Advancements in hemotype identification: Fingerprint analysis for blood group determination

Hemotype determination through fingerprint analysis offers a non-invasive, pain free, and efficient alternative for blood group classification, enhancing current diagnostic and forensic methodologies. While traditional ABO and Rh typing methods such as the slide agglutination test are relatively simple and can be performed using a minimally invasive fingertip puncture, they still rely on biological sample handling and reagent availability, which may pose challenges in certain emergency or resource limited scenarios. The proposed approach leverages fingerprint ridge patterns to explore correlations between ridge frequencies and the ABO-Rh blood group system. By extracting and analyzing spatial features, including ridge flow and minutiae points, using advanced computer vision and expert system algorithms, accurate hemotype classification is achieved. The methodology employs Scale Invariant Feature Transform (SIFT) for robust feature extraction and XGBoost for efficient classification. This non-invasive framework enhances the accessibility of blood group determination and holds potential for applications in healthcare, emergency response, and forensic investigations where rapid, reagent-free diagnostics are essential.

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Publication Details

Journal
Franklin Open
Published
2025-11-20
DOI
https://doi.org/10.1016/j.fraope.2025.100429
Primary Topic
Forensic and Genetic Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Advancements in hemotype identification: Fingerprint analysis for blood group determination

Naga Satish G., Akansha Tyagi, Prasanth Vaidya Sanivarapu, Sandhya Ashok et al.
Franklin Open
Forensic and Genetic Research
article

Advancements in hemotype identification: Fingerprint analysis for blood group determination

Naga Satish G., Akansha Tyagi, Prasanth Vaidya Sanivarapu, Sandhya Ashok, R. Meenakshi
article en

Abstract

Hemotype determination through fingerprint analysis offers a non-invasive, pain free, and efficient alternative for blood group classification, enhancing current diagnostic and forensic methodologies. While traditional ABO and Rh typing methods such as the slide agglutination test are relatively simple and can be performed using a minimally invasive fingertip puncture, they still rely on biological sample handling and reagent availability, which may pose challenges in certain emergency or resource limited scenarios. The proposed approach leverages fingerprint ridge patterns to explore correlations between ridge frequencies and the ABO-Rh blood group system. By extracting and analyzing spatial features, including ridge flow and minutiae points, using advanced computer vision and expert system algorithms, accurate hemotype classification is achieved. The methodology employs Scale Invariant Feature Transform (SIFT) for robust feature extraction and XGBoost for efficient classification. This non-invasive framework enhances the accessibility of blood group determination and holds potential for applications in healthcare, emergency response, and forensic investigations where rapid, reagent-free diagnostics are essential.

Franklin OpenVol. 13
Alliance University (IN), Chennai Mathematical Institute (IN), University College for Women (IN)
Openalex Percentile: Top 63%
Forensic and Genetic Research
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