Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Skin-interfaced wireless biosensors for perinatal and paediatric health

An Author Correction to this article was published on 07 August 2023

This article has been updated

Abstract

Continuous monitoring of the parameters that define physiological health status is an essential aspect of modern care for critically ill patients, particularly for vulnerable populations. Current hospital-grade systems for such purposes involve sensors taped to the skin, with hard-wired connections to large, expensive data-acquisition and display systems. Soft, wireless, skin-interfaced alternatives reduce associated burdens on the patients, simplify operations in clinical care, minimize risks of adhesive-induced skin injuries and reduce the costs of monitoring, as recently demonstrated in devices designed for maternal, foetal and paediatric health. The implications extend beyond hospital and home settings in well resourced areas of the globe to remote clinics in low and middle-income countries. This Review summarizes the latest progress in this research area, with an emphasis on the growing range of options in device configurations and form factors, sensor modalities and operational features. Examples of technologies capable of monitoring all key vital signs as well as various unconventional metrics of health status highlight the transition from academic prototypes to manufactured systems and scaled deployments.

Key points

  • Continuous physiological monitoring is an essential aspect of modern healthcare for the critically ill, especially perinatal and paediatric patients.

  • Wireless monitoring technologies reduce patient discomfort, risk of iatrogenic injury and healthcare provider burden while informing and guiding many aspects of clinical care.

  • Soft, compliant, miniaturized skin-interfaced sensors enable safe and reliable connectivity to the skin of the most fragile patients at different body locations, without straps, bands or abrasive adhesives.

  • Cost-effective engineering designs and manufacturing techniques allow for the practical use of advanced technologies in low-resource settings.

  • Broad, multi-modal data streams collected in healthcare facilities or in home settings can serve as the basis for a data-centric approach for early intervention and patient care.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Comparisons of traditional and emerging monitoring technologies for maternal and paediatric health.
Fig. 2: Diagrams of physiological markers of health status from different patients.
Fig. 3: Diagrams and examples of device architectures and body interfaces.
Fig. 4: Wireless biosensors for maternal and foetal monitoring.
Fig. 5: Wireless biosensors for paediatric monitoring.

Change history

References

  1. Candid: Gates Foundation report finds slow progress on SDGs but sees potential. Philanthropy News Digest https://philanthropynewsdigest.org/news/gates-foundation-report-finds-slow-progress-on-sdgs-but-sees-potential (14 September 2022).

  2. Sedgh, G., Singh, S. & Hussain, R. Intended and unintended pregnancies worldwide in 2012 and recent Trends. Stud. Fam. Plann. 45, 301–314 (2014).

    Google Scholar 

  3. Intrapartum care for a positive childbirth experience. WHO https://www.who.int/publications/i/item/9789241550215 (2018).

  4. MacDorman, M. F., Declercq, E., Cabral, H. & Morton, C. Is the United States maternal mortality rate increasing? Disentangling trends from measurement issues. Obstet. Gynecol. 128, 447–455 (2016).

    Google Scholar 

  5. Trends in maternal mortality 2000 to 2017: estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. UNFPA/WHO https://www.unfpa.org/featured-publication/trends-maternal-mortality-2000-2017 (2019).

  6. Neonatal mortality. UNICEF https://data.unicef.org/topic/child-survival/neonatal-mortality/ (2021).

  7. Ettinger, A. S. Children’s Health, The Nation’s Wealth: Assessing And Improving Child Health (National Academies Press, 2004).

  8. Xu, S., Jayaraman, A. & Rogers, J. A. Skin sensors are the future of health care. Nature 571, 319–321 (2019).

    Google Scholar 

  9. Fox, P. E. & Rutter, N. The childhood scars of newborn intensive care. Early Hum. Dev. 51, 171–177 (1998).

    Google Scholar 

  10. Lund, C. Medical adhesives in the NICU. Newborn Infant. Nurs. Rev. 14, 160–165 (2014).

    Google Scholar 

  11. Tottman, A. C., Alsweiler, J. M., Bloomfield, F. H. & Harding, J. E. Presence and pattern of scarring in children born very preterm. Arch. Dis. Child. Fetal Neonatal Ed. 103, F277–F279 (2018).

    Google Scholar 

  12. Gao, W. et al. Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature 529, 509–514 (2016).

    Google Scholar 

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

    Google Scholar 

  14. Rochat, R. W., Koonin, L. M., Atrash, H. K. & Jewett, J. F. Maternal mortality in the United States: report from the maternal mortality collaborative. Obstet. Gynecol. 72, 91–97 (1988).

    Google Scholar 

  15. Kodio, B. et al. Levels and causes of maternal mortality in Senegal. Trop. Med. Int. Health 7, 499–505 (2002).

    Google Scholar 

  16. D’Alton, M. E. et al. Putting the “M” back in maternal–fetal medicine: a 5-year report card on a collaborative effort to address maternal morbidity and mortality in the United States. Am. J. Obstet. Gynecol. 221, 311–317 (2019).

    Google Scholar 

  17. Nagaya, K. et al. Causes of maternal mortality in Japan. J. Am. Med. Assoc. 283, 2661–2667 (2000).

    Google Scholar 

  18. Vousden, N., Nathan, H. L. & Shennan, A. H. Innovations in vital signs measurement for the detection of hypertension and shock in pregnancy. Reprod. Health 15, 87–91 (2018).

    Google Scholar 

  19. Harville, E. W., Viikari, J. S. A. & Raitakari, O. T. Preconception cardiovascular risk factors and pregnancy outcome. Epidemiology 22, 724–730 (2011).

    Google Scholar 

  20. Cameron, N. A. et al. Geographic differences in prepregnancy cardiometabolic health in the United States, 2016 through 2019. Circulation 145, 549–551 (2022).

    Google Scholar 

  21. Aggarwal, G. & Wei, Y. Non-invasive fetal electrocardiogram monitoring techniques: potential and future research opportunities in smart textiles. Signals 2, 392–412 (2021).

    Google Scholar 

  22. López Bernal, A. Overview. Preterm labour: mechanisms and management. BMC Pregnancy Childbirth 7, S2 (2007).

    Google Scholar 

  23. La Rosa, P. S., Eswaran, H., Preissl, H. & Nehorai, A. Multiscale forward electromagnetic model of uterine contractions during pregnancy. BMC Med. Phys. 12, 4 (2012).

    Google Scholar 

  24. Schifrin, B. S. Fetal heart rate monitoring during labor. J. Am. Med. Assoc. 222, 196–202 (1972).

    Google Scholar 

  25. Freeman, R. K., Garite, T. J., Nageotte, M. P. & Miller, L. A. Fetal Heart Rate Monitoring (Lippincott Williams & Wilkins, 2012).

  26. von Steinburg, S. P. et al. What is the “normal” fetal heart rate? PeerJ 1, e82 (2013).

    Google Scholar 

  27. Jagannath, D. J. & Selvakumar, A. I. Issues and research on fetal electrocardiogram signal elicitation. Biomed. Signal. Process. Control. 10, 224–244 (2014).

    Google Scholar 

  28. Boatin, A. A. et al. Wireless vital sign monitoring in pregnant women: a functionality and acceptability study. Telemed. J. E Health 22, 564–571 (2016).

    Google Scholar 

  29. Martinek, R. et al. Comparative effectiveness of ICA and PCA in extraction of fetal ECG from abdominal signals: toward non-invasive fetal monitoring. Front. Physiol. 9, 648 (2018).

    Google Scholar 

  30. Hayes-Gill, B. et al. Accuracy and reliability of uterine contraction identification using abdominal surface electrodes. Clin. Med. Insights Women’s Health 5, CMWH.S10444 (2012).

    Google Scholar 

  31. Euliano, T. Y. et al. Monitoring uterine activity during labor: a comparison of 3 methods. Am. J. Obstet. Gynecol. 208, 66.e1–66.e6 (2013).

    Google Scholar 

  32. Vlemminx, M. W. C. et al. Electrohysterography for uterine monitoring during term labour compared to external tocodynamometry and intra-uterine pressure catheter. Eur. J. Obstet. Gynecol. Reprod. Biol. 215, 197–205 (2017).

    Google Scholar 

  33. Hadar, E., Biron-Shental, T., Gavish, O., Raban, O. & Yogev, Y. A comparison between electrical uterine monitor, tocodynamometer and intra uterine pressure catheter for uterine activity in labor. J. Maternal-Fetal Neonatal Med. 28, 1367–1374 (2015).

    Google Scholar 

  34. Cohen, W. R. & Hayes‐Gill, B. Influence of maternal body mass index on accuracy and reliability of external fetal monitoring techniques. Acta Obstet. Gynecol. Scand. 93, 590–595 (2014).

    Google Scholar 

  35. Martin, J. A., Hamilton, B. E., Osterman, M. J. K. & Driscoll, A. K. Births: final data for 2018. Natl. Vital. Stat. Rep. 68, 1–47 (2019).

    Google Scholar 

  36. Alfirevic, Z., Gyte, G. M., Cuthbert, A. & Devane, D. Continuous cardiotocography (CTG) as a form of electronic fetal monitoring (EFM) for fetal assessment during labour. Cochrane Database Syst. Rev. 2, CD006066 (2017).

    Google Scholar 

  37. Karlsson, B., Berson, M., Helgason, T., Geirsson, R. T. & Pourcelot, L. Effects of fetal and maternal breathing on the ultrasonic Doppler signal due to fetal heart movement. Eur. J. Ultrasound 11, 47–52 (2000).

    Google Scholar 

  38. Garite, T. J. The search for an adequate back-up test for intrapartum fetal heart rate monitoring. Am. J. Obstet. Gynecol. 208, 163–164 (2013).

    Google Scholar 

  39. Ryu, D. et al. Comprehensive pregnancy monitoring with a network of wireless, soft, and flexible sensors in high- and low-resource health settings. Proc. Natl Acad. Sci. USA 118, e2100466118 (2021). This article reports on wireless, skin-interfaced sensors for labouring women and their foetuses.

    Google Scholar 

  40. de Vries, J. I. P. & Fong, B. F. Normal fetal motility: an overview. Ultrasound Obstet. Gynecol. 27, 701–711 (2006).

    Google Scholar 

  41. Andonotopo, W. & Kurjak, A. The assessment of fetal behavior of growth restricted fetuses by 4D sonography. J. Perinat. Med. 34, 471–478 (2006).

    Google Scholar 

  42. Hatat, T. T. A. et al. Optimization and initial experience of a multisection balanced steady-state free precession cine sequence for the assessment of fetal behavior in utero. Am. J. Neuroradiol. 32, 331–338 (2011).

    Google Scholar 

  43. Akata, T. et al. Reliability of fingertip skin-surface temperature and its related thermal measures as indices of peripheral perfusion in the clinical setting of the operating theatre. Anaesth. Intensive Care 32, 519–529 (2004).

    Google Scholar 

  44. Aynsley-Green, A. & Pickering, D. Use of central and peripheral temperature measurements in care of the critically ill child. Arch. Dis. Child. 49, 477–481 (1974).

    Google Scholar 

  45. Lima, A. & Bakker, J. Noninvasive monitoring of peripheral perfusion. Intensive Care Med. 31, 1316–1326 (2005).

    Google Scholar 

  46. Vali, K. et al. Estimation of fetal blood oxygen saturation from transabdominally acquired photoplethysmogram waveforms. In 2021 43rd Ann. Int. Conf. IEEE Engineering in Medicine & Biology Society (EMBC) 1100–1103 (IEEE, 2021).

  47. Pediatric medical devices. USFDA https://www.fda.gov/medical-devices/products-and-medical-procedures/pediatric-medical-devices (2022).

  48. Harless, J., Ramaiah, R. & Bhananker, S. M. Pediatric airway management. Int. J. Crit. Illn. Inj. Sci. 4, 65–70 (2014).

    Google Scholar 

  49. Huelke, D. F. An overview of anatomical considerations of infants and children in the adult world of automobile safety design. Annu. Proc. Assoc. Adv. Automot. Med. 42, 93–113 (1998).

    Google Scholar 

  50. Burdi, A. R., Huelke, D. F., Snyder, R. G. & Lowrey, G. H. Infants and children in the adult world of automobile safety design: pediatric and anatomical considerations for design of child restraints. J. Biomech. 2, 267–280 (1969).

    Google Scholar 

  51. Figaji, A. A. Anatomical and physiological differences between children and adults relevant to traumatic brain injury and the implications for clinical assessment and care. Front. Neurol. 8, 685 (2017).

    Google Scholar 

  52. Krieger, I. Studies on mechanics of respiration in infancy. Am. J. Dis. Child. 105, 439–448 (1963).

    Google Scholar 

  53. Haque, I. U. & Zaritsky, A. L. Analysis of the evidence for the lower limit of systolic and mean arterial pressure in children. Pediatr. Crit. Care Med. 8, 138–144 (2007).

    Google Scholar 

  54. Padayachy, L. C., Figaji, A. A. & Bullock, M. R. Intracranial pressure monitoring for traumatic brain injury in the modern era. Childs Nerv. Syst. 26, 441–452 (2010).

    Google Scholar 

  55. Costello, J. M., Patak, L. & Pritchard, J. Communication vulnerable patients in the pediatric ICU: enhancing care through augmentative and alternative communication. J. Pediatr. Rehabil. Med. 3, 289–301 (2010).

    Google Scholar 

  56. Baddley, D. Enhancing effective communication among non-verbal patients. Pediatr. Nurs. 44, 144–146 (2018).

    Google Scholar 

  57. Rosenberg, D. I. & Moss, M. M. Guidelines and levels of care for pediatric intensive care units. Pediatrics 114, 1114–1125 (2004).

    Google Scholar 

  58. Pollack, M. M., Ruttimann, U. E., Glass, N. L. & Yeh, T. S. Monitoring patients in pediatric intensive care. Pediatrics 76, 719–724 (1985).

    Google Scholar 

  59. Liu, C. et al. Wireless, skin-interfaced devices for pediatric critical care: application to continuous, noninvasive blood pressure monitoring. Adv. Healthc. Mater. 10, 2100383 (2021).

    Google Scholar 

  60. Brambilla, C. et al. Combined use of EMG and EEG techniques for neuromotor assessment in rehabilitative applications: a systematic review. Sensors 21, 7014 (2021).

    Google Scholar 

  61. Davidson, A. J. Measuring anesthesia in children using the EEG. Pediatr. Anesth. 16, 374–387 (2006).

    Google Scholar 

  62. Pandey, B. & Mishra, R. B. An integrated intelligent computing model for the interpretation of EMG based neuromuscular diseases. Expert. Syst. Appl. 36, 9201–9213 (2009).

    Google Scholar 

  63. Chen, W., Bouwstra, S., Oetomo, S. B. & Feijs, L. Intelligent design for neonatal monitoring with wearable sensors. In Intelligent and Biosensors 386–410 (IntechOpen, 2010).

  64. Branche, T., Perez, M. & Saugstad, O. D. The first golden minute — is it relevant? Resuscitation 156, 284–285 (2020).

    Google Scholar 

  65. American College of Obstetricians and Gynecologists Committee on Practice Bulletins — Obstetrics. Prediction and prevention of spontaneous preterm birth: ACOG Practice Bulletin, Number 234. Obstet. Gynecol. 138, e65–e90 (2021).

    Google Scholar 

  66. Galal, M., Symonds, I., Murray, H., Petraglia, F. & Smith, R. Postterm pregnancy. Facts Views Vis. ObGyn. 4, 175–187 (2012).

    Google Scholar 

  67. Rao, H. et al. Design Of A Wearable Remote Neonatal Health Monitoring Device In Biomedical Engineering Systems And Technologies 34–51 (Springer International Publishing, 2015).

  68. Durrani, N. U. R., Imam, A. A. & Soni, N. Hypernatremia in newborns: a practical approach to management. Biomed. Hub. 7, 55–69 (2022).

    Google Scholar 

  69. Gomella, T., Cunningham, M., Eyal, F. G. & Tuttle, D. J. Hyperkalemia In Neonatology: Management, Procedures, On-call Problems, Diseases, And Drugs 7th edn (McGraw Hill, 2013).

  70. Vemgal, P. & Ohlsson, A. Interventions for non-oliguric hyperkalaemia in preterm neonates. Cochrane Database Syst. Rev. 5, CD005257 (2012).

    Google Scholar 

  71. Sakr, M. & Balasundaram, P. Neonatal Therapeutic Hypothermia (StatPearls Publishing, 2021).

  72. Chung, H. U. et al. Binodal, wireless epidermal electronic systems with in-sensor analytics for neonatal intensive care. Science 363, eaau0780 (2019).

    Google Scholar 

  73. Chung, H. U. et al. Skin-interfaced biosensors for advanced wireless physiological monitoring in neonatal and pediatric intensive-care units. Nat. Med. 26, 418–429 (2020). This article describes wireless, skin-interfaced sensors for physical signal monitoring in neonatal and paediatric intensive-care units.

    Google Scholar 

  74. Garcia-Carmona, L. et al. Pacifier biosensor: toward noninvasive saliva biomarker monitoring. Anal. Chem. 91, 13883–13891 (2019).

    Google Scholar 

  75. Lim, H.-R. et al. Smart bioelectronic pacifier for real-time continuous monitoring of salivary electrolytes. Biosens. Bioelectron. 210, 114329 (2022).

    Google Scholar 

  76. Catrysse, M. et al. Towards the integration of textile sensors in a wireless monitoring suit. Sens. Actuators Phys. 114, 302–311 (2004).

    Google Scholar 

  77. Cay, G. et al. An e-textile respiration sensing system for NICU monitoring: design and validation. J. Signal. Process. Syst. 94, 543–557 (2022).

    Google Scholar 

  78. Chen, W. et al. Design of an integrated sensor platform for vital sign monitoring of newborn infants at neonatal intensive care units. J. Healthc. Eng. 1, 535–554 (2010).

    Google Scholar 

  79. Joglekar, A. et al. A wearable sensor for monitoring kangaroo mother care treatment for premature neonates. In 2018 IEEE Sensors https://doi.org/10.1109/ICSENS.2018.8589633 (IEEE, 2018).

  80. Jeong, H. et al. Miniaturized wireless, skin-integrated sensor networks for quantifying full-body movement behaviors and vital signs in infants. Proc. Natl Acad. Sci. USA 118, e2104925118 (2021). This article describes miniaturized and time-synchronized devices for body movement tracking in infants.

    Google Scholar 

  81. Kwak, S. S. et al. Skin-integrated devices with soft, holey architectures for wireless physiological monitoring, with applications in the neonatal intensive care unit. Adv. Mater. 33, 2103974 (2021).

    Google Scholar 

  82. Jinkins, K. R. et al. Thermally switchable, crystallizable oil and silicone composite adhesives for skin-interfaced wearable devices. Sci. Adv. 8, eabo0537 (2022).

    Google Scholar 

  83. Nie, S. et al. Soft, stretchable thermal protective substrates for wearable electronics. npj Flex. Electron. 6, 36 (2022). This article reports soft, stretchable thermal protective materials for the substrates of wearable electronics.

    Google Scholar 

  84. Yoo, S. et al. Responsive materials and mechanisms as thermal safety systems for skin-interfaced electronic devices. Nat. Commun. 14, 1024 (2023).

    Google Scholar 

  85. Liu, C. et al. Multifunctional materials strategies for enhanced safety of wireless, skin-interfaced, bioelectronic devices. Adv. Funct. Mater https://doi.org/10.1002/adfm.202302256 (2023).

    Article  Google Scholar 

  86. Cho, D. et al. Bitter flavored, soft composites for wearables designed to reduce risks of choking in infants. Adv. Mater. 33, 2103857 (2021).

    Google Scholar 

  87. Wang, C. et al. Multifunctional biosensors made with self-healable silk fibroin imitating skin. ACS Appl. Mater. Interf. 13, 33371–33382 (2021).

    Google Scholar 

  88. Jang, K.-I. et al. Rugged and breathable forms of stretchable electronics with adherent composite substrates for transcutaneous monitoring. Nat. Commun. 5, 4779 (2014).

    Google Scholar 

  89. Choi, J. et al. Artificial stretchable armor for skin-interfaced wearable devices and soft robotics. Extreme Mech. Lett. 50, 101537 (2022).

    Google Scholar 

  90. Ray, T. et al. Soft, skin-interfaced sweat stickers for cystic fibrosis diagnosis and management. Sci. Transl. Med. 13, eabd8109 (2021). This article describes skin-interfaced sensors for chemical signal monitoring in paediatric patients.

    Google Scholar 

  91. Chen, W., Sonntag, C., Boesten, F., Oetomo, S. B. & Feijs, L. A design of power supply for neonatal monitoring with wearable sensors. J. Ambient. Intell. Smart Environ. 1, 185–196 (2009).

    Google Scholar 

  92. Rwei, A. et al. A wireless, skin-interfaced biosensor for cerebral hemodynamic monitoring in pediatric care. Proc. Natl Acad. Sci. USA 117, 31674–31684 (2020).

    Google Scholar 

  93. Poole, A. E. & Macko, D. J. Pediatric vital signs: recording methods and interpretations. Pediatr. Dent. 6, 10–16 (1984).

    Google Scholar 

  94. Evans, D., Hodgkinson, B. & Berry, J. Vital signs in hospital patients: a systematic review. Int. J. Nurs. Stud. 38, 643–650 (2001).

    Google Scholar 

  95. Di Rienzo, M. et al. Wearable seismocardiography: towards a beat-by-beat assessment of cardiac mechanics in ambulant subjects. Auton. Neurosci. 178, 50–59 (2013).

    Google Scholar 

  96. Preeti, M., Koushik, G., Baishnab, K. L., Dusarlapudi, K. & Narasimha Raju, K. Low frequency MEMS accelerometers in health monitoring — a review based on material and design aspects. Mater. Today Proc. 18, 2152–2157 (2019).

    Google Scholar 

  97. Cristina Oliveira, R., Gama, A. C. C. & Magalhães, M. D. C. Fundamental voice frequency: acoustic, electroglottographic, and accelerometer measurement in individuals with and without vocal alteration. J. Voice 35, 174–180 (2021).

    Google Scholar 

  98. Smith, A. D. H., Crabtree, D. R., Bilzon, J. L. J. & Walsh, N. P. The validity of wireless iButtons® and thermistors for human skin temperature measurement. Physiol. Meas. 31, 95–114 (2009).

    Google Scholar 

  99. Dollberg, S., Rimon, A., Atherton, H. D. & Hoath, S. B. Continuous measurement of core body temperature in preterm infants. Am. J. Perinatol. 17, 257–264 (2000).

    Google Scholar 

  100. Wang, C. et al. Advanced carbon for flexible and wearable electronics. Adv. Mater. 31, 1801072 (2019).

    Google Scholar 

  101. Porter, P. et al. Accuracy, clinical utility, and usability of a wireless self-guided fetal heart rate monitor. Obstet. Gynecol. 137, 673–681 (2021).

    Google Scholar 

  102. Boatin, A. et al. Wireless fetal heart rate monitoring in inpatient full-term pregnant women: testing functionality and acceptability. PLoS One 10, e0117043 (2015).

    Google Scholar 

  103. Yang, W. et al. Fetal heart rate monitoring system with mobile internet. 2014 IEEE Int. Symp. Circuits and Systems (ISCAS) 443–446 (IEEE, 2014).

  104. US National Library of Medicine Clinical Trials.gov https://clinicaltrials.gov/ct2/show/NCT05147584 (2022).

  105. Cohen, W. R. et al. Accuracy and reliability of fetal heart rate monitoring using maternal abdominal surface electrodes. Acta Obstet. Gynecol. Scand 91, 1306–1313 (2012).

    Google Scholar 

  106. Schwartz, N. et al. Novel uterine contraction monitoring to enable remote, self-administered nonstress testing. Am. J. Obstet. Gynecol. 226, 554.e1–554.e12 (2021).

    Google Scholar 

  107. Lai, J. et al. Performance of a wearable acoustic system for fetal movement discrimination. PLoS One 13, e0195728 (2018).

    Google Scholar 

  108. Xu, S. et al. Wireless skin sensors for physiological monitoring of infants in low-income and middle-income countries. Lancet Digit. Health 3, e266–e273 (2021). This article describes physiological monitoring devices for the care of vulnerable patients in low-resource regions.

    Google Scholar 

  109. Vogl, J. et al. Kangaroo father care: a pilot feasibility study of physiologic, biologic, and psychosocial measures to capture the effects of father–infant and mother–infant skin-to-skin contact in the Neonatal Intensive Care Unit. Dev. Psychobiol. 63, 1521–1533 (2021).

    Google Scholar 

  110. Inamori, G. et al. Neonatal wearable device for colorimetry-based real-time detection of jaundice with simultaneous sensing of vitals. Sci. Adv. 7, eabe3793 (2021).

    Google Scholar 

  111. Kim, Y.-S. et al. Wireless, skin-like membrane electronics with multifunctional ergonomic sensors for enhanced pediatric care. IEEE Trans. Biomed. Eng. 67, 2159–2165 (2019).

    Google Scholar 

  112. Chen, H. et al. Design of an integrated wearable multi-sensor platform based on flexible materials for neonatal monitoring. IEEE Access. 8, 23732–23747 (2020).

    Google Scholar 

  113. Airaksinen, M. et al. Automatic posture and movement tracking of infants with wearable movement sensors. Sci. Rep. 10, 169 (2020). This article describes an e-textile form factor that allows mobile accelerometer and gyroscope data collection during infant movements.

    Google Scholar 

  114. Chun, K. S. et al. A skin-conformable wireless sensor to objectively quantify symptoms of pruritus. Sci. Adv. 7, eabf9405 (2021).

    Google Scholar 

  115. Yang, A. F. et al. Validation of a hand-mounted wearable sensor for scratching movements in adults with atopic dermatitis. J. Am. Acad. Dermatol 88, 726–729 (2023).

    Google Scholar 

  116. Farooq, M., Chandler-Laney, P. C., Hernandez-Reif, M. & Sazonov, E. Monitoring of infant feeding behavior using a jaw motion sensor. J. Healthc. Eng. 6, 23–40 (2015).

    Google Scholar 

  117. Grassi, A. et al. Sensorized pacifier to evaluate non-nutritive sucking in newborns. Med. Eng. Phys. 38, 398–402 (2016).

    Google Scholar 

  118. Ibrahim, Z. H. et al. Wireless multichannel electroencephalography in the newborn. J. Neonatal-Perinat. Med. 9, 341–348 (2016).

    Google Scholar 

  119. McKinlay, C. J. D. et al. Continuous glucose monitoring in neonates: a review. Matern. Health Neonatol. Perinatol. 3, 18 (2017).

    Google Scholar 

  120. Foster, K. G., Hey, E. N. & Katz, G. The response of the sweat glands of the new‐born baby to thermal stimuli and to intradermal acetylcholine. J. Physiol. 203, 13–29 (1969).

    Google Scholar 

  121. Hardy, J. D., Davison, S. H., Higgins, M. U. & Polycarpou, P. N. Sweat tests in the newborn period. Arch. Dis. Child. 48, 316 (1973).

    Google Scholar 

  122. Kim, J. et al. A skin-interfaced, miniaturized microfluidic analysis and delivery system for colorimetric measurements of nutrients in sweat and supply of vitamins through the skin. Adv. Sci. 9, 2103331 (2022).

    Google Scholar 

  123. Imani, S. et al. A wearable chemical–electrophysiological hybrid biosensing system for real-time health and fitness monitoring. Nat. Commun. 7, 11650 (2016).

    Google Scholar 

  124. Kim, S. et al. Soft, skin-interfaced microfluidic systems with integrated immunoassays, fluorometric sensors, and impedance measurement capabilities. Proc. Natl Acad. Sci. USA 117, 27906–27915 (2020).

    Google Scholar 

  125. Zhang, Y. et al. Passive sweat collection and colorimetric analysis of biomarkers relevant to kidney disorders using a soft microfluidic system. Lab Chip 19, 1545–1555 (2019).

    Google Scholar 

  126. Koh, A. et al. A soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat. Sci. Transl. Med. 8, 366ra165 (2016).

    Google Scholar 

  127. Emaminejad, S. et al. Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform. Proc. Natl Acad. Sci. 114, 4625–4630 (2017).

    Google Scholar 

  128. Lee, H. et al. Wearable/disposable sweat-based glucose monitoring device with multistage transdermal drug delivery module. Sci. Adv. 3, e1601314 (2017).

    Google Scholar 

  129. Bandodkar, A. J. et al. Battery-free, skin-interfaced microfluidic/electronic systems for simultaneous electrochemical, colorimetric, and volumetric analysis of sweat. Sci. Adv. 5, eaav3294 (2019).

    Google Scholar 

  130. Liu, Y.-L. et al. Flexible electrochemical urea sensor based on surface molecularly imprinted nanotubes for detection of human sweat. Anal. Chem. 90, 13081–13087 (2018).

    Google Scholar 

  131. Hussain, S. & Park, S. Sweat-based noninvasive skin-patchable urea biosensors with photonic interpenetrating polymer network films integrated into PDMS chips. ACS Sens. 5, 3988–3998 (2020).

    Google Scholar 

  132. Symon, A. F., Hassan, N., Rashid, H., Ahmed, I. U. & Taslim Reza, S. M. Design and development of a smart baby monitoring system based on Raspberry Pi and Pi camera. In 2017 4th Int. Conf. on Advances in Electrical Engineering (ICAEE) 117–122 (IEEE, 2017).

  133. Wang, A., Sunshine, J. E. & Gollakota, S. Contactless infant monitoring using white noise. In 25th Ann. Int. Conf. Mobile Computing and Networking https://doi.org/10.1145/3300061.3345453 (Association for Computing Machinery, 2019).

  134. Pallin, M. et al. Comparison of a novel non-contact biomotion sensor with wrist actigraphy in estimating sleep quality in patients with obstructive sleep apnoea. J. Sleep Res. 23, 475–484 (2014).

    Google Scholar 

  135. De Chazal, P. et al. Sleep/wake measurement using a non-contact biomotion sensor. J. Sleep Res. 20, 356–366 (2011).

    Google Scholar 

  136. Yue, S., Yang, Y., Wang, H., Rahul, H. & Katabi, D. BodyCompass: monitoring sleep posture with wireless signals. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4, 66 (2020).

    Google Scholar 

  137. Hsu, C.-Y. et al. Zero-effort in-home sleep and insomnia monitoring using radio signals. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 59 (2017).

    Google Scholar 

  138. Knowles, M., Krasniansky, A. & Nagappan, A. Consumer adoption of digital health in 2022: moving at the speed of trust. RockHealth https://rockhealth.com/insights/consumer-adoption-of-digital-health-in-2022-moving-at-the-speed-of-trust/ (2023).

Download references

Acknowledgements

We especially thank H. Jeong for providing advice on maternal health. J.K. acknowledges support from the KIST Institutional Program (project numbers 2E32341 and 2E32349) and the National Research Foundation of Korea (NRF) funded by the Korean government (MSIT) (grant number RS-2023–00211342). S.S.K. acknowledges support from the KIST Institutional Program (project number 2E32341).

Author information

Authors and Affiliations

Authors

Contributions

J.K., S.Y., C.L. and S.S.K. contributed equally to the figure design and manuscript writing. J.R.W. and S.X. reviewed the article. J.A.R. wrote, edited and reviewed the article. All authors contributed to the discussion.

Corresponding author

Correspondence to John A. Rogers.

Ethics declarations

Competing interests

S.X. and J.A.R. are co-founders and S.X. is an employee at a startup company (Sibel Health) that is involved in commercialization of some of the technologies covered by this Review. J.R.W. has a spouse with a commercial interest in the technologies described in this Review. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Reviews Bioengineering thanks Alex Chortos, Martin Kaltenbrunner, Do Hwan Kim and Carolyn Lund for their contribution to the peer review of this work.

Additional information

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

Related links

General Data Protection Regulation: https://gdpr-info.eu/

HITRUST/SOC2: https://hitrustalliance.net/; https://soc2.co.uk/

NEST360°: https://www.unicef.org/supply/media/2931/file/pulse-oximeter-TPP.pdf

Rights and permissions

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

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, J., Yoo, S., Liu, C. et al. Skin-interfaced wireless biosensors for perinatal and paediatric health. Nat Rev Bioeng 1, 631–647 (2023). https://doi.org/10.1038/s44222-023-00090-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s44222-023-00090-0

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing