Assessment of Infrared Thermography of Thyroid Gland for Development of a New Non-invasive Sleep Detection System
Abstract
Background and Objective: One of the causes of the human death is the road crashes due to the driver drowsiness or falling asleep. Thermography is one of new techniques for non-invasive automatic detection of driver drowsiness, which could help to prevent sleep-related road accidents. In this research, we aimed to record the temperature of the thyroid gland when a person is awake, drowsy, or starts to fall asleep.
Materials and Methods: For capturing the neck’s thermogram, a human thermal video recording was designed. The imaging procedure consisted of the attended cases’ preparation, capturing static thermal video of the neck, and analyz-ing the resultant thermal videos with a particular image-processing algorithm for extracting the temperature data. The image-processing algorithm consisted of image segmentation, noise reduction, and specification of the region of interest for recording the thyroid temperature.
Results: In the wakefulness, a region of the skin, which is in the front of thyroid gland, had an average temperature of 34.5 ± 0.3 C. A change from being awake to being drowsy and falling asleep reduced the average temperature of the neck area to 33.5 ± 0.2 C and 32.5 ± 0.1 C, respectively.
Conclusion: A change from being awake to being drowsy and falling asleep reduces the temperature of the thyroid gland and the neck skin which is located in front of the thyroid gland. By knowing such temperature reduction, a non-invasive system for detection of the person drowsiness or falling asleep can be developed by means of the infrared thermography (IRT).
https://drowsydriving.org/2016/11/national-sleep-foundation-white-paper-on-drowsy-driving/
2. National Highway Traffic Safety Administration. NHTSA Drowsy Driving Research and Program Plan [Online]. [cited 2016 Mar]; Available from: URL: https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/drowsydriving_strategicplan_030316.pdf
3. Sahayadhas A, Sundaraj K, Murugappan M. Detecting driver drowsiness based on sensors: A review. Sensors (Basel) 2012; 12: 16937-53.
4. Sigari MH, Fathy M, Soryani M. A driver face monitoring system for fatigue and distraction detection. Int J Veh Technol 2013; 2013: 263983.
5. Khan MI, Mansoor AB. real time eyes tracking and classification for driver fatigue detection. Proceedings of International Conference on Image Analysis and Recognition (ICIAR 2008); 2008 Jun 25-27; Povoa de Varzim, Portugal. Berlin, Germany, Springer: p. 729-38.
6. Ring EFJ. History of thermology and thermography: Pioneers and progress. Thermology international 2012; 22 Appendix: 3-8.
7. Institute of Medicine (US) Committee on Sleep Medicine and Research, Colten HR, Altevogt BM. Sleep disorders and sleep deprivation: An unmet public
health problem. Washington, DC: National Academies Press; 2006.
8. Cholewka A, Stanek A, Kwiatek S, et al. Does the temperature gradient correlate with the photodynamic diagnosis parameter numerical colour value (NCV)? Photodiagnosis Photodyn Ther 2013; 10: 33-8.
9. Gonnermann J, Klein JP, Klamann MK, et al. Dry eye symptoms in patients after eyelid reconstruction with full-thickness eyelid defects: Using the Tomey TG-1000 thermographer. Ophthalmic Res 2012; 48: 192-8.
10. Bahramian F, Mojra A. Analysis of thyroid ther-mographic images for detection of thyroid tumor: An experimental-numerical study. Int J Numer Method Biomed Eng 2019; 35: e3192.
11. Ring F. Thermal imaging today and its relevance to diabetes. J Diabetes Sci Technol 2010; 4: 857-62.
12. Ebrahimian Hadi Kiashari S, Nahvi A, Homayoun-fard A, et al. Monitoring the variation in driver respira-tion rate from wakefulness to drowsiness: A non-intrusive method for drowsiness detection using thermal imaging. J Sleep Sci 3:1-9.
13. Jin C, He ZZ, Yang Y, et al. MRI-based three-dimensional thermal physiological characterization of thyroid gland of human body. Med Eng Phys 2014; 36: 16-25.
14. Helmy A, Holdmann M, Rizkalla M. Application of thermography for non-invasive diagnosis of thyroid gland disease. IEEE Trans Biomed Eng 2008; 55: 1168-75.
15. Brioschi ML, Teixeira MJ, Silva FMRM, et al. Medical thermography textbook: Principles and applications. Sao Paulo, Brazil: Andreoli; 2010.
16. Pavlidis I, Tsiamyrtzis P, Manohar C, et al. Biomet-rics: Face recognition in thermal infrared. In: Bronzino JD, editor. Biomedical engineering handbook. Boca Raton, FL: CRC Press; 2006.
17. Perona P, Malik J. Scale-space and edge detection using anisotropic diffusion. IEEE Trans Pattern Anal Mach Intell 1990; 12: 629-39.
18. Garbey M, Merla A, Pavlidis I. Estimation of blood flow speed and vessel location from thermal video. Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004 (CVPR 2004); 2004 27 Jun-2 Jul; Washington, DC, USA.
| Files | ||
| Issue | Vol 4 No 1-2 (2019): Winter-Spring | |
| Section | Original Article(s) | |
| Keywords | ||
| Thermography; Thyroid gland; Sleep | ||
| Rights and permissions | |
|
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
