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Non-invasive Haemoglobin Estimation Using Different Colour and Texture Features of Palm

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Computer Vision and Image Processing (CVIP 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1777))

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Abstract

Anaemia, caused due to lack of blood haemoglobin levels, is one of the most common diseases which affects billions of people across the world. According to WHO statistics, India is one of the developing countries with highest prevalence of anaemia. Conventional invasive methods are cost-prohibitive and difficult to administer globally which essentially demands non-invasive, accurate, and low-cost approaches for screening of anaemia. The current work targets to combine cutting edge computational approaches with the age-old practice of rough estimation of blood haemoglobin levels by observing pallor in the palm to develop a non-invasive reliable anaemia detection system. The proposed system works with the principle of inducing pallor changes in palm with suitable pressure application and release, measuring the rate of change of colour and performing time-domain analysis thereof to correlate with blood haemoglobin concentration. The entire event of colour changes in palm induced through a customized device, is videophotographed using smartphone camera sensor and is processed and analysed through a set of image processing and analysis techniques. Different handcrafted colour and texture feature extraction techniques are applied on some of the dominant frames considering different colour models on the video samples. The set of features selected through feature selection techniques are provided as input to multi-layer perceptron (MLP) networks comprising of different activation functions and optimizers. The proposed system ensures an accurate estimation of blood haemoglobin level with an average RMSE of 0.597 as determined based on palm pallor video samples of 41 participants.

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Acknowledgment

This work was supported by Ministry of Electronics and Information Technology, Government of India under Sanction number:4(3)/2018-ITEA. We sincerely thank to PTMO, Parulia Health Centre Durgapur, and Superintendent of ESI hospital Durgapur, for their help and cooperation in the data collection process during the clinical study.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Durgapur, India

    Abhishek Kesarwani, Sunanda Das, Mamata Dalui & Dakshina Ranjan Kisku

Authors
  1. Abhishek Kesarwani
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  2. Sunanda Das
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  3. Mamata Dalui
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  4. Dakshina Ranjan Kisku
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Corresponding author

Correspondence to Abhishek Kesarwani .

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Editors and Affiliations

  1. Visvesvaraya National Institute of Technology Nagpur, Nagpur, India

    Deep Gupta

  2. Visvesvaraya National Institute of Technology Nagpur, Nagpur, India

    Kishor Bhurchandi

  3. Indian Institute of Technology Ropar, Rupnagar, India

    Subrahmanyam Murala

  4. Indian Institute of Technology Roorkee, Roorkee, India

    Balasubramanian Raman

  5. Indian Institute of Technology Roorkee, Roorkee, India

    Sanjeev Kumar

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Kesarwani, A., Das, S., Dalui, M., Kisku, D.R. (2023). Non-invasive Haemoglobin Estimation Using Different Colour and Texture Features of Palm. In: Gupta, D., Bhurchandi, K., Murala, S., Raman, B., Kumar, S. (eds) Computer Vision and Image Processing. CVIP 2022. Communications in Computer and Information Science, vol 1777. Springer, Cham. https://doi.org/10.1007/978-3-031-31417-9_14

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  • DOI: https://doi.org/10.1007/978-3-031-31417-9_14

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  • Online ISBN: 978-3-031-31417-9

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