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Thermometry and interpretation of body temperature

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Abstract

This article reviews the historical development and up-to-date state of thermometric technologies for measuring human body temperature (BT) from two aspects: measurement methodology and significance interpretation. Since the first systematic and comprehensive study on BT and its relation to human diseases was conducted by Wunderlich in the late 19th century, BT has served as one of the most fundamental vital signs for clinical diagnosis and daily healthcare. The physiological implication of BT set point and thermoregulatory mechanisms are briefly outlined. Influential determinants of BT measurement are investigated thoroughly. Three types of BT measurement, i.e., core body temperature, surface body temperature and basal body temperature, are categorized according to its measurement position and activity level. With the comparison of temperature measurement in industrial fields, specialties in technological and biological aspects in BT measurement are mentioned. Methodologies used in BT measurement are grouped into instrumental methods and mathematical methods. Instrumental methods utilize results of BT measurements directly from temperature-sensitive transducers and electronic instrumentations by the combination of actual and predictive measurement, invasive and noninvasive measurement. Mathematical methods use several numerical models, such as multiple regression model, autoregressive model, thermoregulatory mechanism-based model and the Kalman filter-based method to estimate BT indirectly from some relevant vital signs and environmental factors. Thermometry modalities are summarized on the dichotomies into invasive and noninvasive, contact and noncontact, direct and indirect, free and restrained, 1-D and n-D. Comprehensive interpretation of BT has an equal importance as the measurement of BT. Two modes to apply BT are classified into real-time applications and long-term applications. With rapid advancement in IoT infrastructure, big data analytics and AI platforms, prospects for future development in thermometry and interpretation of BT are discussed.

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  • 25 February 2019

    The author would like to add “ⓒTogawa T.” in the figure 1 caption for the online published article.

References

  1. Bianconi E, Piovesan A, Facchin F, Beraudi A, Casadei R, Frabetti F, Vitale L, Pelleri MC, Tassani S, Piva F, Perez-Amodio S, Strippoli P, Canaider S. An estimation of the number of cells in the human body. Ann Hum Biol. 2013;40(6):463–71.

    Article  Google Scholar 

  2. Wunderlich CA. On the temperature in diseases: a manual of medical thermometry. Oxford: The New Sydenham Society; 1871.

    Google Scholar 

  3. Mackowiak PA, Worden G. Carl reinhold August Wunderlich and the evolution of clinical thermometry. Clin Infect Dis. 1994;18(3):458–67.

    Article  Google Scholar 

  4. Cabej NR. Epigenetic principles of evolution—1. control systems and determination of phenotypic traits in Metazoans. In Cabej NR, editor. Amsterdam: Elsevier; 2012; 3:38.

  5. Kelly GS. Body temperature variability (Part 1): a review of the History of body temperatureand its variability due to site selection, biological rhythms, fitness, and aging. Altern Med Rev. 2006;11(4):278–93.

    Google Scholar 

  6. Kelly GS. Body temperature variability (Part 2): masking influences of body temperature variability and a review of body temperature variability in disease. Altern Med Rev. 2007;12(1):49–62.

    MathSciNet  Google Scholar 

  7. Sund-Levander M, Forsberg C, Wahren LK. Normal oral, rectal, tympanic and axillary body temperature in adult men and women: a systematic literature review. Scand J Caring Sci. 2002;16:122–8.

    Article  Google Scholar 

  8. Traditional Chinese medicine undisclosed recipe network. On the application of “cold head and warm feet. 21 July 2017. http://www.21nx.com/21nx/html/zhuanti/zhongyiyangsheng/2017/0721/62178.html. Accessed 28 Nov 2018.

  9. Gao D. A collection of Chinese ancient medical works unearthed in 20th Century—commentary on Mountain Zhang Jia’s inscribed bamboo slips “Pulseology”, Chengdu, China. Chengdu: Chengdu Publishing Company; 1992.

    Google Scholar 

  10. Wikipedia. Ole Rømer. Accessed 23 Nov 2018. https://en.wikipedia.org/wiki/Ole_R%C3%B8mer. Accessed 1 Dec 2018.

  11. Timetoast timelines. History of the Thermometer. https://media.timetoast.com/timelines/history-of-the-thermometer–9.Accessed 1 Dec 2018.

  12. Neuman MR. Measurement of vital signs:temperature. IEEE Pulse. 2010;1(2):40–9.

    Article  Google Scholar 

  13. McNamara GA. Semiconductor diodes and transistors as electrical thermometers. Rev Sci Instrum. 1962;33(3):330–3.

    Article  Google Scholar 

  14. Cohen BG, Snow WB, Tretola AR. GaAs p-n junction diodes for wide range thermometry. Rev Sci Instrum. 1963;34(10):1091–3.

    Article  Google Scholar 

  15. Tagawa T, Tamura T, Oberg AP. Biomedical sensors and instruments. Boca Raton: CRC Press; 2011.

    Google Scholar 

  16. Verster CT. P-N junction as an ultralinear calculable thermometer. Electron Lett. 1968;4(9):175–6.

    Article  Google Scholar 

  17. Ruhle AR. Solid-state temperature sensor outperforms previous transducers. Electronics. 1975;48(6):127–30.

    Google Scholar 

  18. Kim M-Y, Oh T-S. Thermoelectric characteristics of the thermopile sensors with variations of the width and the thickness of the electrodeposited Bismuth–Telluride and Antimony–Telluride thin films. Mater Trans. 2010;51(10):1909–13.

    Article  Google Scholar 

  19. Rogalski, A. Next decade in infrared detectors in Proc. SPIE 10433. Electro-optical and Infrared systems: technology and applications. Warsaw, Poland; 2017.

  20. Terumo Corporation. Terumo moves from Mercury to electronic thermometers. http://www.terumo.com/about/terumostory/1921_2001/cat5_2.html.

  21. O’Brien DL, Rogers IR, Holden W, Jacobs I, Mellett S, Wall EJ, Davies D. The accuracy of oral predictive and infrared emission detection tympanic thermometers in an emergency department setting. Acad Emerg Med. 2000;7(9):1061–4.

    Article  Google Scholar 

  22. Monnard C, Fares E-J, Calonne J, Miles-Chan J, Montani J-P, Durrer D, Schutz Y, Dulloo A. Issues in continuous 24-h core body temperature monitoring in Humans using an ingestible capsule telemetric sensor. Front Endocrinol. 2017;8:130–42.

    Article  Google Scholar 

  23. Lim CL, Byrne C, Lee JK. Human thermoregulation and measurement of body temperature in exercise and clinical settings. Ann Acad Med Singapore. 2008;37:347–53.

    Google Scholar 

  24. Cooper KE, Cranston WI, Snell ES. Temperature in the external auditory meatus as an index of central temperature changes. J Appl Physiol. 1964;19(5):1032–5.

    Article  Google Scholar 

  25. Grassl T, Ventur M, Koch J, Sattler F. Double temperature sensor. USA atent US 8,708,926 B2. 29 Apr 2014.

  26. Fox RH, Solman AJ, Isaacs R, Fry AJ, MacDonald IC. A new method for monitoring deep body temperature from the skin surface. Clin Sci. 1973;4:81–6.

    Article  Google Scholar 

  27. Kobayashi T, Nemoto T, Kamiya A, Togawa T. Improvement of deep body thermometer for man. Ann Biomed Eng. 1975;3(2):181–8.

    Article  Google Scholar 

  28. Nemoto T, Togawa T. Improved probe for a deep body thermometer. Med Biol Eng Comput. 1988;26(7):456–9.

    Article  Google Scholar 

  29. Kitamura K-I, Zhu X, Chen W, Nemoto T. Development of a new method for the noninvasive measurement of deep body temperature without a heater. Med Eng Phys. 2010;32(1):1–6.

    Article  Google Scholar 

  30. Huang M, Chen W. Theoretical study on the inverse modeling of deep body temperature measurement. Physiol Meas. 2012;33:429–43.

    Article  Google Scholar 

  31. Huang M, Tamura T, Tang Z, Chen W, Kanaya S. Structural optimization of a wearable deep body thermometer: from theoretical simulation to experimental verification. J Sens. 2016;2016:1–7.

    Google Scholar 

  32. Rodbard S. Body temperature, blood pressure, and hypothalamus. Science. 1948;108(2807):413–5.

    Article  Google Scholar 

  33. Jensen MM, Brabrand M. The relationship between body temperature, heart rate and respiratory rate in acute patients at admission to a medical care unit. Scand J Trauma, Resusc Emerg Med. 2015;23:A12.

    Article  Google Scholar 

  34. Richmond VL, Davey S, Griggs K, Havenith G. Prediction of core body temperature from multiple variables. Ann Occup Hyg. 2015;59(9):1168–78.

    Article  Google Scholar 

  35. Gribok AV, Buller MJ, Reifman J. Individualized short-term core temperature prediction in humans using biomathematical models. IEEE Trans BME. 2008;55(5):1477–87.

    Article  Google Scholar 

  36. Gribok AV, Rumpler W, Buller M, Hoyt R. Predicting core temperature in humans using autoregressive model with exogenous inputs. The FASEB Journal. 2011;25:1052–3.

    Google Scholar 

  37. Gribok AV, Buller MJ, Hoyt RW, Reifman J. A real-time algorithm for predicting core temperature in Humans. IEEE Trans Inf Technol Biomed. 2010;14(4):1039–45.

    Article  Google Scholar 

  38. Yokota M, Berglund L, Cheuvron S, Santee W, Latzka W, Montain S, Kolka M, Moran D. Thermoregulatory model to predict physiological status from ambient environment and heart rate. Comput Biol Med. 2008;38:1187–93.

    Article  Google Scholar 

  39. Buller MJ, Tharion WJ, Cheuvront SN, Montain SJ, Kenefick RW, Castellani J, Latzka WA, Roberts WS, Richter M, Jenkins OC, Hoyt RW. Estimation of human core temperature from sequential heart rate observations. Physiol Meas. 2013;34:781–98.

    Article  Google Scholar 

  40. Sim S, Yoon H, Ryou H, Park K. Estimation of body temperature rhythm based on heart activity parameters in daily life. in 36th annual International conference of the IEEE Engineering in Medicine and Biology Society, 2014. Chicago, Illinois, USA.

  41. Tamura T, Huang M, Togawa T. Body Temperature, Heat Flow, and Evaporation. in Seamless Health care Monitoring. Springer International Publishing AG. 2018; 281-307.

  42. de Souza MA, Paz AAC, Sanches IJ, Nohama P, Gamba HR. 3D Thermal medical image visualization tool: Integration between MRI and thermographic images in 36th annual International conference of the IEEE Engineering in Medicine and Biology Society, 2014. Chicago, IL, USA.

  43. Horvath SM, Menduke H, Piersol GM. Oral and rectal temperatures of man. JAMA. 1950;144(18):1562–5.

    Article  Google Scholar 

  44. Mackowiak PA, Wasserman SS, Levine MM. A critical appraisal of 98.6F, the upper limit of the normal body temperature, and other legacies of Carl Reinhold August Wunderlich. JAMA. 1992;268(12):1578–80.

    Article  Google Scholar 

  45. Wikipedia. Human body temperature. https://en.wikipedia.org/wiki/Human_body_temperature#cite_note-pmid18788094-2. Accessed 5 Dec 2018.

  46. Longo DL, Fauci A, Kasper D, Hauser S, Jameson J, Loscalzo J. Harrison’s principles of internal medicine, (18 ed.). New York: McGraw-Hill; 2011. p. 4012.

    Google Scholar 

  47. Asayama M. Guideline for the prevention of heat disorder in Japan. Global Environ Res. 2009;13(1):19–25.

    Google Scholar 

  48. Gunga H-C, Sandsund M, Reinertsen RE, Sattler F, Koch J. A non-invasive device to continuously determine heat strain in humans. J Therm Biol. 2008;33:297–307.

    Article  Google Scholar 

  49. Çam R, Yönem H, Özsoy H. Core body temperature changes during surgery and nursing management. Clin Med Res. 2016;5(2–1):1–5.

    Google Scholar 

  50. Habash R, Bansal R, Krewski D, Alhafid H. Thermal therapy, part 1: an introduction to thermal therapy. Crit Rev Biomed Eng. 2006;34(6):459–89.

    Article  Google Scholar 

  51. Habash R, Bansal R, Krewski D, Alhafid H. Thermal therapy, part 2: hyperthermia techniques. Crit Rev Biomed Eng. 2006;34(6):451–542.

    Google Scholar 

  52. Healthline media. Benefits of Cryotherapy.https://www.healthline.com/health/cryotherapy-benefits. Accessed 1 Dec 2018.

  53. Bleakley CM, Bieuzen F, Davison GW, Costello JT. Whole-body cryotherapy: empirical evidence and theoretical perspectives. Open Access J Sports Med. 2014;5:25–36.

    Article  Google Scholar 

  54. Huang M, Chen W, Nemoto T. Core temperature rhythm of bedridden patients with sequelae of cerebral infarction in the 49th annual conference of Japanese society of medical and biomedical engineering. Osaka, Japan. 2010.

  55. Huang M, Tamura T, Chen W, Kitamura K, Nemo T, Kanaya S. Characterization of ultradian and circadian rhythms of core body temperature based on wavelet analysis in Conf Proc IEEE Eng Med Biol Soc. 2014. Chicago, Illinois, USA.

  56. Chen W, Kitazawa M, Togawa T. HMM-based estimation of menstrual cycle from skin temperature during sleep in 30th annual International IEEE EMBS conference. Vancouver, British Columbia, Canada. 20–24 Aug 2008.

  57. Chen W, Kitazawa M, Togawa T. Estimation of the biphasic property in a female’s menstrual cycle from cutaneous temperature measured during sleep. Ann Biomed Eng. 2009;37(9):1827–38.

    Article  Google Scholar 

  58. Ran’s Night. QOL Corporation. http://rans-night.jp/. Accessed 13 Nov 2018.

  59. Lack L, Gradisar M, Van Someren E, Wright H, Lushington K. The relationship between insomnia and body temperatures. Sleep Med Rev. 2008;12(4):307–17.

    Article  Google Scholar 

  60. Halberg F. Chronobiology. Ann Rev Physiol. 1969;31:675–725.

    Article  Google Scholar 

  61. Nippon Avionics Co., Ltd. Thermo Mirror SX-01 series. http://www.avio.co.jp/jp/news/2011/0111-thermo-mirror.html.Accessed 11 Dec 2018.

  62. Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, Brilliant L. Detecting influenza epidemics using search engine query data. Nature. 2009;457:1012–4.

    Article  Google Scholar 

  63. Halberg F, Cornélissen G. Rhythms and blood pressure. Ann 1st Super Sanita. 1993;29(4):647–65.

    Google Scholar 

  64. Halberg F, Cornélissen G, Wang Z, Wan C, Ulmer W, Katinas G, Singh R, Singh R, Singh RK, Gupta B, Singh R, Kumar A, Kanabrocki E, Sothern RB, Rao G, Bhatt ML, Srivastava M, Rai G, Singh S, Pati AK, Nath P, Halberg F, Halberg J, Schwartzkopff O, Bakken E, Shastri SVK. Chronomics: circadian and circaseptan timing of radiotherapy, drugs, calories, perhaps nutriceuticals and beyond. J Exp Ther Oncol. 2003;3(5):223–60.

    Article  Google Scholar 

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Funding

This study was supported in part by the Competitive Research Fund 2018-P-14 of the University of Aizu.

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  1. Biomedical Information Technology Laboratory, Research Center for Advanced Information Science and Technology, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Wenxi Chen

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Correspondence to Wenxi Chen.

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Chen, W. Thermometry and interpretation of body temperature. Biomed. Eng. Lett. 9, 3–17 (2019). https://doi.org/10.1007/s13534-019-00102-2

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