Label-free laser spectroscopy for respiratory virus detection: A review

Yury V. Kistenev, Anubhab Das, Nirmal Mazumder, Olga P. Cherkasova, Anastasia I. Knyazkova, Alexander P. Shkurinov, Valery V. Tuchin, Igor K. Lednev

Research output: Contribution to journalReview articlepeer-review

4 Citations (Scopus)


Infectious diseases are among the most severe threats to modern society. Current methods of virus infection detection based on genome tests need reagents and specialized laboratories. The desired characteristics of new virus detection methods are noninvasiveness, simplicity of implementation, real-time, low cost and label-free detection. There are two groups of methods for molecular biomarkers' detection and analysis: (i) a sample physical separation into individual molecular components and their identification, and (ii) sample content analysis by laser spectroscopy. Variations in the spectral data are typically minor. It requires the use of sophisticated analytical methods like machine learning. This review examines the current technological level of laser spectroscopy and machine learning methods in applications for virus infection detection.

Original languageEnglish
Article numbere202200100
JournalJournal of Biophotonics
Issue number10
Publication statusPublished - 10-2022

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Materials Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Engineering(all)
  • Physics and Astronomy(all)


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