Using ATR-FTIR spectroscopy and machine learning for forensic hair identification
Zehua Fan PhD
Institute of Forensic Science, Fudan University, Shanghai, People's Republic of China
Search for more papers by this authorChenyu Li PhD
College of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang, People's Republic of China
Search for more papers by this authorQiran Sun PhD
Department of Forensic Pathology, Institute of Forensic Science, Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science, Shanghai, People's Republic of China
Search for more papers by this authorYiwen Luo PhD
Department of Forensic Pathology, Institute of Forensic Science, Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science, Shanghai, People's Republic of China
Search for more papers by this authorCorresponding Author
Hancheng Lin PhD
Institute of Forensic Science, Fudan University, Shanghai, People's Republic of China
Correspondence
Hancheng Lin, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Bin Cong, College of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang 050000, People's Republic of China.
Email: [email protected]
Ping Huang, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Search for more papers by this authorCorresponding Author
Bin Cong PhD
College of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang, People's Republic of China
Correspondence
Hancheng Lin, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Bin Cong, College of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang 050000, People's Republic of China.
Email: [email protected]
Ping Huang, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Search for more papers by this authorCorresponding Author
Ping Huang PhD
Institute of Forensic Science, Fudan University, Shanghai, People's Republic of China
Correspondence
Hancheng Lin, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Bin Cong, College of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang 050000, People's Republic of China.
Email: [email protected]
Ping Huang, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Search for more papers by this authorZehua Fan PhD
Institute of Forensic Science, Fudan University, Shanghai, People's Republic of China
Search for more papers by this authorChenyu Li PhD
College of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang, People's Republic of China
Search for more papers by this authorQiran Sun PhD
Department of Forensic Pathology, Institute of Forensic Science, Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science, Shanghai, People's Republic of China
Search for more papers by this authorYiwen Luo PhD
Department of Forensic Pathology, Institute of Forensic Science, Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science, Shanghai, People's Republic of China
Search for more papers by this authorCorresponding Author
Hancheng Lin PhD
Institute of Forensic Science, Fudan University, Shanghai, People's Republic of China
Correspondence
Hancheng Lin, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Bin Cong, College of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang 050000, People's Republic of China.
Email: [email protected]
Ping Huang, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Search for more papers by this authorCorresponding Author
Bin Cong PhD
College of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang, People's Republic of China
Correspondence
Hancheng Lin, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Bin Cong, College of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang 050000, People's Republic of China.
Email: [email protected]
Ping Huang, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Search for more papers by this authorCorresponding Author
Ping Huang PhD
Institute of Forensic Science, Fudan University, Shanghai, People's Republic of China
Correspondence
Hancheng Lin, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Bin Cong, College of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang 050000, People's Republic of China.
Email: [email protected]
Ping Huang, Institute of Forensic Science, Fudan University, Shanghai 200032, People's Republic of China.
Email: [email protected]
Search for more papers by this authorZehua Fan and Chenyu Li contributed equally.
Abstract
The purpose of this experiment is to utilize attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy for the discrimination of different types of hair, as numerous studies have substantiated its efficacy in substance classification. In this study, ATR-FTIR spectroscopy was employed to analyze scalp hair, pubic hair, and armpit hair from human subjects. Additionally, a machine learning model was integrated to differentiate between hairs originating from distinct body regions. Because of the limited sampling conditions, we only chose samples from Chinese people who have been living in Shanghai and the surrounding areas for a long time to conduct the experiment. We developed partial least squares discriminant analysis (PLS-DA), random forest (RF), and support vector machine (SVM) classification models and compared their performance in identification. The results show that the SVM model has the best identification results with 90.37% accuracy, 90.37% recall, and 90.38% precision. This preliminary study suggests that ATR-FTIR spectroscopy combined with SVM may be an effective and promising aid in assisting the identification of hair in different parts of the human body. This method is non-destructive, fast, and accurate, and does not require a sample preparation process, which makes it promising in the field of forensic science. Also, we found that the main substance differences that contributed to the good distinction between hairs were expressed in amide I, followed by amide III and C-H deformation.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflict of interest.
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