Elemental analysis for human identification assisted by machine learning techniques

https://doi.org/10.53730/ijhs.v6nS5.11832

Authors

  • Ambiga. N Research Scholar, Department of Computer Applications, Alagappa University, India
  • Nagarajan. A Assistant Professor, Department of Computer Applications, Alagappa University, India

Keywords:

Nail, Trace-Element, concentration, Multi-modal, Soft Biometrics, Biometrics

Abstract

Background: Biometrics Authentication is the process of measuring the biological, physical and behavioural characteristics to identify and to verify the individual. Most of the characteristics are inherited and cannot be guessed or stolen. Objectives and Aims: The present research aims to investigate a novel method in Biometric authentication to overcome the difficulties that exist in present Biometric Authentication. The research is to study the trace elements present in the biological nail tissue and measuring their concentration and to prove that this is the best method to identify individuals .It uses Biological features to authenticate the person. Study Data and Participant Sampling: This study collected data from open dataset www.pubmed,com. The datasets are free to use. The capabilities of laser ablation double focusing sector field inductively coupled plasma mass spectrometry is used for the determination of 55 trace elements in nails and the elemental composition were studied and analysed. In this study, the first set of data of Fingernail samples of the human body were collected from two healthy individuals (male of 36 years of age, female of 28 years of age) and they were monitored over an 8-month period of duration (at 3-4 weeks once) - (from July– to February).

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Published

18-08-2022

How to Cite

Ambiga, N., & Nagarajan, A. (2022). Elemental analysis for human identification assisted by machine learning techniques. International Journal of Health Sciences, 6(S5), 11024–11041. https://doi.org/10.53730/ijhs.v6nS5.11832

Issue

Section

Peer Review Articles