Non-contact biometric identification and authentication using microwave Doppler sensor

Okano, Takaaki; Izumi, Shintaro; Kawaguchi, Hiroshi; Yoshimoto, Masahiko

doi:10.1109/biocas.2017.8325160

Cited by 9 publications

(4 citation statements)

References 3 publications

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“…In this scenario, the first attempts have exploited radar systems, relying on the Doppler effect to derive discriminative information related to specific movements of a person. For instance, heart-induced movements of the chest cage have been considered to design contactless recognition systems in [11] and [12]. When focusing on lower frequencies of the signals received by radar, it is also possible to recover information on the respiratory activity of the subject and use this information to recognize people [13].…”

Section: Mw Fields For Biometric Recognition: State-of-the-artmentioning

confidence: 99%

Biometric Recognition Based on Hand Electromagnetic Scattering at Microwaves

Maiorana

Ramaccia

Stefanini

et al. 2023

IEEE Trans. Microwave Theory Techn.

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In recent years, the need for secure, reliable, and easy-to-use automatic recognition approaches has favored the diffusion of biometric systems. Such methods exploit individuals' physical or behavioral characteristics to differentiate between legitimate users and potential impostors. In this article, we evaluate the feasibility of recognizing a subject by exploiting the electromagnetic (EM) scattering from the user's hand or wrist when it interacts with an EM field at microwave (MW) frequencies. In detail, the proposed recognition framework requires a subject to place a hand between two antennas emitting at frequencies in the X-band, i.e., between 8.2 and 12.4 GHz. The measured scattering parameters are employed as discriminative characteristics to perform user recognition. To improve the achievable recognition performance, an EM model of the involved body parts has been studied and used to design a metasurface (MTS) wristband that could emphasize subject-specific characteristics. The effectiveness of the proposed approach has been tested by collecting multiple measurements from 43 subjects during two distinct acquisition sessions. The obtained results testify that the proposed approach can be used either to implement a robust stand-alone biometric system or exploited together with other well-established hand characteristics such as fingerprint, palm print, or hand vein to improve the achievable recognition performance.

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Section: Mw Fields For Biometric Recognition: State-of-the-artmentioning

confidence: 99%

Biometric Recognition Based on Hand Electromagnetic Scattering at Microwaves

Maiorana

Ramaccia

Stefanini

et al. 2023

IEEE Trans. Microwave Theory Techn.

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“…Another study used a 24-GHz radar system to extract heartbeat related unique features to recognize eleven different participants [75]. An autoregressive (AR) model-based frequency analysis was introduced, which is superior to FFT, having a window length of 100 milliseconds, from which power spectral density could be calculated [75]. Each peak in this analysis represents the contraction and extraction of the heart.…”

Section: Radar-based Identity Authentication Through Heart-based Featuresmentioning

confidence: 99%

Radar-Based Non-Contact Continuous Identity Authentication

et al. 2020

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Non-contact vital signs monitoring using microwave Doppler radar has shown great promise in healthcare applications. Recently, this unobtrusive form of physiological sensing has also been gaining attention for its potential for continuous identity authentication, which can reduce the vulnerability of traditional one-pass validation authentication systems. Physiological Doppler radar is an attractive approach for continuous identity authentication as it requires neither contact nor line-of-sight and does not give rise to privacy concerns associated with video imaging. This paper presents a review of recent advances in radar-based identity authentication systems. It includes an evaluation of the applicability of different research efforts in authentication using respiratory patterns and heart-based dynamics. It also identifies aspects of future research required to address remaining challenges in applying unobtrusive respiration-based or heart-based identity authentication to practical systems. With the advancement of machine learning and artificial intelligence, radar-based continuous authentication can grow to serve a wide range of valuable functions in society.

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“…In other words, personal biological information is accumulated in a database of medical institutions via a network, which will be useful for disease treatment and health management. In that case, what is important is a security function and authentication technology [62], [103]- [107]. With biometric authentication, memorization and password input are unnecessary.…”

Section: Future Directionmentioning

confidence: 99%

Recent Progress of Biomedical Processor SoC for Wearable Healthcare Application: A Review

Yoshimoto

Izumi

2019

IEICE Trans. Electron.

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This paper surveys advances in biomedical processor SoC technology for healthcare application and reviews state-of-the-art architecture and circuits used in SoC integration. Particularly, this paper categorizes and describes techniques for improving power efficiency in communication, computation, and sensing. Additionally, it surveys accuracy enhancement techniques for bio-signal measurement and recognition. Finally, we have discussed the potential new directions for development as well as research.

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Non-contact biometric identification and authentication using microwave Doppler sensor

Cited by 9 publications

References 3 publications

Biometric Recognition Based on Hand Electromagnetic Scattering at Microwaves

Biometric Recognition Based on Hand Electromagnetic Scattering at Microwaves

Radar-Based Non-Contact Continuous Identity Authentication

Recent Progress of Biomedical Processor SoC for Wearable Healthcare Application: A Review

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