensory biology of aquatic animals, Springer-Verlag, New York, USA, 1988, 553–593.

    Chapter  Google Scholar 

  73. Bleckmann H. The lateral line system of fish. Integrative Zoology, 2009, 4, 13–25.

    Article  Google Scholar 

  74. Cichlidae N L. Morphology and innervation of the lateral line system. Zoomorphologie, 1979, 93, 73–86.

    Article  Google Scholar 

  75. Munz H. Functional Organization of the Lateral Line Periphery. In: Coombs S, Görner P, Münz H eds, The mechanosensory lateral line: Neurobiology and evolution, Springer-Verlag, New York, USA, 1989, 285–297.

    Chapter  Google Scholar 

  76. Northcutt R G, Bleckmann H. Pit organs in axolotls: A second class of lateral line neuromasts. Journal of Comparative Physiology A, 1993, 172, 439–446.

    Article  Google Scholar 

  77. Coombs S. Smart skins: Information processing by lateral line flow sensors. Autonomous Robots, 2001, 11, 255–261.

    Article  MATH  Google Scholar 

  78. Montgomery J, Carton G, Voigt R, Baker C, Diebel C. Sensory processing of water currents by fishes. Philosophical Transactions of the Royal Society B: Biological Sciences, 2000, 355, 1325–1327.

    Article  Google Scholar 

  79. Van Netten S M, Kroese A B A. Laser interferometric measurements on the dynamic behaviour of the cupula in the fish lateral line. Hearing Research, 1987, 29, 55–61.

    Article  Google Scholar 

  80. van Netten S M. Hydrodynamics of the excitation of the cupula in the fish canal lateral line. The Journal of the Acoustical Society of America, 1991, 89, 310–319.

    Article  Google Scholar 

  81. Van Netten S M. Hydrodynamic detection by cupulae in a lateral line canal: Functional relations between physics and physiology. Biological Cybernetics, 2006, 94, 67–85.

    Article  MATH  Google Scholar 

  82. McHenry M J, Strother J A, Van Netten S M. Mechanical filtering by the boundary layer and fluid–structure interaction in the superficial neuromast of the fish lateral line system. Journal of Comparative Physiology A, 2008, 194, 795–810.

    Article  Google Scholar 

  83. Volkova T, Zeidis I, Witte H, Schmidt M, Zimmermann K. Analysis of the vibrissa parametric resonance causing a signal amplification during whisking behaviour. Journal of Bionic Engineering, 2016, 13, 312–323.

    Article  Google Scholar 

  84. Stokes G G. On the effect of the internal friction of fluids on the motion of pendulums. Transactions of the Cambridge Philosophical Society, 1851, 9, 8.

    Google Scholar 

  85. Harris G G, van Bergeijk W A. Evidence that the lateral-line organ responds to near-field displacements of sound sources in water. The Journal of the Acoustical Society of America, 1962, 34, 1831–1841.

    Article  Google Scholar 

  86. Kalmijn A J. Hydrodynamic and acoustic field detection. In: Atema J, Fay R R, Popper A N, Tavolga W N, eds, Sensory Biology of Aquatic Animals, Springer-Verlag, New York, USA, 1988, 83–130.

    Chapter  Google Scholar 

  87. Zhou H, Hu T, Low K H, Shen L, Ma Z, Wang G, Xu H. Bio-inspired flow sensing and prediction for fish-like un dulating locomotion: A CFD-aided approach. Journal of Bionic Engineering, 2015, 12, 406–417.

    Article  Google Scholar 

  88. Sexl V T. Über den von EG Richardson entdeckten Annulareffekt. European Physical Journal, 1930, 61, 349–362.

    MATH  Google Scholar 

  89. Denton E J, Gray J A B. The rigidity of fish and patterns of lateral line stimulation. Nature, 1982, 297, 679–681.

    Article  Google Scholar 

  90. Denton E J, Gray J. Mechanical factors in the excitation of clupeid lateral lines. Proceedings of the Royal Society B: Biological Sciences, 1983, 218, 1–26.

    Article  Google Scholar 

  91. Windsor S P, McHenry M J. The influence of viscous hydrodynamics on the fishlateral-line system. Integrative and Comparative Biology, 2009, 49, 691–701.

    Article  Google Scholar 

  92. Nawi M N, Manaf A A, Arshad M R, Sidek O. Development of biomimetic flow sensor based on artificial lateral line flow sensor for underwater applications. Indian Journal of Geo-Marine Sciences, 2012, 41, 527–532.

    Google Scholar 

  93. Qualtieri A, Rizzi F, Todaro M T, Passaseo A, Cingolani R, De Vittorio M. Stress-driven AlN cantilever-based flow sensor for fish lateral line system. Microelectronic Engineering, 2011, 88, 2376–2378.

    Article  Google Scholar 

  94. Qualtieri A, Rizzi F, Epifani G, Ernits A, Kruusmaa M, De Vittorio M. Parylene-coated bioinspired artificial hair cell for liquid flow sensing. Microelectronic Engineering, 2012, 98, 516–519.

    Article  Google Scholar 

  95. Rizzi F, Qualtieri A, Chambers L D, Megill W M, De Vittorio M. Parylene conformal coating encapsulation as a method for advanced tuning of mechanical properties of an artificial hair cell. Soft Matter, 2013, 9, 2584–2588.

    Article  Google Scholar 

  96. Akanyeti O, Venturelli R, Visentin F. A bio-inspired real- time capable artificial lateral line system for freestream flow measurements. Bioinspiration & Biomimetics, 2016, 11, 35006.

    Article  Google Scholar 

  97. Rizzi F, Qualtieri A, Dattoma T, Epifani G, De Vittorio M. Biomimetics of underwater hair cell sensing. Microelectronic Engineering, 2015, 132, 90–97.

    Article  Google Scholar 

  98. Kottapalli A G P, Asadnia M, Miao J M, Barbastathis G, Triantafyllou M S. A flexible liquid crystal polymer MEMS pressure sensor array for fish-like underwater sensing. Smart Materials and Structures, 2012, 21, 115030.

    Article  Google Scholar 

  99. Kottapalli A G P, Bora M, Asadnia M, Miao J M, Venkatraman S S, Triantafyllou M S. Nanofibril scaffold assisted MEMS artificial hydrogel neuromasts for enhanced sensitivity flow sensing. Scientific Reports, 2016, 6, 19336.

    Article  Google Scholar 

  100. Yaul F M, Bulovic V, Lang J H. A flexible underwater pressure sensor array using a conductive elastomer strain gauge. Journal of Microelectromechanical Systems, 2012, 21, 897–907.

    Article  Google Scholar 

  101. Abdulsadda A T, Tan X. An artificial lateral line system using IPMC sensor arrays. International Journal of Smart and Nano Materials, 2012, 3, 226–242.

    Article  Google Scholar 

  102. Asadnia M, Kottapalli A G P, Shen Z, Miao J M, Triantafyllou M S. Flexible and surface-mountable piezoelectric sensor arrays for underwater sensing in marine vehicles. IEEE Sensors Journal, 2013, 13, 3918–3925.

    Article  Google Scholar 

  103. Asadnia M, Kottapalli A G P, Miao J M, Warkiani M E, Triantafyllou M S. Artificial fish skin of self-powered micro-electromechanical systems hair cells for sensing hydrodynamic flow phenomena. Journal of the Royal Society Interface, 2015, 12, 20150322.

    Article  Google Scholar 

  104. Kottapalli A G P, Asadnia M, Miao J M, Triantafyllou M S. Touch at a distance sensing: Lateral-line inspired MEMS flow sensors. Bioinspiration & Biomimetics, 2014, 9, 46011.

    Article  Google Scholar 

  105. Fu J, Jiang Y, Zhang D. PVDF based artificial canal lateral line for underwater detection. IEEE Sensors, Busan, South Korea, 2015.

    Google Scholar 

  106. Dagamseh A, Wiegerink R, Lammerink T, Krijnen G. Imaging dipole flow sources using an artificial lateral-line system made of biomimetic hair flow sensors. Journal of the Royal Society Interface, 2013, 10, 20130162.

    Article  Google Scholar 

  107. Dagamseh A M K, Wiegerink R J, Lammerink T S J, Krijnen G J M. Towards a high-resolution flow camera using artificial hair sensor arrays for flow pattern observations. Bioinspiration & Biomimetics, 2012, 7, 46009.

    Article  Google Scholar 

  108. Herzog H, Steltenkamp S, Klein A, Tätzner S, Schulze E, Bleckmann H. Micro-machined flow sensors mimicking lateral line canal neuromasts. Micromachines, 2015, 6, 1189–1212.

    Article  Google Scholar 

  109. Herzog H, Klein A, Bleckmann H, Holik P, Schmitz S, Siebke G, Tätzner S, Lacher M, Steltenkamp S. µ-biomimetic flow-sensors — Introducing light-guiding PDMS structures into MEMS. Bioinspiration & Biomimetics, 2015, 10, 036001.

    Article  Google Scholar 

  110. Abdulsadda A T, Tan X. Localization of a moving dipole source underwater using an artificial lateral line. Proceedings of SPIE Smart Structures and Materials, San Diego, California, USA, 2012, 833909.

    Google Scholar 

  111. Abdulsadda A T, Tan X. Underwater tracking of a moving dipole source using an artificial lateral line: Algorithm and experimental validation with ionic polymer–metal composite flow sensors. Smart Materials and Structures, 2013, 22, 45010.

    Article  Google Scholar 

  112. Abdulsadda A T, Tan X. Nonlinear estimation-based dipole source localization for artificial lateral line systems. Bioinspiration & Biomimetics, 2013, 8, 26005.

    Article  Google Scholar 

  113. Kottapalli A G P, Asadnia M, Miao J M, Triantafyllou M S. Biomechanical canal sensors inspired by canal neuromasts for ultrasensitive flow sensing. Proceedings of the IEEE International Conference on Micro Electro Mechanical System, Estoril, Portugal, 2015, 500–503.

    Google Scholar 

  114. Lipson H, Kurman M. Fabricated: The New World of 3D Printing, John Wiley & Sons, Indianapolis, USA, 2013.

    Google Scholar 

  115. Muth J T, Vogt D M, Truby R L, Mengüç Y, Kolesky D B, Wood R J, Lewis J A. Embedded 3D printing of strain sensors within highly stretchable elastomers. Advanced Materials, 2014, 26, 6307–6312.

    Article  Google Scholar 

  116. Singh G, Chan H, Baskin A, Gelman E, Repnin N, Král P, Klajn R. Self-assembly of magnetite nanocubes into helical superstructures. Science, 2014, 345, 1149–1153.

    Article  Google Scholar 

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Acknowledgments

This research was supported by the Natural Science Foundation of China (Nos. 51325501, 51675220 and 51205161), Natural Science Foundation of Jilin Province of China (No. 20170101115JC), the 13th Five-Year scientific research project of Education Department of Jilin Province (No. 2015474).

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Correspondence to Junqiu Zhang.

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Han, Z., Liu, L., Wang, K. et al. Artificial Hair-Like Sensors Inspired from Nature: A Review. J Bionic Eng 15, 409–434 (2018). https://doi.org/10.1007/s42235-018-0033-9

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