• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology

Article

Indian Journal of Science and Technology

Year: 2021, Volume: 14, Issue: 20, Pages: 1689-1698

Original Article

Continuous monitoring of Physiological parameters using PPG

Received Date:05 November 2020, Accepted Date:26 April 2021, Published Date:08 June 2021

Abstract

Objectives: To develop a non-invasive measurement of continuous monitoring of hemoglobin using IoT-enabled pulse oximetry. Currently in India, most women, senior citizens, and rural area people are suffering from anemia. In many cases, people unable to visit hospitals and laboratories for hemoglobin testing. To help the above people our proposed system will measure hemoglobin concentration without visiting the hospital at an affordable price. Methods: We developed real-time continuous monitoring of Hb concentration and oxygen saturation (SpO2) using pulse oximetry. In this study, 47 healthy volunteers were participated and measure the above-mentioned parameters under resting conditions. Findings: The obtained results were in unison with laboratory measurements with the variation of 0.12g/dL to 1.0g/dL. Novelty/Applications: Experimental results showed the approach of continuous monitoring of hemoglobin and SpO2 using an IoT-enabled non-invasive method can be useful in healthcare management.

Keywords

Hemoglobin, oxygen saturation, pulse oximetry, IoT, Anaemia

References

  1. Khandpur RS. Hand Book of Biomedical Instrumentation. New Delhi. Tata Mc Graw Hill publication. 2003.
  2. Viana MB. Anemia and infection: a complex relationship. Revistabrasileira de hematologiae hemoterapia. 2011;33(2):90–92. Available from: http://doi.org/10.5581/1516-8484.20110024
  3. Chaparro CM, Suchdev PS. Anemia epidemiology, pathophysiology, and etiology in low-and middle-income countries. Annals of the New York Academy of Sciences. 2019;1450(1):15–31. Available from: https://doi.org/10.1111/nyas.14092
  4. Joseph B, Haider A, Rhee P. Non-invasive hemoglobin monitoring. International Journal of Surgery. 2016;33:254–261. Available from: https://doi.org/10.1016/j.ijsu.2015.11.048
  5. Joseph B, Pandit V, Aziz H, Kulvatunyou N, Zangbar B, Tang A, et al. Transforming hemoglobin measurement in trauma patients: noninvasive spot check hemoglobin. Journal of the American College of Surgeons. 2015;220(1):93–98. Available from: https://doi.org/10.1016/j.jamcollsurg.2014.09.022
  6. Farris L, Szmuk P. Use of the Masimo Rainbow Noninvasive Hemoglobin Measurement for Children with Sickle Cell Disease. Journal of Investigative Medicine. 2011;59(2):520. Available from: https://hdl.handle.net/2152.5/1116
  7. Butwick A, Hilton G, Carvalho B. Non-invasive hemoglobin measurement in patients undergoing elective Caesarean section. British journal of anesthesia. 2012;108(2):271–278. Available from: https://doi.org/10.1093/bja/aer373
  8. Yoshida A, Saito K, Ishii K, Azuma I, Sasa H, Furuya K. Assessment of noninvasive, percutaneous hemoglobin measurement in pregnant and early postpartum women. Medical Devices. 2014;7:11–16. Available from: https://doi.org/10.2147/MDER.S54696
  9. Chaudhary R, AD, AS. Techniques used for the screening of hemoglobin levels in blood donors: current insights and future directions. Journal of blood medicine. 2017;8:75–82. Available from: 10.2147/JBM.S103788
  10. Pajares-Herraiz AL, Rodriguez-Gambarte JD, Eguia-Lopez B. A comparative study of three non-invasive systems for measurement of hemoglobin with hemocue system having coulter LH750 as reference value. Hematology & Transfusion International Journal. 2015;1(3):68–74. Available from: 10.15406/htij.2015.01.00016
  11. Jeon KJ, Kim SJ, Park KK, Kim JW, Yoon G. Noninvasive total hemoglobin measurement. Journal of biomedical optics. 2002;7(1):45–51. Available from: https://doi.org/10.1117/1.1427047
  12. Gamal M, BA, Zakaria D, Dayem OAE, Rady A, Fawzy M, et al. Evaluation of noninvasive hemoglobin monitoring in trauma patients with low hemoglobin levels. Shock. 2018;49:150–153. Available from: 10.1097/SHK.0000000000000949
  13. Patino M, Schultz L, Hossain M, Moeller J, Mahmoud M, Gunter J, et al. Trending and accuracy of noninvasive hemoglobin monitoring in pediatric perioperative patients. Anesthesia & Analgesia. 2014;119:920–925. Available from: 10.1213/ANE.0000000000000369
  14. Shah N, Osea EA, Martinez GJ. Accuracy of noninvasive hemoglobin and invasive point of care hemoglobin testing compared with a laboratory analyzer. International journal of laboratory hematology. 2014;36:56–61. Available from: https://doi.org/10.111/ijlh.12118
  15. Kallur JY, Bharat C, Shridevi SH, Shankar U. Efficacy of Pulse Co-oximeter in Hemoglobin Estimation: A noninvasive method. Annals of Pathology and Laboratory Medicine. 2017;4(5):A585–A590. Available from: 10.21276/APALM.1558
  16. Kumar R, Ranganathan H. Noninvasive sensor technology for total hemoglobin measurement in blood. Journal of Industrial and Intelligent Information. 2013;1(4):243–249. Available from: 10.12720/jiii.1.4.243-246
  17. Rochmanto RA, Zakaria H, Alviana RD, Shahib N. Non-invasive hemoglobin measurement for Anemia diagnosis. In 2017 4th International Conference on Electrical Engineering. 2017;p. 1–5. Available from: 10.11591/eecsi.v4.1003
  18. Awada WN, Mohmoued MF, Radwan TM, GZH, Elkady HW. Continuous and noninvasive hemoglobin monitoring reduces red blood cell transfusion during neurosurgery: a prospective cohort study. Journal of clinical monitoring and computing. 2015;29:733–740. Available from: https://doi.org/10.1007/s10877-015-9660-4
  19. Muady GF, Bitterman H, Laor A, Vardi M, Urin V, NGZ. Hemoglobin levels and blood transfusion in patients with sepsis in Internal Medicine Departments. BMC Infectious Diseases. 2016;16(569):1–8. Available from: https://doi.org/10.1186/s12879-016-1882-7
  20. Jr RDW, Mei Z, Mapango C, Jefferds MED. Methods and analyzers for hemoglobin measurement in clinical laboratories and field settings. Annals of the New York Academy of Sciences. 2019;1450(1):147–171. Available from: https://doi.org/10.1111/nyas.14124
  21. Barker SJ, Shander A, Ramsay MA. Continuous noninvasive hemoglobin monitoring: a measured response to a critical review. Anesthesia and analgesia. 2016;122:565–572. Available from: 10.1213/ANE.0000000000000605
  22. Cohen ZV, Haxha S, Aggoun A. Pulse oximetry optical sensor using oxygen-bound haemoglobin. Optics Express. 2016;24(9):10115–10131. Available from: 10.1364/oe.24.010115
  23. Chong AV, Terosiet M, Histace A, O.Romain. Towards a novel single-LED pulse oximeter based on a multispectral sensor for IoT applications. Microelectronics Journal. 2019;88:128–136. Available from: 10.1016/j.mejo.2018.03.005
  24. Macknet MR, Allard M, Applegate RL, Rook J. The accuracy of noninvasive and continuous total hemoglobin measurement by pulse CO-Oximetry in human subjects undergoing hemodilution. Anesthesia & Analgesia. 2010;111(6):1424–1426. Available from: 10.1213/ANE.0b013e3181fc74b9
  25. Lamhaut L, Apriotesei R, Combes X, Lejay M, Carli P, Vivien B. Comparison of the accuracy of noninvasive hemoglobin monitoring by spectrophotometry (SpHb) and HemoCue® with automated laboratory hemoglobin measurement. The Journal of the American Society of Anesthesiologists. 2011;115(3):548–554. Available from: https://doi.org/10.1097/ALN.0b013e3182270c22
  26. Lindner G, Exadaktylos AK. How noninvasive haemoglobin measurement with pulse CO-Oximetry can change your practice: an expert review. Emergency medicine international. 2013;701529 . Available from: https://doi.org/10.1155/2013/701529
  27. Mcmurdy JW, Jay GD, Suner S, Trespalacios F, Crawford GP. Diffuse reflectance spectra of the palpebral conjunctiva and its utility as a noninvasive indicator of total hemoglobin. Journal of Biomedical Optics. 2006;11(1):14019. Available from: https://doi.org/10.1117/1.2167967
  28. Esenaliev R, Motamedi M, Prough D. United States patent US 6,751,490 Continuous optoacoustic monitoring of hemoglobin concentration and hematocrit. 2004.
  29. Abay TY, Kyriacou PA. Photoplethysmography for blood volumes and oxygenation changes during intermittent vascular occlusions. Journal of Clinical Monitoring and Computing. 2018;32(3):447–455. Available from: 10.1007/s10877-017-0030-2
  30. Veerabhadrappa ST, Vyas AL, Anand S. Changes in heart rate variability and pulse wave characteristics during normal pregnancy and postpartum. International Journal of Biomedical Engineering and Technology. 2015;17(2):99–114. Available from: https://doi.org/10.1504/IJBET.2015.068045
  31. Timm U, Leen G, Lewis E, Mcgrath D, Kraitl J, Ewald H. Non-invasive optical real-time measurement of total hemoglobin content. Procedia Engineering. 2010;5:488–491. Available from: https://doi.org/10.1016/j.proeng.2010.09.153
  32. Elgendi M, Fletcher R, Liang Y, Howard N, Lovell NH, Abbott D, et al. The use of photoplethysmography for assessing hypertension. NPJ Digital Medicine. 2019;2(60):1–11. Available from: https://doi.org/10.1038/s41746-019-0136-7
  33. Shao J, Shi P, Hu S, Liu Y, Yu H. An optimization study of estimating blood pressure models based on pulse arrival time for continuous monitoring. Journal of Healthcare Engineering. 2020;p. 1078251 . Available from: https://doi.org/10.1155/2020/1078251
  34. Al-Sheikh MA, Ameen IA. Design of Mobile Healthcare Monitoring System Using IoT Technology and Cloud Computing. IOP Conference Series: Materials Science and Engineering. 2020;881:1–17. Available from: 10.1088/1757-899X/881/1/012113
  35. Lopez LJR, Aponte GP, Garcia AR. Internet of Things Applied in Healthcare Based on Open Hardware with Low-Energy Consumption. Healthcare Informatics Research. 2019;25(3):230–235. Available from: https://doi.org/10.4258/hir.2019.25.3.230
  36. Kuncoro C, Luo WJ, Kuan YD. Wireless Photoplethysmography Sensor for Continuous Blood Pressure Biosignal Shape Acquisition. Journal of Sensors. 2020;p. 7192015 . Available from: https://doi.org/10.1155/2020/7192015
  37. Liao LD, Wang Y, Tsao YC, Wang IJ, Jhang DF, Chuang CC, et al. Design and implementation of a multifunction wearable device to monitor sleep physiological signals. Micromachines. 2020;11(7):672. Available from: https://doi.org/10.3390/mi11070672
  38. Chowdhury MH, Shuzan MN, Chowdhury ME, Mahbub ZB, Uddin MM, Khandakar A. Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques. . Sensors. 2020;20:3127. Available from: https://doi.org/10.3390/s20113127

Copyright

© 2021 Veerabhadrappa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)

DON'T MISS OUT!

Subscribe now for latest articles and news.