𝙎𝙋𝙀𝘾𝙄𝘼𝙇 𝙄𝙎𝙎𝙐𝙀 𝙤𝙣 𝙍𝙚𝙘𝙚𝙣𝙩 𝘼𝙙𝙫𝙖𝙣𝙘𝙚𝙨 𝙞𝙣 𝘽𝙞𝙤𝙢𝙚𝙩𝙧𝙞𝙘𝙨 𝘽𝙖𝙨𝙚𝙙 𝙤𝙣 𝘽𝙞𝙤𝙢𝙚𝙙𝙞𝙘𝙖𝙡 𝙄𝙣𝙛𝙤𝙧𝙢𝙖𝙩𝙞𝙤𝙣


This special issue in 𝗢𝗽𝗲𝗻 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 (𝗜𝗙 𝟮𝟬𝟮𝟮: 𝟭.𝟱) focuses on Recent Advances in Biometrics Based on Biomedical Information.
Biometrics can be defined as a technology which recognizes individuals by their physical or behavioral characteristics. This common definition is often employed by considering Biometrics as a security solution to deal with the identification or verification of individuals. Nowadays, Biometric technology is not restricted to law enforcement or government departments by identifying criminals or by controlling borders, but it is also accessible and used in almost everyday life. It allows a more secure access as well as making our life easier. Due to the fact that Biometric systems are commonly integrated into general purpose devices such as smartphones and computers, the attitude of the general public has changed towards them because it has become more acceptable. In addition, the commercial Biometric industry is still growing and is continually being innovated, so it is not surprising the conventional metal key and passwords will not be used anymore as we know it today.
Recently, a new class of Biometrics using biomedical traits has emerged. It includes the electrical signal of the brain (EEG), the muscle (EMG) or the heart (ECG), as well as other measurements from the hidden part of the human body, already adopted in biomedical applications such as heartbeat, vein, sclera vein and DNA. In addition to the previously mentioned modalities, multi-modal biomedical biometric and information fusion are also taken into consideration. Besides their uniqueness, biomedical traits are confidential and secure to an individual. They are difficult to mimic and hard to be copied. Therefore, the identity of an individual is unlikely to be forged, thus preserving the secrecy and privacy of the users.
The aim of the proposed Special Issue is to promote research and reflect the most recent advances in biomedical traits for personal human identification with the emphasis on the following aspects, but certainly not limited to:
• Machine learning and deep learning for biomedical-based biometrics
• Electromyogram based Biometrics
• Electrocardiogram based Biometrics
• X-ray imaging and Magnetic Resonance Imaging based Biometrics
• Behavioral of Biometrics: emerging modalities
• Multimodal approaches in biomedical-based biometrics
• Machine Learning for Biomedical, Behavioral and Hidden Biometrics
• Deep Learning for Biomedical, Behavioral and Hidden Biometrics
• Fraud detection in biomedical-based biometrics
• Data protection and data privacy
• Ethical and social implications of biomedical-based biometrics
• Usability and accessibility in biomedical-based biometrics
• Trustworthiness and reliability in biomedical-based biometrics

Authors are requested to submit their full revised papers complying the general scope of the journal. The submitted papers will undergo the standard peer-review process before they can be accepted. Notification of acceptance will be communicated as we progress with the review process.

===
𝑮𝑼𝑬𝑺𝑻 𝑬𝑫𝑰𝑻𝑶𝑹𝑺

Mohammad Shabaz, Model Institute of Engineering and Technology, Jammu, J&K, India
Imad Rida, Université de Technologie de Compiègne, France
Shah Nazir, University of Swabi, Swabi, Pakistan
Abolfazl Mehbodniya, Kuwait College of Science and Technology (KCST), Doha, Kuwait

===
𝑫𝑬𝑨𝑫𝑳𝑰𝑵𝑬

The deadline for submissions is 𝗡𝗢𝗩𝗘𝗠𝗕𝗘𝗥 𝟮𝟱, 𝟮𝟬𝟮𝟯, but individual papers will be reviewed and published online on an ongoing basis.

===
𝑯𝑶𝑾 𝑻𝑶 𝑺𝑼𝑩𝑴𝑰𝑻

All submissions to the Special Issue must be made electronically via the online submission system Editorial Manager:

𝗵𝘁𝘁𝗽𝘀://𝘄𝘄𝘄.𝗲𝗱𝗶𝘁𝗼𝗿𝗶𝗮𝗹𝗺𝗮𝗻𝗮𝗴𝗲𝗿.𝗰𝗼𝗺/𝗼𝗽𝗲𝗻𝗰𝘀/𝗱𝗲𝗳𝗮𝘂𝗹𝘁𝟮.𝗮𝘀𝗽𝘅

Please choose the article type “𝙎𝙄: 𝙍𝙚𝙘𝙚𝙣𝙩 𝘼𝙙𝙫𝙖𝙣𝙘𝙚𝙨 𝙞𝙣 𝘽𝙞𝙤𝙢𝙚𝙩𝙧𝙞𝙘𝙨 𝘽𝙖𝙨𝙚𝙙 𝙤𝙣 𝘽𝙞𝙤𝙢𝙚𝙙𝙞𝙘𝙖𝙡 𝙄𝙣𝙛𝙤𝙧𝙢𝙖𝙩𝙞𝙤𝙣”.

===
𝑪𝑶𝑵𝑻𝑨𝑪𝑻

𝗼𝗽𝗲𝗻𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿𝘀𝗰𝗶𝗲𝗻𝗰𝗲@𝗱𝗲𝗴𝗿𝘂𝘆𝘁𝗲𝗿.𝗰𝗼𝗺

===
𝗙𝗼𝗿 𝗺𝗼𝗿𝗲 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻, 𝗽𝗹𝗲𝗮𝘀𝗲 𝘃𝗶𝘀𝗶𝘁 𝗼𝘂𝗿 𝘄𝗲𝗯𝘀𝗶𝘁𝗲.

https://www.degruyter.com/journal/key/comp/html#overview