Thermometry and interpretation of body temperature
Open accessAbstract
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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The body temperature of an animal is closely related to its basal metabolic rate.
“The body temperature of an animal is closely related to its basal metabolic rate (Chen, 2019).”
From Body temperatures of <i>Manis pentadactyla</i> and <i>Manis javanica</i> (2021) · cites this paper as Chen, 2019
Section 1.1 links human body temperature to metabolic activity, stating that body temperature reflects thermal energy generated by metabolism. It does not specifically discuss basal metabolic rate or establish this relationship for animals generally. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe low body temperatures in pangolins are possibly due to the low metabolic rates of the species.
“The low body temperatures in pangolins are possibly due to the low metabolic rates of species.”
From Body temperatures of <i>Manis pentadactyla</i> and <i>Manis javanica</i> (2021) · cites this paper as Chen, 2019
Section 1.1 (page unavailable) links human body temperature to heat generated by metabolism, supporting the general physiological connection. The paper does not address pangolins or establish that their low body temperatures may result from low metabolic rates; searches for pangolins and species-specific metabolic rates found no such passage. (LLM, conf=0.77)
Experimental — accuracy not yet measuredIndirect core body temperature evaluation can achieve a high accuracy of ±0.03 °C.
“From these data, the internal core body temperature is evaluated with a high accuracy of ±0.03 °C [129,140,146,147,148,149].”
From The Current State of Optical Sensors in Medical Wearables (2022) · cites this paper as [140]
Core temperature changes are affected by circadian rhythms.
“Core temperature changes are affected by circadian rhythms.”
From The Current State of Optical Sensors in Medical Wearables (2022) · cites this paper as [140]
Continuous measurement of core body temperature can determine the patient's circadian cycle.
“From continuous measurements of core body temperature, we can determine the circadian cycle of the patient.”
From The Current State of Optical Sensors in Medical Wearables (2022) · cites this paper as [140]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Harrison's Principles of Internal Medicine.
(1988) · Annals of Internal Medicine · doi:10.7326/0003-4819-108-3-499_2 · Cited by 12,528 · see citing works
Detecting influenza epidemics using search engine query data
Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S., & Brilliant, L. (2009) · Nature · doi:10.1038/nature07634 · Cited by 4,295 · see citing works
An estimation of the number of cells in the human body
Bianconi, E., Piovesan, A., Facchin, F., Beraudi, A., Casadei, R., Frabetti, F., Vitale, L., Pelleri, M. C., Tassani, S., Piva, F., et al. (2013) · Annals of Human Biology · doi:10.3109/03014460.2013.807878 · Cited by 1,012 · see citing works
Halberg, F. E. (1969) · Annual Review of Physiology · doi:10.1146/annurev.ph.31.030169.003331 · Cited by 700 · see citing works
Sund‐Levander, M., Forsberg, C., & Wahren, L. K. (2002) · Scandinavian Journal of Caring Sciences · doi:10.1046/j.1471-6712.2002.00069.x · Cited by 514 · see citing works
Mackowiak, P. A. (1992) · JAMA · doi:10.1001/jama.268.12.1578 · Cited by 449 · see citing works
Mackowiak, P. A. (1992) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.1992.03490120092034 · Cited by 419 · see citing works
Human Thermoregulation and Measurement of Body Temperature in Exercise and Clinical Settings
Lim, C. L., Byrne, C., & LEE, J. K. W. (2008) · Annals of the Academy of Medicine Singapore · doi:10.47102/annals-acadmedsg.v37n4p347 · Cited by 374 · see citing works
Thermal Therapy, Part 1: An Introduction to Thermal Therapy
Habash, R. W. Y., Bansal, R., Krewski, D. R., et al. (2006) · Critical Reviews in Biomedical Engineering · doi:10.1615/critrevbiomedeng.v34.i6.20 · Cited by 349 · see citing works
The relationship between insomnia and body temperatures
Lack, L. C., Gradisar, M., Van Someren, E. J. W., Wright, H. R., & Lushington, K. (2008) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2008.02.003 · Cited by 285 · see citing works
Thermal Therapy, Part 2: Hyperthermia Techniques
Habash, R. W. Y., Bansal, R., Krewski, D. R., et al. (2006) · Critical Reviews in Biomedical Engineering · doi:10.1615/critrevbiomedeng.v34.i6.30 · Cited by 234 · see citing works
Estimation of human core temperature from sequential heart rate observations
Buller, M. J., Tharion, W. J., Cheuvront, S. N., Montain, S. J., Kenefick, R. W., Castellani, J. W., Latzka, W. A., Roberts, W. S., Richter, M., Jenkins, O. C., et al. (2013) · Physiological Measurement · doi:10.1088/0967-3334/34/7/781 · Cited by 172 · see citing works
A New Method for Monitoring Deep Body Temperature from the Skin Surface
Fox, R. H., Solman, A., Isaacs, R., Fry, A. J., & MacDonald, I. C. (1973) · Clinical Science · doi:10.1042/cs0440081 · Cited by 169 · see citing works
Whole-body cryotherapy: empirical evidence and theoretical perspectives
Bleakley, C., Bieuzen, F., Davison, G. W., & Costello, J. T. (2014) · Open Access Journal of Sports Medicine · doi:10.2147/oajsm.s41655 · Cited by 137 · see citing works
A non-invasive device to continuously determine heat strain in humans
Gunga, H.-C., Sandsund, M., Reinertsen, R. E., Sattler, F., & Koch, J. (2008) · Journal of Thermal Biology · doi:10.1016/j.jtherbio.2008.03.004 · Cited by 129 · see citing works
Next decade in infrared detectors
Rogalski, A. (2017) · doi:10.1117/12.2300779 · Cited by 115 · see citing works
On the Temperature in Diseases: A Manual of Medical Thermometry
Wunderlich, C., & Woodman, W. B. (2010) · Cited by 98 · see citing works
Kitamura, K., Zhu, X., Chen, W., & Nemoto, T. (2009) · Medical Engineering & Physics · doi:10.1016/j.medengphy.2009.09.004 · Cited by 98 · see citing works
Self-citationTemperature in the external auditory meatus as an index of central temperature changes
Cooper, K., Cranston, W. I., & Snell, E. S. (1964) · Journal of Applied Physiology · doi:10.1152/jappl.1964.19.5.1032 · Cited by 96 · see citing works
Carl Reinhold August Wunderlich and the Evolution of Clinical Thermometry
Mackowiak, P. A., & Worden, G. (1994) · Clinical Infectious Diseases · doi:10.1093/clinids/18.3.458 · Cited by 89 · see citing works
Prediction of Core Body Temperature from Multiple Variables
Richmond, V. L., Davey, S., Griggs, K., & Havenith, G. (2015) · The Annals of Occupational Hygiene · doi:10.1093/annhyg/mev054 · Cited by 73 · see citing works
Semiconductor Diodes and Transistors as Electrical Thermometers
McNamara, A. G. (1962) · Review of Scientific Instruments · doi:10.1063/1.1717834 · Cited by 70 · see citing works
Kelly, G. S. (2007) · PubMed · Cited by 61 · see citing works
Improvement of deep body thermometer for man
Kobayashi, T., Nemoto, T., Kamiya, A., & Togawa, T. (1975) · Annals of Biomedical Engineering · doi:10.1007/bf02363069 · Cited by 56 · see citing works
Wave Height Estimation from Shipborne X-Band Nautical Radar Images
Liu, X., Huang, W., & Gill, E. W. (2015) · Journal of Sensors · doi:10.1155/2016/1078053 · Cited by 54 · see citing works
GaAs p-n Junction Diodes for Wide Range Thermometry
Cohen, B. G., Snow, W. B., & Tretola, A. R. (1963) · Review of Scientific Instruments · doi:10.1063/1.1718140 · Cited by 54 · see citing works
Biomedical Sensors and Instruments
Tagawa, T., TAMURA, T., & Öberg, P. Å. (2011) · CRC Press eBooks · doi:10.1201/b10775 · Cited by 51 · see citing works
ORAL AND RECTAL TEMPERATURES OF MAN
Horvath, S. M. (1950) · JAMA · doi:10.1001/jama.1950.62920180006007 · Cited by 50 · see citing works
Thermoregulatory model to predict physiological status from ambient environment and heart rate
Yokota, M., Berglund, L. G., Cheuvront, S. N., et al. (2008) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2008.09.003 · Cited by 48 · see citing works
Halberg, F., Cornélissen, G., Wang, Z., et al. (2003) · Journal of Experimental Therapeutics and Oncology · doi:10.1111/j.1533-869x.2003.01097.x · Cited by 46 · see citing works
Monnard, C. R., Fares, E.-J., Calonne, J., Miles-Chan, J. L., Montani, J., Durrer, D., Schütz, Y., & Dulloo, A. G. (2017) · Frontiers in Endocrinology · doi:10.3389/fendo.2017.00130 · Cited by 41 · see citing works
Body Temperature, Blood Pressure, and Hypothalamus
Rodbard, S. (1948) · Science · doi:10.1126/science.108.2807.413 · Cited by 37 · see citing works
p – n junction as an ultralinear calculable thermometer
Verster, T. C. (1968) · Electronics Letters · doi:10.1049/el:19680133 · Cited by 35 · see citing works
Brecht, H. M., & Schoeppe, W. (1978) · Clinical Science · doi:10.1042/cs055081s · Cited by 33 · see citing works
A Real-Time Algorithm for Predicting Core Temperature in Humans
Gribok, A. V., Buller, M. J., Hoyt, R. W., & Jaques Reifman, A. (2010) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2010.2043956 · Cited by 24 · see citing works
Improved probe for a deep body thermometer
Nemoto, T., & Togawa, T. (1988) · Medical & Biological Engineering & Computing · doi:10.1007/bf02442312 · Cited by 23 · see citing works
Kim, M., & Oh, T.-S. (2010) · MATERIALS TRANSACTIONS · doi:10.2320/matertrans.m2010122 · Cited by 21 · see citing works
Huang, M., TAMURA, T., Tang, Z., Chen, W., & Kanaya, S. (2015) · Journal of Sensors · doi:10.1155/2016/4828093 · Cited by 21 · see citing works
Self-citationIndividualized Short-Term Core Temperature Prediction in Humans Using Biomathematical Models
Gribok, A., Buller, M., & Reifman, J. (2008) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2007.913990 · Cited by 19 · see citing works
Biomedical Sensors and Instruments
Öberg, P. Å. (2011) · Cited by 19 · see citing works
Jensen, M. M., & Brabrand, M. (2015) · Scandinavian Journal of Trauma Resuscitation and Emergency Medicine · doi:10.1186/1757-7241-23-s1-a12 · Cited by 15 · see citing works
Measurement of Vital Signs: Temperature [Tutorial
Neuman, M. R. (2010) · IEEE Pulse · doi:10.1109/mpul.2010.937907 · Cited by 15 · see citing works
O’Brien, D., Rogers, I. R., Holden, W., et al. (2000) · Academic Emergency Medicine · doi:10.1111/j.1553-2712.2000.tb02101.x · Cited by 15 · see citing works
Chen, W., Kitazawa, M., & Togawa, T. (2009) · Annals of Biomedical Engineering · doi:10.1007/s10439-009-9746-6 · Cited by 15 · see citing works
Self-citationHalberg, F., & Cornelissen, G. (1993) · PubMed · Cited by 12 · see citing works
Measurement of Vital Signs: Temperature
Neuman, M. R. (2010) · Cited by 10 · see citing works
3D thermal medical image visualization tool: Integration between MRI and thermographic images
de Souza, M. A., Paz, A. A. C., Sanches, I. J., et al. (2014) · doi:10.1109/embc.2014.6944892 · Cited by 9 · see citing works
SOLID-STATE TEMPERATURE SENSOR OUTPERFORMS PREVIOUS TRANSDUCERS.
Ruehle, R. (1975) · Cited by 6 · see citing works
Theoretical study on the inverse modeling of deep body temperature measurement
Huang, M., & Chen, W. (2012) · Physiological Measurement · doi:10.1088/0967-3334/33/3/429 · Cited by 5 · see citing works
Self-citationHMM-based estimation of menstrual cycle from skin temperature during sleep
Chen, W., Kitazawa, M., & Togawa, T. (2008) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2008.4649487 · Cited by 5 · see citing works
Self-citationEstimation of body temperature rhythm based on heart activity parameters in daily life
Sim, S. Y., Yoon, H., Ryou, H., & Park, K. (2014) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2014.6944066 · Cited by 5 · see citing works
Body Temperature, Heat Flow, and Evaporation
TAMURA, T., Huang, M., & Togawa, T. (2017) · Springer eBooks · doi:10.1007/978-3-319-69362-0_10 · Cited by 5 · see citing works
Huang, M., TAMURA, T., Chen, W., et al. (2014) · doi:10.1109/embc.2014.6944555 · Cited by 4 · see citing works
Self-citationCore Body Temperature Changes During Surgery and Nursing Management
Çam, R., Yönem, H., & Özsoy, H. (2016) · Clinical Medicine & Research · doi:10.11648/j.cmr.s.2016050201.11 · Cited by 2 · see citing works
Control Systems and Determination of Phenotypic Traits in Metazoans
Cabej, N. R. (2011) · Elsevier eBooks · doi:10.1016/b978-0-12-415831-3.00001-x · Cited by 1 · see citing works
Predicting core temperature in humans using autoregressive model with exogenous inputs
Gribok, A. V., Rumpler, W. V., Buller, M. J., et al. (2011) · The FASEB Journal · doi:10.1096/fasebj.25.1_supplement.1052.3 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 4
- Tagawa T, Tamura T, Oberg AP. Biomedical sensors and instru- ments. Boca Raton: CRC Press; 2011.
- Wikipedia. Human body temperature. https ://en.wikip edia.org/ wiki/Human _body_tempe ratur e#cite_note-pmid1 87880 94-2. Accessed 5 Dec 2018.
- Asayama M. Guideline for the prevention of heat disorder in Japan. Global Environ Res. 2009;13(1):19-25.
- Huang M, Chen W, Nemoto T. Core temperature rhythm of bed- ridden patients with sequelae of cerebral infarction in the 49th annual conference of Japanese society of medical and biomedical engineering. Osaka, Japan. 2010.
Cited by
Sorted by citations
The Current State of Optical Sensors in Medical Wearables
Vavrinsky, E., Esfahani, N. E., Hausner, M., Kuzma, A., Rezo, V., Donoval, M., & Kosnacova, H. (2022) · Biosensors · doi:10.3390/bios12040217 · Cited by 103 · see citing works
Body temperatures of <i>Manis pentadactyla</i> and <i>Manis javanica</i>
Yu, Y., Wu, S., Wang, W., Mahmood, A., & Zhang, F. (2021) · Veterinary Medicine and Science · doi:10.1002/vms3.611 · Cited by 8 · see citing works
- Authors
- Chen, W.
- Affiliations
- University of Aizu (JP)
- Corresponding author
- Chen, Wenxi
- ORCID
- Chen, Wenxi
- Venue
- Biomedical Engineering Letters
- Published
- 2019-02
- Volume
- 9
- Issue
- 1
- Pages
- 3-17
- ISSN
- 2093-985X (ISSN-L)
- 2093-9868
- PMC
- PMC6431316
- OpenAlex
- W2912226957
- Cited by
- 72
- References
- 57
- Citations by year
- 2026: 4 · 2025: 12 · 2024: 18 · 2023: 7 · 2022: 16 · 2021: 6 · 2020: 6 · 2019: 3
- FWCI
- 0.62
- Type
- journal article
- Language
- en
- Update notices
- correction (2019-02-25)
- Open access
- hybrid
- doi.org
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Biomedical Engineering Letters (publishedVersion, other-oa)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Aizu (2018-P-14)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Critical Care and Intensive Care Medicine › Thermal Regulation in Medicine
- Health Sciences › Medicine › Physiology › Thermoregulation and physiological responses
- Keywords
- body temperature measurement, temperature measurement, core body temperature, skin temperature, basal body temperature, thermoregulation, body temperature set point, non-invasive temperature measurement, Kalman filter, autoregressive models, multiple regression model, vital signs, Internet of Things, artificial intelligence, big data analytics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
