Review of the Capacity to Accurately Detect the Temperature of Human Skin Tissue Using the Microwave Radiation Method.

early diagnosis microwave radiometry non-contact precise measurement subcutaneous tissue temperature

Journal

Biosensors
ISSN: 2079-6374
Titre abrégé: Biosensors (Basel)
Pays: Switzerland
ID NLM: 101609191

Informations de publication

Date de publication:
28 Apr 2024
Historique:
received: 01 04 2024
revised: 24 04 2024
accepted: 26 04 2024
medline: 24 5 2024
pubmed: 24 5 2024
entrez: 24 5 2024
Statut: epublish

Résumé

Microwave radiometry (MWR) is instrumental in detecting thermal variations in skin tissue before anatomical changes occur, proving particularly beneficial in the early diagnosis of cancer and inflammation. This study concisely traces the evolution of microwave radiometers within the medical sector. By analyzing a plethora of pertinent studies and contrasting their strengths, weaknesses, and performance metrics, this research identifies the primary factors limiting temperature measurement accuracy. The review establishes the critical technologies necessary to overcome these limitations, examines the current state and prospective advancements of each technology, and proposes comprehensive implementation strategies. The discussion elucidates that the precise measurement of human surface and subcutaneous tissue temperatures using an MWR system is a complex challenge, necessitating an integration of antenna directionality for temperature measurement, radiometer error correction, hardware configuration, and the calibration and precision of a multilayer tissue forward and inversion method. This study delves into the pivotal technologies for non-invasive human tissue temperature monitoring in the microwave frequency range, offering an effective approach for the precise assessment of human epidermal and subcutaneous temperatures, and develops a non-contact microwave protocol for gauging subcutaneous tissue temperature distribution. It is anticipated that mass-produced measurement systems will deliver substantial economic and societal benefits.

Identifiants

pubmed: 38785695
pii: bios14050221
doi: 10.3390/bios14050221
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : the National Natural Science Foundation of China
ID : 62276009

Auteurs

Jingtao Wu (J)

School of Information Science and Engineering, Southeast University, Nanjing 210096, China.

Jie Liu (J)

The Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China.

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Classifications MeSH