Abstract
The paper presents a novel, self-sufficient, Internet of Medical Things-based model called iNAP to address the shortcomings of anemia and polycythemia detection. The proposed model captures eye and fingernail images using a smartphone camera and automatically extracts the conjunctiva and fingernails as the regions of interest. A novel algorithm extracts the dominant color by analyzing color spectroscopy of the extracted portions and accurately predicts blood hemoglobin level. A less than 11.5 gdL\( ^{-1} \) value is categorized as anemia while a greater than 16.5 gdL\( ^{-1} \) value as polycythemia. The model incorporates machine learning and image processing techniques allowing easy smartphone implementation. The model predicts blood hemoglobin to an accuracy of \( \pm \)0.33 gdL\( ^{-1} \), a bias of 0.2 gdL\( ^{-1} \), and a sensitivity of 90\( \% \) compared to clinically tested results on 99 participants. Furthermore, a novel brightness adjustment algorithm is developed, allowing robustness to a wide illumination range and the type of device used. The proposed IoMT framework allows virtual consultations between physicians and patients, as well as provides overall public health information. The model thereby establishes itself as an authentic and acceptable replacement for invasive and clinically-based hemoglobin tests by leveraging the feature of self-anemia and polycythemia diagnosis.
- [1] . 2019. Ergonomic Lighting Levels by Room for Residential Spaces. Available at https://www.thoughtco.com/lighting-levels-by-room-1206643.Google Scholar
- [2] . 2019. Non-invasive screening tool to detect anemia. In 2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT). IEEE, Bethesda, MD, USA, 67–70.Google Scholar
- [3] . 2010. A novel regression based model for detecting anemia using color microscopic blood images. Journal of Software Engineering and Applications 3, 8 (2010), 756.Google Scholar
- [4] . 2016. A novel approach to evaluate blood parameters using computer vision techniques. In 2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA). IEEE, Benevento, Italy, 1–6.Google Scholar
- [5] . 2021. Smartphone-enabled paper-based hemoglobin sensor for extreme point-of-care diagnostics. ACS Sensors 6, 3 (2021), 1077–1085.Google Scholar
- [6] . 1974. A dendrite method for cluster analysis. Communications in Statistics-Theory and Methods 3, 1 (1974), 1–27.Google ScholarCross Ref
- [7] . 2016. Non-invasive detection of anaemia using digital photographs of the conjunctiva. PloS One 11, 4 (2016), e0153286.Google ScholarCross Ref
- [8] . 1979. A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-1, 2 (1979), 224–227.Google ScholarDigital Library
- [9] . 2019. Anaemia among men in India: A nationally representative cross-sectional study. The Lancet Global Health 7, 12 (2019), 1685–1694.Google Scholar
- [10] . 2018. Automatic segmentation of relevant sections of the conjunctiva for non-invasive anemia detection. In 2018 3rd International Conference on Smart and Sustainable Technologies (SpliTech). IEEE, Split, Croatia, 1–5.Google Scholar
- [11] . 2018. A new method and a non-invasive device to estimate anemia based on digital images of the conjunctiva. IEEE Access 6 (2018), 46968–46975.Google ScholarCross Ref
- [12] . 1973. A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters. Journal of Cybernetics 3 (1973), 32–57.Google ScholarCross Ref
- [13] . 2017. Anaemia cells detection based on shape signature using neural networks. Measurement 104 (2017), 50–59.Google ScholarCross Ref
- [14] . 2019. Tracking your eyes with Python. Available at https://medium.com/@stepanfilonov/tracking-your-eyes-with-python-3952e66194a6.Google Scholar
- [15] . 2020. sHEMO: Smartphone spectroscopy for blood hemoglobin level monitoring in smart anemia-care. IEEE Sensors Journal 21, 6 (2020), 8520–8529.Google Scholar
- [16] . 2017. Digital camera-based spectrometry for the development of point-of-care anemia detection on ultra-low volume whole blood sample. IEEE Sensors Journal 17, 21 (2017), 7149–7156.Google Scholar
- [17] . 2019. A novel technique of noninvasive hemoglobin level measurement using HSV value of fingertip image. arXiv preprint arXiv:1910.02579.Google Scholar
- [18] . 2016. Early stage disease diagnosis system using human nail image processing. IJ Information Technology and Computer Science 7 (2016), 30–35.Google Scholar
- [19] . 2013. Modified k-means for better initial cluster centres. International Journal of Computer Science and Mobile Computing 2, 7 (2013), 219–223.Google Scholar
- [20] . 2010. The accuracy of noninvasive and continuous total hemoglobin measurement by pulse CO-Oximetry in human subjects undergoing hemodilution. Anesthesia & Analgesia 111, 6 (2010), 1424–1426.Google Scholar
- [21] . 2018. Smartphone app for non-invasive detection of anemia using only patient-sourced photos. Nature Communications 9, 1 (2018), 1–10.Google Scholar
- [22] . 2017. A review: Fingernail images for disease detection. Int. J. Eng. Comput. Sci 6, 11 (2017), 22830–22835.Google Scholar
- [23] . 2020. Detection of anaemia from retinal fundus images via deep learning. Nature Biomedical Engineering 4, 1 (2020), 18–27.Google ScholarCross Ref
- [24] . 2008. Worldwide prevalence of anaemia 1993-2005: WHO global database on anaemia. (2008).Google Scholar
- [25] . 2020. mHealth spectroscopy of blood hemoglobin with spectral super-resolution. Optica 7, 6 (2020), 563–573.Google Scholar
- [26] . 2019. IoMT based smart health care monitoring system. International Journal for Innovative Research in Science & Technology 5 (2019), 58–64.Google Scholar
- [27] . 2014. Diagnosis and management of polycythemia vera: Proceedings from a multidisciplinary roundtable. American Health & Drug Benefits 7, 7 suppl3 (2014), S36.Google Scholar
- [28] . 2006. Simple method for estimation of hemoglobin in human blood using color analysis. IEEE Transactions on Information Technology in Biomedicine 10, 4 (2006), 657–662.Google ScholarDigital Library
- [29] . 1987. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics 20 (1987), 53–65.Google ScholarDigital Library
- [30] . 2001. Estimating the prevalence of anaemia: A comparison of three methods. Bulletin of the World Health Organization 79 (2001), 506–511.Google Scholar
- [31] . 2018. Detection anemia based on conjunctiva pallor level using k-means algorithm. IOP Conference Series: Materials Science and Engineering 420, 1 (2018), 012101.Google Scholar
- [32] . 1995. A simple and reliable method for estimating haemoglobin. Bulletin of the World Health Organization 73, 3 (1995), 369.Google Scholar
- [33] . 2007. Non-invasive determination of hemoglobin by digital photography of palpebral conjunctiva. The Journal of Emergency Medicine 33, 2 (2007), 105–111.Google Scholar
- [34] . 2017. Detection of anemia from image of the anterior conjunctiva of the eye by image processing and thresholding. In 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC). IEEE, Dhaka, Bangladesh, 697–701.Google Scholar
- [35] . 2018. Rare Disease Database. Available at https://rarediseases.org/rare-diseases/polycythemia-vera/.Google Scholar
- [36] . 2001. Estimating the number of clusters in a data set via the gap statistic. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 63, 2 (2001), 411–423.Google ScholarCross Ref
- [37] . 1999. Topographic anatomy of the eyelids, and the effects of sex and age. British Journal of Ophthalmology 83, 3 (1999), 347–352.Google Scholar
- [38] . 2004. Robust real-time face detection. International Journal of Computer Vision 57, 2 (2004), 137–154.Google ScholarDigital Library
- [39] . 1986. Evaluation of “HemoCue,” a new device for determining hemoglobin. Clinical Chemistry 32, 3 (1986), 526–529.Google Scholar
- [40] . 2016. HemaApp: Noninvasive blood screening of hemoglobin using smartphone cameras. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery, Heidelberg, Germany, 593–604.Google Scholar
Index Terms
- iNAP: A Hybrid Approach for NonInvasive Anemia-Polycythemia Detection in the IoMT
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