Portable and Wireless Imaging of Dorsal Hand Vein

Audrey Huong, Hui Ern See, W. Mahani Hafizah W. Mahmud, Xavier Ngu

Abstract


Technologies for visualization of dorsal hand vein are of the great interest in the studies of drugs-body response, identity authentication and human metabolism. This study integrates near infrared (NIR) technology into an optical system for non-contact, mobile and quick on the spot visualization of dorsal vascular system. The performance of the developed system was tested on twenty subjects of different skin tone and body frame dimensions. The results showed that the proposed system is able to produce output image of Signal-Noise Ratio (SNR) and Peak SNR of greater than 30 dB and 20 dB, respectively. While this work found a correlation between skin tone and image quality metrics, high consistency was observed in the quality metrics calculated for image data of individuals having different body frame size. This work concluded that the proposed system can be suitably used as a portable and robust tool for enhanced visualization of dorsal hand vein.


Keywords


Body Mass Index; Imaging; Portable; Skin tone; Vein

References


P. Oltulu, B. Ince, N. Kokbudak, S. Findik and F. Kilinc, “Measurement of epidermis, dermis and total skin thicknesses from six different body regions with new ethical histometric technique,” Turkish Journal of Plastic Surgery, vol.26, pp. 56-61, 2018.

M. Rezende, R. Junior, A. Cho, O. Hasegawa and S. Ribak, “Anatomic study of the dorsal arterial system of the hand,” Rev Hosp Clin. Fac. Med. S. Paulo, vol. 59, pp. 71-76, 2004.

A. Adefurin, et al., “Genetic variation in the alpha1B-adrenergic receptor and vascular response,” The Pharmacogenomics Journal, vol. 17, pp. 366-371, 2017.

A. Gorgey, G. Farkas, D. Dolbow, R. Khalil and D. Gater, “Gender dimorphism in central adiposity may explain metabolic dysfunction after spinal cord injury”, PM&R, vol. 10, pp. 338-348, 2018.

J. Lee, T. Lo and C. Chang, “Dorsal hand vein recognition based on directional filter bank,” Signal, image and video processing, vol. 10, pp. 145-152, 2016.

C. Gopal, S. Srivastava, S. Bhardwaj and S. Bhargava, Applied Soft Computing, vol.47, pp. 12-20, 2016.

F. Chandra, A. Wahyudianto andM. Yasin, “Design of vein finder with multi tuning wavelength using RGB LED,” Journal of Physics: Conference Series, vol. 853, 2017.

P. Anupongongarch, K. Khaosomboon and T. Keawgun, “Design and construction of median cubital vein transillumination device by using LED,” IEEE Xplore, pp. 1–3, 2015.

A. B. Bawase and M. S. D. Apte, “Infrared Hand Vein Detection System,” IOSR Journal of Electronics and Communication Engineering, pp. 48–52, 2015.

J. Fan, J. Yang, C. Wu, D. Ai, H. Song, A. Hao and Y. Wang, “Multiple features decomposition for subcutaneous vein extraction and measurement,” IEEE Xplore, pp. 11265-11277, 2018.

T. Walczak, J. K. Grabski, M. Michalowska and D. Szadkowska, “Application of artificial neural networks in the human identification based on thermal images of hands,” Biomechanics in Medicine and Biology, vol. 831, pp. 114-122, 2019.

M. Wadhwani, A. D. Sharma, A. Pillai, N. Pisai and M. Bhowmick, “Vein detection system using infrared light,” International Journal of Scientific & Engineering Research, vol. 6, pp. 780 -785, 2015.

B. M. Sontakke, V. T. Humbe and P. L. Yannawar, “Dorsal hand vein authentication system: A review,” International Journal of Scientific Research Engineering and Technology, vol. 6, pp. 511-517, 2017.

M. I. Delma, “The quest for Type 2 Diabetes subgroups identification: Literature review for a new subtype proposal,” Cureus, vol. 10, pp. 1-6, 2018.

B. M. Thomas, “Introduction to Video and Image Processing. Building Real System and Application,” Denmark: Springer, 2012.

B. B. Singh and S. Patel, “Efficient medical image enhancement using CLAHE enhancement and wavelet fusion,” International Journal of Computer Applications, vol. 167, pp. 1-5, 2017.

U. Sara, M. Akter and M. S. Uddin, “Image quality assessment through FSIM, SSIM, MSE and PSNR- a comparative study,” Journal of Computer and Communication, Scientific Research Publishing, vol. 6, pp. 8- 18, 2019.

N. Thomos, N. Boulgouris and M. Strintzis, “Optimized transmission of jpeg2000 streams over wireless channels,” Trans. Image Process., vol. 15, pp. 54–67, 2006.

I. Hurbain, et al. “Melanosome distribution in keratinocytes in different skin types: Melanosome clusters are not degradative organelles,” J Invest Dermatol., vol. 138, no. 3, pp. 647 – 656, 2018.

T. Homma, S. Kageyama, A. Nishikawa, K. Nagata, “Melanosome degradation in epidermal keratinocytes related to lysosomal protease cathepsin V,” Biochem. Biophys. Res. Commun., vol. 500, pp. 339-343, 2018.

L. Souza-Barros, et al. , “Skin color and tissue thickness effects on transmittance, reflectance, and skin temperature when using 635 and 808 nm lasers in low intensity therapeutics,” Lasers Surg Med, vol. 50, no. 4, pp. 291-301, 2018.

S. C. Yeon, K. H. Hyuck, J. K. Beom, N. K. Myeung and D. P. Hyo, “Development of a non-invasive measurement to the thickness of the subcutaneous adipose tissue layer,” Exp. Dermatol., vol. 17, pp. 537-541, 2008.

P. A. Fowler, M. F. Fuller, C. A. Glasbey, G. G. Cameron and M. A. Foster, “Validation of the in vivo measurement of adipose tissue by magnetic resonance imaging of lean and obese pigs,” Am J Clin Nutr., vol. 56, no. 1, pp. 7-13, 1992.

J. Zhang, H. He and A.F. Liu, “Identification of muscle and adipose gene expression patterns in lean and obese pig,” S Afr J Anim Sc. vol. 49, no. 1, pp. 71-79, 2019.

H. M. Aitken-Buck, et al. “Relationship between epicardial adipose tissue thickness and epicardial adipocyte size with increasing body mass index,” Adipocyte, vol. 8, np. 1, pp. 412-420, 2019.




DOI: http://doi.org/10.11591/ijeecs.v19.i2.pp%25p
Total views : 1 times

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

shopify stats IJEECS visitor statistics