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Wearables, E-textiles, and Soft Robotics for Personalized Medicine

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Springer Handbook of Automation

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Abstract

The rapidly growing pressure on health systems created by the aging of population forces medicine to search for new approaches to expand the reach and improve the efficacy of healthcare. To alleviate this socio-economical problem, the ever-expanding field of electronics has generated a variety of wearable gadgets capable of monitoring the wearer during daily life activities. Due to their proximity with their user, wearables constitute a unique platform for the incorporation of sensors and actuators that can not only regularly check the health status of the wearer but assist them during recovery and rehabilitation. This chapter describes the efforts to create wearable biomedical devices capable to provide clinicians with the information necessary to elaborate precise and personalized medical attention to the patient. First, a technical foundation for design and development of wearables, smart textiles, and soft robots capable of democratizing access to personalized medicine will be provided. Next, a description of how the Internet of Things and big data analytics expands the capabilities of these wearable devices will be provided. Finally, current challenges and emerging trends to automate patient care and enhance medical attention using wearables will be analyzed.

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References

  1. Abul-Husn, N.S., Kenny, E.E.: Personalized medicine and the power of electronic health records. Cell 177(1), 58–69 (2019)

    Google Scholar 

  2. Ometov, A., Shubina, V., Klus, L., Skibińska, J., Saafi, S., Pascacio, P., Flueratoru, L., Gaibor, D.Q., Chukhno, N., Chukhno, O., et al.: A survey on wearable technology: history, state-of-the-art and current challenges. Comput. Netw. 193, 108074 (2021)

    Google Scholar 

  3. Aguado, B.A., Grim, J.C., Rosales, A.M., Watson-Capps, J.J., Anseth, K.S.: Engineering precision biomaterials for personalized medicine. Sci. Transl. Med. 10(424) (2018)

    Google Scholar 

  4. Piwek, L., Ellis, D.A., Andrews, S., Joinson, A.: The rise of consumer health wearables: promises and barriers. PLoS Med. 13(2), e1001953 (2016)

    Google Scholar 

  5. Pal, A., Goswami, D., Cuellar, H.E., Castro, B., Kuang, S., Martinez, R.V.: Early detection and monitoring of chronic wounds using low-cost, omniphobic paper-based smart bandages. Biosens. Bioelectron. 117, 696–705 (2018)

    Google Scholar 

  6. Ismar, E., Bahadir, S.K., Kalaoglu, F., Koncar, V.: Futuristic clothes: electronic textiles and wearable technologies. Global Chall. 4(7), 1900092 (2020)

    Google Scholar 

  7. Tse, Z.T.H., Chen, Y., Hovet, S., Ren, H., Cleary, K., Xu, S., Wood, B., Monfaredi, R.: Soft robotics in medical applications. J. Med. Robot. Res. 3(03n04), 1841006 (2018)

    Google Scholar 

  8. Koydemir, H.C., Ozcan, A.: Wearable and implantable sensors for biomedical applications. Ann. Rev. Anal. Chem. 11, 127–146 (2018)

    Google Scholar 

  9. Guk, K., Han, G., Lim, J., Jeong, K., Kang, T., Lim, E.-K., Jung, J.: Evolution of wearable devices with real-time disease monitoring for personalized healthcare. Nanomaterials 9(6), 813 (2019)

    Google Scholar 

  10. Hasan, N.U.M., Negulescu, I.I.: Wearable technology for baby monitoring: a review. J. Text. Eng. Fash. Technol. 6(112.10), 15406 (2020)

    Google Scholar 

  11. Qureshi, F., Krishnan, S.: Wearable hardware design for the internet of medical things (IoMT). Sensors 18(11), 3812 (2018)

    Google Scholar 

  12. Yetisen, A.K., Martinez-Hurtado, J.L., Ünal, B., Khademhosseini, A., Butt, H.: Wearables in medicine. Adv. Mater. 30(33), 1706910 (2018)

    Google Scholar 

  13. Niknejad, N., Ismail, W.B., Mardani, A., Liao, H., Ghani, I.: A comprehensive overview of smart wearables: the state of the art literature, recent advances, and future challenges. Eng. Appl. Artif. Intell. 90, 103529 (2020)

    Google Scholar 

  14. Seibold, A., Alva, S., Feuchter, L., Lazarus, M., Liu, H., Nada, M.: Performance of freestyle libre® 2 system in adult and pediatric populations. Diabetologie und Stoffwechsel 14(S 01), P–178 (2019)

    Google Scholar 

  15. Seshadri, D.R., Bittel, B., Browsky, D., Houghtaling, P., Drummond, C.K., Desai, M.Y., Gillinov, A.M.: Accuracy of apple watch for detection of atrial fibrillation. Circulation 141(8), 702–703 (2020)

    Google Scholar 

  16. Ray, P.P., Dash, D., Kumar, N.: Sensors for internet of medical things: state-of-the-art, security and privacy issues, challenges and future directions. Comput. Commun. 160, 111–131 (2020)

    Google Scholar 

  17. de Zambotti, M., Goldstone, A., Claudatos, S., Colrain, I.M., Baker, F.C.: A validation study of fitbit charge 2™compared with polysomnography in adults. Chronobiol. Int. 35(4), 465–476 (2018)

    Google Scholar 

  18. Bolourchi, M., Silver, E.S., Muwanga, D., Mendez, E., Liberman, L.: Comparison of holter with zio patch electrocardiography monitoring in children. Am. J. Cardiol. 125(5), 767–771 (2020)

    Google Scholar 

  19. Herman, A., Baeck, M., de Montjoye, L., Bruze, M., Giertz, E., Goossens, A., Mowitz, M.: Allergic contact dermatitis caused by isobornyl acrylate in the enlite glucose sensor and the paradigm minimed quick-set insulin infusion set. Contact Dermatitis 81(6), 432–437 (2019)

    Google Scholar 

  20. Weizman, Y., Tan, A.M., Fuss, F.K.: Benchmarking study of the forces and centre of pressure derived from a novel smart-insole against an existing pressure measuring insole and force plate. Measurement 142, 48–59 (2019)

    Google Scholar 

  21. Areia, C., Young, L., Vollam, S., Ede, J., Santos, M., Tarassenko, L., Watkinson, P.: Wearability testing of ambulatory vital sign monitoring devices: prospective observational cohort study. JMIR Mhealth Uhealth 8(12), e20214 (2020)

    Google Scholar 

  22. Askari, R., Keriakos, N., Jha, S.K., Khouzam, R.: Quinine syncope diagnosed by life vest. Clin. Exp. Pharmacol. 5(172), 2 (2015)

    Google Scholar 

  23. Kim, D.-H., Lu, N., Ma, R., Kim, Y.-S., Kim, R.-H., Wang, S., Wu, J., Won, S.M., Tao, H., Islam, A., You, K.J., Kim, T.I., Chowdhury, R., Ying, M., Xu, L., Li, M., Chung, H.J., Keum, H., McCormick, M., Liu, P., Zhang, Y.W., Omenetto, F.G., Huang, Y., Coleman, T., Rogers, J.A.: Epidermal electronics. Science 333(6044), 838–843 (2011)

    Google Scholar 

  24. Dagdeviren, C., Shi, Y., Joe, P., Ghaffari, R., Balooch, G., Usgaonkar, K., Gur, O., Tran, P.L., Crosby, J.R.: Meyer: conformal piezoelectric systems for clinical and experimental characterization of soft tissue biomechanics. Nat. Mat. 14(7), 728–736 (2015)

    Google Scholar 

  25. Son, D., Lee, J., Qiao, S., Ghaffari, R., Kim, J., Lee, J.E., Song, C., Kim, S.J., Lee, D.J., Jun, S.W.: Multifunctional wearable devices for diagnosis and therapy of movement disorders. Nat. Nanotechnol. 9(5), 397–404 (2014)

    Google Scholar 

  26. Gao, W., Emaminejad, S., Nyein, H.Y.Y., Challa, S., Chen, K., Peck, A., Fahad, H.M., Ota, H., Shiraki, H., Kiriya, D.: Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature 529(7587), 509–514 (2016)

    Google Scholar 

  27. Kim, J., Lee, M., Shim, H.J., Ghaffari, R., Cho, H.R., Son, D., Jung, Y.H., Soh, M., Choi, C., Jung, S.: Stretchable silicon nanoribbon electronics for skin prosthesis. Nat. Commun. 5(1), 1–11 (2014)

    Google Scholar 

  28. Mannoor, M.S., Tao, H., Clayton, J.D., Sengupta, A., Kaplan, D.L., Naik, R.R., Verma, N., Omenetto, F.G., McAlpine, M.C.: Graphene-based wireless bacteria detection on tooth enamel. Nat. Commun. 3(1), 1–9 (2012)

    Google Scholar 

  29. Kim, S.-K., Koo, J., Lee, G.-H., Jeon, C., Mok, J.W., Mun, B.H., Lee, K.J., Kamrani, E., Joo, C.-K., Shin, S., et al.: Wireless smart contact lens for diabetic diagnosis and therapy. Sci. Adv. 6(17), eaba3252 (2020)

    Google Scholar 

  30. Dorairaj, S., Beltran-Agullo, L., Buys, Y.M., Trope, G.E., Shapiro, C., Simon-Zoula, S., Mansouri, K.: Detection of rapid eye movement sleep periods with a smart contact lens. Invest. Ophthalmol. Vis. Sci. 59(9), 2015 (2018)

    Google Scholar 

  31. Pal, A., Nadiger, V.G., Goswami, D., Martinez, R.V.: Conformal, waterproof electronic decals for wireless monitoring of sweat and vaginal ph at the point-of-care. Biosens. Bioelectron., 112206 (2020)

    Google Scholar 

  32. Olsson, M., Järbrink, K., Divakar, U., Bajpai, R., Upton, Z., Schmidtchen, A., Car, J.: The humanistic and economic burden of chronic wounds: a systematic review. Wound Repair Regen. 27(1), 114–125 (2019)

    Google Scholar 

  33. Mostafalu, P., Tamayol, A., Rahimi, R., Ochoa, M., Khalilpour, A., Kiaee, G., Yazdi, I.K., Bagherifard, S., Dokmeci, M.R., Ziaie, B., et al.: Smart bandage for monitoring and treatment of chronic wounds. Small 14(33), 1703509 (2018)

    Google Scholar 

  34. Derakhshandeh, H., Kashaf, S.S., Aghabaglou, F., Ghanavati, I.O., Tamayol, A.: Smart bandages: the future of wound care. Trends Biotechnol. 36(12), 1259–1274 (2018)

    Google Scholar 

  35. McLister, A., Phair, J., Cundell, J., Davis, J.: Electrochemical approaches to the development of smart bandages: a mini-review. Electrochem. Commun. 40, 96–99 (2014)

    Google Scholar 

  36. Han, G., Ceilley, R.: Chronic wound healing: a review of current management and treatments. Adv. Ther. 34(3), 599–610 (2017)

    Google Scholar 

  37. Gianino, E., Miller, C., Gilmore, J.: Smart wound dressings for diabetic chronic wounds. Bioengineering 5(3), 51 (2018)

    Google Scholar 

  38. Swisher, S.L.: Synthesis, Characterization, and Applications of Solution-Processed Nanomaterials: From Thin-film Transistors to Flexible “Smart Bandages”. University of California, Berkeley (2015)

    Google Scholar 

  39. Pang, Q., Lou, D., Li, S., Wang, G., Qiao, B., Dong, S., Ma, L., Gao, C., Wu, Z.: Smart flexible electronics-integrated wound dressing for real-time monitoring and on-demand treatment of infected wounds. Adv. Sci. 7(6), 1902673 (2020)

    Google Scholar 

  40. Mervis, J.S., Phillips, T.J.: Pressure ulcers: Pathophysiology, epidemiology, risk factors, and presentation. J. Am. Acad. Dermatol. 81(4), 881–890 (2019)

    Google Scholar 

  41. Tun, S.Y.Y., Madanian, S., Mirza, F.: Internet of things (IoT) applications for elderly care: a reflective review. Aging Clin. Exp. Res. 33(4), 855–867 (2021)

    Google Scholar 

  42. Brown, M.S., Ashley, B., Koh, A.: Wearable technology for chronic wound monitoring: current dressings, advancements, and future prospects. Front. Bioeng. Biotechnol. 6, 47 (2018)

    Google Scholar 

  43. Long, Y., Wei, H., Li, J., Yao, G., Yu, B., Ni, D., Gibson, A.L.F., Lan, X., Jiang, Y., Cai, W., et al.: Effective wound healing enabled by discrete alternative electric fields from wearable nanogenerators. ACS Nano 12(12), 12533–12540 (2018)

    Google Scholar 

  44. Zhang, A., Lieber, C.M.: Nano-bioelectronics. Chem. Rev. 116(1), 215–257 (2016)

    Google Scholar 

  45. Yu, Y., Nyein, H.Y.Y., Gao, W., Javey, A.: Flexible electrochemical bioelectronics: the rise of in situ bioanalysis. Adv. Mat. 32(15), 1902083 (2020)

    Google Scholar 

  46. Lim, C., Hong, Y.J., Jung, J., Shin, Y., Sunwoo, S.-H., Baik, S., Park, O.K., Choi, S.H., Hyeon, T., Kim, J.H., et al.: Tissue-like skin-device interface for wearable bioelectronics by using ultrasoft, mass-permeable, and low-impedance hydrogels. Sci. Adv. 7(19), eabd3716 (2021)

    Google Scholar 

  47. Tsujimura, S.: From fundamentals to applications of bioelectrocatalysis: bioelectrocatalytic reactions of fad-dependent glucose dehydrogenase and bilirubin oxidase. Biosci. Biotechnol. Biochem. 83(1), 39–48 (2019)

    Google Scholar 

  48. Ciui, B., Martin, A., Mishra, R.K., Brunetti, B., Nakagawa, T., Dawkins, T.J., Lyu, M., Cristea, C., Sandulescu, R., Wang, J.: Wearable wireless tyrosinase bandage and microneedle sensors: toward melanoma screening. Adv. Healthcare Mater. 7(7), 1701264 (2018)

    Google Scholar 

  49. Rojas, D., Hernández-Rodríguez, J.F., Pelle, F.D., Carlo, M.D., Compagnone, D., Escarpa, A.: Oxidative stress on-chip: Prussian blue-based electrode array for in situ detection of H 2 O 2 from cell populations. Biosens. Bioelectron. 170, 112669 (2020)

    Google Scholar 

  50. Kim, J., Jeerapan, I., Sempionatto, J.R., Barfidokht, A., Mishra, R.K., Campbell, A.S., Hubble, L.J., Wang, J.: Wearable bioelectronics: Enzyme-based body-worn electronic devices. Acc. Chem. Res. 51(11), 2820–2828 (2018)

    Google Scholar 

  51. Poongodi, M., Hamdi, M., Malviya, M., Sharma, A., Dhiman, G., Vimal, S.: Diagnosis and combating covid-19 using wearable oura smart ring with deep learning methods. Pers. Ubiquit. Comput., 1–11 (2021)

    Google Scholar 

  52. Zhang, X., Kadimisetty, K., Yin, K., Ruiz, C., Mauk, M.G., Liu, C.: Smart ring: a wearable device for hand hygiene compliance monitoring at the point-of-need. Microsyst. Technol. 25(8), 3105–3110 (2019)

    Google Scholar 

  53. Gheran, B.-F., Vanderdonckt, J., Vatavu, R.-D.: Gestures for smart rings: empirical results, insights, and design implications. In: Proceedings of the 2018 Designing Interactive Systems Conference, pp. 623–635 (2018)

    Google Scholar 

  54. Lee, S., Song, Y., Lee, J., Oh, J., Lim, T.H., Ahn, C., Kim, I.Y.: Development of smart-ring-based chest compression depth feedback device for high quality chest compressions: A proof-of-concept study. Biosensors 11, 35 (2021)

    Google Scholar 

  55. Ju, A.L., Spasojevic, M.: Smart jewelry: The future of mobile user interfaces. In Proceedings of the 2015 Workshop on Future Mobile User Interfaces, pp. 13–15 (2015)

    Google Scholar 

  56. Kalantarian, H., Alshurafa, N., Le, T., Sarrafzadeh, M.: Non-invasive detection of medication adherence using a digital smart necklace. In: 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), pp. 348–353. IEEE, Piscataway (2015)

    Google Scholar 

  57. Chung, H.-Y., Chung, Y.-L., Liang, C.-Y., et al.: Design and implementation of a novel system for correcting posture through the use of a wearable necklace sensor. JMIR Mhealth Uhealth 7(5), e12293 (2019)

    Google Scholar 

  58. Kan, C.-W., Lam, Y.-L.: Future trend in wearable electronics in the textile industry. Appl. Sci. 11(9), 3914 (2021)

    Google Scholar 

  59. Kumaravel, S.: Smart healthcare with sensors and wireless body area networking. In: Smart Healthcare for Disease Diagnosis and Prevention, pp. 213–227. Elsevier, Amsterdam (2020)

    Google Scholar 

  60. Randhawa, P., Shanthagiri, V., Mour, R., Kumar, A.: Design and development of smart-jacket for posture detection. In: 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE), pp. 1–5. IEEE, Piscataway (2018)

    Google Scholar 

  61. Naranjo-Hernández, D., Talaminos-Barroso, A., Reina-Tosina, J., Roa, L.M., Barbarov-Rostan, G., Cejudo-Ramos, P., Márquez-Martín, E., Ortega-Ruiz, F.: Smart vest for respiratory rate monitoring of copd patients based on non-contact capacitive sensing. Sensors 18(7), 2144 (2018)

    Google Scholar 

  62. Sayem, A.S.M., Teay, S.H., Shahariar, H., Fink, P.L., Albarbar, A.: Review on smart electro-clothing systems (SeCSs). Sensors 20(3), 587 (2020)

    Google Scholar 

  63. Cheng, A.L., Santos, C., Santos, P., Vega, N.L.: Development of a smart sleeve control mechanism for active assisted living. In: 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), pp. 847–851. IEEE, Piscataway (2019)

    Google Scholar 

  64. Chang, W.-J., Chen, L.-B., Chiou, Y.-Z.: Design and implementation of a drowsiness-fatigue-detection system based on wearable smart glasses to increase road safety. IEEE Trans. Consum. Electron. 64(4), 461–469 (2018)

    Google Scholar 

  65. Akpa, A.H., Fujiwara, M., Suwa, H., Arakawa, Y., Yasumoto, K.: A smart glove to track fitness exercises by reading hand palm. J. Sens. 2019 (2019)

    Google Scholar 

  66. Gögele, C., Hahn, J., Elschner, C., Breier, A., Schröpfer, M., Prade, I., Meyer, M., Schulze-Tanzil, G.: Enhanced growth of lapine anterior cruciate ligament-derived fibroblasts on scaffolds embroidered from poly (l-lactide-co-ε-caprolactone) and polylactic acid threads functionalized by fluorination and hexamethylene diisocyanate cross-linked collagen foams. Int. J. Mol. Sci. 21(3), 1132 (2020)

    Google Scholar 

  67. He, M., Ou, F., Wu, Y., Sun, X., Chen, X., Li, H., Sun, D., Zhang, L.: Smart multi-layer pva foam/cmc mesh dressing with integrated multi-functions for wound management and infection monitoring. Mater. Des. 194, 108913 (2020)

    Google Scholar 

  68. Kim, D.-H., Wang, S., Keum, H., Ghaffari, R., Kim, Y.-S., Tao, H., Panilaitis, B., Li, M., Kang, Z., Omenetto, F., et al.: Thin, flexible sensors and actuators as ‘instrumented’surgical sutures for targeted wound monitoring and therapy. Small 8(21), 3263–3268 (2012)

    Google Scholar 

  69. Wang, C., Kim, Y., Min, S.D.: Soft-material-based smart insoles for a gait monitoring system. Materials 11(12), 2435 (2018)

    Google Scholar 

  70. Rezayi, S., Safaei, A.A., Mohammadzadeh, N.: Design and evaluation of a wearable smart blanket system for monitoring vital signs of patients in an ambulance. J. Sens. 2021 (2021)

    Google Scholar 

  71. de Medeiros, M.S., Chanci, D., Moreno, C., Goswami, D., Martinez, R.V.: Waterproof, breathable, and antibacterial self-powered e-textiles based on omniphobic triboelectric nanogenerators. Adv. Funct. Mat. 29(42), 1904350 (2019)

    Google Scholar 

  72. Cianchetti, M., Laschi, C., Menciassi, A., Dario, P.: Biomedical applications of soft robotics. Nat. Rev. Mat. 3(6), 143–153 (2018)

    Google Scholar 

  73. Rich, S.I., Wood, R.J., Majidi, C.: Untethered soft robotics. Nat. Elect. 1(2), 102–112 (2018)

    Google Scholar 

  74. Park, H.-L., Lee, Y., Kim, N., Seo, D.-G., Go, G.-T., Lee, T.-W.: Flexible neuromorphic electronics for computing, soft robotics, and neuroprosthetics. Adv. Mat. 32(15), 1903558 (2020)

    Google Scholar 

  75. Chew, E., Turner, D.A.: Can a robot bring your life back? a systematic review for robotics in rehabilitation. Robot. Healthc. Field Examples Challenges 1170, 1–35 (2019)

    Google Scholar 

  76. Natividad, R.F., Hong, S.W., Miller-Jackson, T.M., Yeow, C.-H.: The exosleeve: a soft robotic exoskeleton for assisting in activities of daily living. In: International Symposium on Wearable Robotics, pp. 406–409. Springer, Berlin (2018)

    Google Scholar 

  77. Wang, J., Gao, D., Lee, P.S.: Recent progress in artificial muscles for interactive soft robotics. Adv. Mat. 33(19), 2003088 (2021)

    Google Scholar 

  78. Goswami, D., Liu, S., Pal, A., Silva, L.G., Martinez, R.V.: 3d-architected soft machines with topologically encoded motion. Adv. Funct. Mat. 29(24), 1808713 (2019)

    Google Scholar 

  79. Fitzgerald, S.G., Delaney, G.W., Howard, D.: A review of jamming actuation in soft robotics. In: Actuators, vol. 9, p. 104. Multidisciplinary Digital Publishing Institute, Basel (2020)

    Google Scholar 

  80. Chang, L., Liu, Y., Yang, Q., Yu, L., Liu, J., Zhu, Z., Lu, P., Wu, Y., Hu, Y.: Ionic electroactive polymers used in bionic robots: a review. J. Bionic Eng. 15 (5), 765–782 (2018)

    Google Scholar 

  81. Yun, G., Tang, S.-Y., Sun, S., Yuan, D., Zhao, Q., Deng, L., Yan, S., Du, H., Dickey, M.D., Li, W.: Liquid metal-filled magnetorheological elastomer with positive piezoconductivity. Nat. Commun. 10(1), 1–9 (2019)

    Google Scholar 

  82. Copaci, D.-S., Blanco, D., Martin-Clemente, A., Moreno, L.: Flexible shape memory alloy actuators for soft robotics: modelling and control. Int. J. Adv. Robot. Syst. 17(1), 1729881419886747 (2020)

    Google Scholar 

  83. Chu, C.-Y., Patterson, R.M.: Soft robotic devices for hand rehabilitation and assistance: a narrative review. J. Neuroeng. Rehab. 15(1), 1–14 (2018)

    Google Scholar 

  84. El-Atab, N., Mishra, R.B., Al-Modaf, F., Joharji, L., Alsharif, A.A., Alamoudi, H., Diaz, M., Qaiser, N., Hussain, M.M.: Soft actuators for soft robotic applications: a review. Adv. Intell. Syst. 2(10), 2000128 (2020)

    Google Scholar 

  85. Kwon, J., Park, J.-H., Ku, S., Jeong, Y.H., Paik, N.-J., Park, Y.-L.: A soft wearable robotic ankle-foot-orthosis for post-stroke patients. IEEE Robot. Autom. Lett. 4(3), 2547–2552 (2019)

    Google Scholar 

  86. Kurita, Y., Thakur, C., Das, S.: Assistive soft exoskeletons with pneumatic artificial muscles. In: Haptic Interfaces for Accessibility, Health, and Enhanced Quality of Life, pp. 217–242. Springer, Berlin (2020)

    Google Scholar 

  87. Xiloyannis, M., Alicea, R., Georgarakis, A.-M., Haufe, F.L., Wolf, P., Masia, L., Riener, R.: Soft robotic suits: State of the art, core technologies, and open challenges. IEEE Trans. Robot. 38(3), 1343–1362 (2021)

    Google Scholar 

  88. Walsh, C.: Human-in-the-loop development of soft wearable robots. Nat. Rev. Mat. 3(6), 78–80 (2018)

    Google Scholar 

  89. Polygerinos, P., Wang, Z., Galloway, K.C., Wood, R.J., Walsh, C.J.: Soft robotic glove for combined assistance and at-home rehabilitation. Robot. Autonom. Syst. 73, 135–143 (2015)

    Google Scholar 

  90. Devi, M.A., Udupa, G., Sreedharan, P.: A novel underactuated multi-fingered soft robotic hand for prosthetic application. Robot. Autonom. Syst. 100, 267–277 (2018)

    Google Scholar 

  91. Park, C., Fan, Y., Hager, G., Yuk, H., Singh, M., Rojas, A., Hameed, A., Saeed, M., Vasilyev, N.V., Steele, T.W.J., et al.: An organosynthetic dynamic heart model with enhanced biomimicry guided by cardiac diffusion tensor imaging. Sci. Robot. 5(38) (2020)

    Google Scholar 

  92. Gul, J.Z., Sajid, M., Rehman, M.M., Siddiqui, G.U., Shah, I., Kim, K.-H., Lee, J.-W., Choi, K.H.: 3d printing for soft robotics–a review. Sci. Technol. Adv. Mat. 19(1), 243–262 (2018)

    Google Scholar 

  93. Ranunkel, O., Güder, F., Arora, H.: Soft robotic surrogate lung. ACS Appl. Bio. Mat. 2(4), 1490–1497 (2019)

    Google Scholar 

  94. Roche, E.T., Horvath, M.A., Wamala, I., Alazmani, A., Song, S.-E., Whyte, W., Machaidze, Z., Payne, C.J., Weaver, J.C., Fishbein, G., Kuebler, J.: Soft robotic sleeve supports heart function. Sci. Transl. Med. 9(373) (2017)

    Google Scholar 

  95. Horvath, M.A., Wamala, I., Rytkin, E., Doyle, E., Payne, C.J., Thalhofer, T., Berra, I., Solovyeva, A., Saeed, M., Hendren, S., et al.: An intracardiac soft robotic device for augmentation of blood ejection from the failing right ventricle. Ann. Biomed. Eng. 45(9), 2222–2233 (2017)

    Google Scholar 

  96. Tanaka, M., Abe, K., Wang, F., Nakagawa, H., Arai, Y., Tanahashi, Y., Chonan, S.: Artificial urethral valve driven by sma actuators with transcutaneous energy transmission system. Int. J. Appl. Electromagn. Mech. 18(1–3), 23–30 (2003)

    Google Scholar 

  97. Dunn, J., Runge, R., Snyder, M.: Wearables and the medical revolution. Pers. Med. 15(5), 429–448 (2018)

    Google Scholar 

  98. Yao, H., Yang, W., Cheng, W., Tan, Y.J., See, H.H., Li, S., Ali, H.P.A., Lim, B.Z.H., Liu, Z., Tee, B.C.K.: Near–hysteresis-free soft tactile electronic skins for wearables and reliable machine learning. Proc. Natl. Acad. Sci., 117(41), 25352–25359 (2020)

    Google Scholar 

  99. Quer, G., Radin, J.M., Gadaleta, M., Baca-Motes, K., Ariniello, L., Ramos, E., Kheterpal, V., Topol, E.J., Steinhubl, S.R.: Wearable sensor data and self-reported symptoms for covid-19 detection. Nat. Med. 27(1), 73–77 (2021)

    Google Scholar 

  100. Yetisen, A.K., Martinez-Hurtado, J.L., Ünal, B., Khademhosseini, A., Butt, H.: Wearables in medicine. Adv. Mat. 30(33), 1706910 (2018)

    Google Scholar 

  101. Cirillo, D., Valencia, A.: Big data analytics for personalized medicine. Curr. Opin. Biotechnol. 58, 161–167 (2019)

    Google Scholar 

  102. Kim, J., Campbell, A.S., de Ávila, B.E.-F., Wang, J.: Wearable biosensors for healthcare monitoring. Nat. Biotechnol. 37(4), 389–406 (2019)

    Google Scholar 

  103. Schork, N.J.: Artificial intelligence and personalized medicine. In: Precision Medicine in Cancer Therapy, pp. 265–283. Springer, Berlin (2019)

    Google Scholar 

  104. Zemouri, R., Zerhouni, N., Racoceanu, D.: Deep learning in the biomedical applications: recent and future status. Appl. Sci. 9(8), 1526 (2019)

    Google Scholar 

  105. Hinton, G.: Deep learning—a technology with the potential to transform health care. JAMA 320(11), 1101–1102 (2018)

    Google Scholar 

  106. Baig, M.M., GholamHosseini, H., Moqeem, A.A., Mirza, F., Lindén, M.: A systematic review of wearable patient monitoring systems–current challenges and opportunities for clinical adoption. J. Med. Syst. 41(7), 1–9 (2017)

    Google Scholar 

  107. Patel, N.M., Michelini, V.V., Snell, J.M., Balu, S., Hoyle, A.P., Parker, J.S., Hayward, M.C., Eberhard, D.A., Salazar, A.H., McNeillie, P., et al.: Enhancing next-generation sequencing-guided cancer care through cognitive computing. Oncologist 23(2), 179 (2018)

    Google Scholar 

  108. Shi, W., Dustdar, S.: The promise of edge computing. Computer 49(5), 78–81 (2016)

    Google Scholar 

  109. Dewanto, S., Alexandra, M., Surantha, N.: Heart rate monitoring with smart wearables using edge computing. Heart 11(3) (2020)

    Google Scholar 

  110. Chervyakov, N., Babenko, M., Tchernykh, A., Kucherov, N., Miranda-López, V., Cortés-Mendoza, J.M.: AR-RRNS: configurable reliable distributed data storage systems for internet of things to ensure security. Fut. Gen. Comput. Syst. 92, 1080–1092 (2019)

    Google Scholar 

  111. Weisberg, S.: Applied Linear Regression, vol. 528. John Wiley & Sons, Hoboken (2005)

    MATH  Google Scholar 

  112. Menard, S.: Applied Logistic Regression Analysis, vol. 106. Sage, Thousand Oaks (2002)

    Google Scholar 

  113. Likas, A., Vlassis, N., Verbeek, J.J.: The global k-means clustering algorithm. Patt. Recog. 36(2), 451–461 (2003)

    Google Scholar 

  114. Do, C.B., Batzoglou, S.: What is the expectation maximization algorithm? Nat. Biotechnol. 26(8), 897–899 (2008)

    Google Scholar 

  115. Duan, J., Soussen, C., Brie, D., Idier, J., Wan, M., Wang, Y.-P.: Generalized lasso with under-determined regularization matrices. Sig. Process. 127, 239–246 (2016)

    Google Scholar 

  116. Mol, C.D., Vito, E.D., Rosasco, L.: Elastic-net regularization in learning theory. J. Complex. 25(2), 201–230 (2009)

    MathSciNet  MATH  Google Scholar 

  117. Ertuğrul, Ö.F., Tağluk, M.E.: A novel version of k nearest neighbor: dependent nearest neighbor. Appl. Soft Comput. 55, 480–490 (2017)

    Google Scholar 

  118. Sinha, S., Singh, T.N., Singh, V.K., Verma, A.K.: Epoch determination for neural network by self-organized map (SOM). Comput. Geosci. 14(1), 199–206 (2010)

    MATH  Google Scholar 

  119. Zhao, Y., Zhang, Y.: Comparison of decision tree methods for finding active objects. Adv. Space Res. 41(12), 1955–1959 (2008)

    Google Scholar 

  120. Yahşi, M., Çanakoğlu, E., Ağralı, S.: Carbon price forecasting models based on big data analytics. Carbon Manage. 10(2), 175–187 (2019)

    Google Scholar 

  121. Saritas, M.M., Yasar, A.: Performance analysis of ann and naive bayes classification algorithm for data classification. Int. J. Intell. Syst. Appl. Eng. 7(2), 88–91 (2019)

    Google Scholar 

  122. Forio, M.A.E., Landuyt, D., Bennetsen, E., Lock, K., Nguyen, T.H.T., Ambarita, M.n.d., Musonge, P.L.S., Boets, P., Everaert, G., Dominguez-Granda, L., et al.: Bayesian belief network models to analyse and predict ecological water quality in rivers. Ecol. Model. 312, 222–238 (2015)

    Google Scholar 

  123. Baig, M.M., Awais, M.M., El-Alfy, E.-S.M.: Adaboost-based artificial neural network learning. Neurocomputing 248, 120–126 (2017)

    Google Scholar 

  124. Biau, G., Scornet, E.: A random forest guided tour. Test 25(2), 197–227 (2016)

    MathSciNet  MATH  Google Scholar 

  125. Zhang, C.-Y., Chen, C.L.P., Gan, M., Chen, L.: Predictive deep boltzmann machine for multiperiod wind speed forecasting. IEEE Trans. Sustain. Energy 6(4), 1416–1425 (2015)

    Google Scholar 

  126. Aghdam, H.H., Heravi, E.J.: Guide to Convolutional Neural Networks. Springer, New York (2017)

    Google Scholar 

  127. Bhandari, A., Gupta, A., Das, D.: Improvised apriori algorithm using frequent pattern tree for real time applications in data mining. Proc. Comput. Sci. 46, 644–651 (2015)

    Google Scholar 

  128. Ma, Z., Yang, J., Zhang, T., Liu, F.: An improved eclat algorithm for mining association rules based on increased search strategy. Int. J. Database Theor. Appl. 9(5), 251–266 (2016)

    Google Scholar 

  129. Bro, R., Smilde, A.K.: Principal component analysis. Anal. Method. 6(9), 2812–2831 (2014)

    Google Scholar 

  130. Tang, Z., Huang, Z., Zhang, X., Lao, H.: Robust image hashing with multidimensional scaling. Sig. Process. 137, 240–250 (2017)

    Google Scholar 

  131. Li, Z., Zhong, Z., Li, Y., Zhang, T., Gao, L., Jin, D., Sun, Y., Ye, X., Yu, L., Hu, Z., et al.: From community-acquired pneumonia to covid-19: a deep learning–based method for quantitative analysis of covid-19 on thick-section CT scans. Eur. Radiol. 30(12), 6828–6837 (2020)

    Google Scholar 

  132. Lu, M.T., Ivanov, A., Mayrhofer, T., Hosny, A., Aerts, H.J.W.L., Hoffmann, U.: Deep learning to assess long-term mortality from chest radiographs. JAMA Netw. Open 2(7), e197416–e197416 (2019)

    Google Scholar 

  133. Abubakar, A., Ugail, H., Smith, K.M., Bukar, A.M., Elmahmudi, A.: Burns depth assessment using deep learning features. J. Med. Biol. Eng. 40(6), 923–933 (2020)

    Google Scholar 

  134. Kiral-Kornek, I., Roy, S., Nurse, E., Mashford, B., Karoly, P., Carroll, T., Payne, D., Saha, S., Baldassano, S., O’Brien, T., et al.: Epileptic seizure prediction using big data and deep learning: toward a mobile system. EBioMedicine 27, 103–111 (2018)

    Google Scholar 

  135. Flanagan, O.: Addiction doesn’t exist, but it is bad for you. Neuroethics 10(1), 91–98 (2017)

    Google Scholar 

  136. King, C.E., Sarrafzadeh, M.: A survey of smartwatches in remote health monitoring. J. Healthc. Infor. Res. 2(1), 1–24 (2018)

    Google Scholar 

  137. Wang, H., Totaro, M., Beccai, L.: Toward perceptive soft robots: progress and challenges. Adv. Sci. 5(9), 1800541 (2018)

    Google Scholar 

  138. Maglio, S., Park, C., Tognarelli, S., Menciassi, A., Roche, E.T.: High-fidelity physical organ simulators: from artificial to bio-hybrid solutions. IEEE Trans. Med. Robot. Bionics 3(2), 349–361 (2021)

    Google Scholar 

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    Ramses V. Martinez

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    Shimon Y. Nof

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    Martinez, R.V. (2023). Wearables, E-textiles, and Soft Robotics for Personalized Medicine. In: Nof, S.Y. (eds) Springer Handbook of Automation. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-030-96729-1_59

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