This paper is in the following e-collection/theme issue:

mHealth for Data Collection and Research (955) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1399) Mobile Health (mhealth) (2939) Novel Sensors and Data Acquisition Methods in Cardiology (196)

Published on in Vol 9, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16806, first published .
Noninvasive Hemoglobin Level Prediction in a Mobile Phone Environment: State of the Art Review and Recommendations

Noninvasive Hemoglobin Level Prediction in a Mobile Phone Environment: State of the Art Review and Recommendations

Noninvasive Hemoglobin Level Prediction in a Mobile Phone Environment: State of the Art Review and Recommendations

Authors of this article:

Md Kamrul Hasan1 Author Orcid Image ;   Md Hasanul Aziz2 Author Orcid Image ;   Md Ishrak Islam Zarif2 Author Orcid Image ;   Mahmudul Hasan3 Author Orcid Image ;   MMA Hashem4 Author Orcid Image ;   Shion Guha2 Author Orcid Image ;   Richard R Love2 Author Orcid Image ;   Sheikh Ahamed2 Author Orcid Image
Article Authors Cited by (24) Tweetations (1) Metrics

Journals

  1. Renò V, Sciancalepore M, Dimauro G, Maglietta R, Cassano M, Gelardi M. A Novel Approach for the Automatic Estimation of the Ciliated Cell Beating Frequency. Electronics 2020;9(6):1002 View
  2. Dimauro G, Deperte F, Maglietta R, Bove M, La Gioia F, Renò V, Simone L, Gelardi M. A Novel Approach for Biofilm Detection Based on a Convolutional Neural Network. Electronics 2020;9(6):881 View
  3. Girardi F, De Gennaro G, Colizzi L, Convertini N. Improving the Healthcare Effectiveness: The Possible Role of EHR, IoMT and Blockchain. Electronics 2020;9(6):884 View
  4. Dimauro G, Bevilacqua V, Fina P, Buongiorno D, Brunetti A, Latrofa S, Cassano M, Gelardi M. Comparative Analysis of Rhino-Cytological Specimens with Image Analysis and Deep Learning Techniques. Electronics 2020;9(6):952 View
  5. Aziz M, Hasan M, Mahmood A, Love R, Ahamed S. Automated Cardiac Pulse Cycle Analysis From Photoplethysmogram (PPG) Signals Generated From Fingertip Videos Captured Using a Smartphone to Measure Blood Hemoglobin Levels. IEEE Journal of Biomedical and Health Informatics 2021;25(5):1385 View
  6. Dimauro G, Bevilacqua V, Pecchia L. Bioelectronic Technologies and Artificial Intelligence for Medical Diagnosis and Healthcare. Electronics 2021;10(11):1242 View
  7. Kesarwani A, Das S, Dalui M, Kisku D, Sen B, Roy S, Basu A. Non-invasive anaemia detection by examining palm pallor: A smartphone-based approach. Biomedical Signal Processing and Control 2023;79:104045 View
  8. Hasan M, Saxena D, Rubaiat Y, Ahamed S, Guha S. Design Recommendations towards Developing a Smartphone-Based Point-of-Care Tool for Rural Bangladeshi Users. International Journal of Human–Computer Interaction 2024;40(4):965 View
  9. Bautista M, Kowal M, Cave D, Downey C, Jayne D. Clinical applications of contactless photoplethysmography for monitoring in adults: A systematic review and meta-analysis. Journal of Clinical and Translational Science 2023;7(1) View
  10. Gullifa G, Barone L, Papa E, Giuffrida A, Materazzi S, Risoluti R. Portable NIR spectroscopy: the route to green analytical chemistry. Frontiers in Chemistry 2023;11 View
  11. Xuan Y, Barry C, Antipa N, Wang E. A calibration method for smartphone camera photophlethysmography. Frontiers in Digital Health 2023;5 View
  12. Raposo-Neto J, Kowalski-Neto E, Luiz W, Fonseca E, Cedro A, Singh M, Martin F, Vassallo P, Campos L, Barauna V. Near-Infrared Spectroscopy with Supervised Machine Learning as a Screening Tool for Neutropenia. Journal of Personalized Medicine 2023;14(1):9 View
  13. Kesarwani A, Das S, Kisku D, Dalui M. Non-invasive anaemia detection based on palm pallor video using tree-structured 3D CNN and vision transformer models. Journal of Experimental & Theoretical Artificial Intelligence 2024:1 View
  14. Peng F, Zhang N, Chen C, Wu F, Wang W. Ensemble Extreme Learning Machine Method for Hemoglobin Estimation Based on PhotoPlethysmoGraphic Signals. Sensors 2024;24(6):1736 View
  15. Amrutha A, Sidenur B, P.S B, S.V S, M.R N, Rajagopal H. Estimation of haemoglobin using non-invasive portable device with spectroscopic signal application. Scientific Reports 2024;14(1) View
  16. Meidita D, Wijayanti K, Hendriyani H. Effectiveness of Hae-Band in Measuring Hb Levels in Postpartum Hemorrhage Risk Monitoring. JURNAL INFO KESEHATAN 2024;22(2):378 View
  17. Açıcı K. Hemoglobin value prediction with bayesian optimization assisted machine learning models. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 2024;66(2):176 View

Books/Policy Documents

  1. Saha S, Bhattacharya R. Internet of Things Based Smart Healthcare. View