Review
Engineering, Electrical & Electronic
Anuradha Singh, Saeed Ur Rehman, Sira Yongchareon, Peter Han Joo Chong
Summary: This paper comprehensively reviews the current state-of-art of non-contact vital sign measurements using radar, highlighting the need to move towards higher frequency for high accuracy in a multi-resident environment. It also analyzes the implications of mmWave exposure on human health and environmental attenuation, while discussing significant challenges associated with hardware and signal processing algorithm. Finally, the review concludes with future directions and challenges associated with detecting vital signs in a multi-resident indoor environment.
IEEE SENSORS JOURNAL
(2021)
Article
Chemistry, Analytical
Michael C. Brown, Changzhi Li
Summary: This paper discusses the challenges and potential solutions of incorporating digital modulation into radar systems. It proposes a reconfigurable phase-modulated continuous wave (PMCW) radar system for vital sign detection and gesture recognition. Experimental results show that this radar system has high flexibility and accuracy under different modulation schemes.
Article
Engineering, Biomedical
Elias Antolinos, Jesus Grajal
Summary: The use of radar technology for contactless monitoring of cardiorespiratory activity has been extensively studied in the past two decades. This article compares the application of continuous-wave (CW) and linear-frequency-modulated continuous-wave (LFMCW) radars in vital sign monitoring scenarios. Results show that both configurations are capable of measuring general metrics, but LFMCW offers better results in identifying cardiac events and extracting certain derived biomarkers.
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS
(2023)
Article
Chemistry, Multidisciplinary
Yael Balal, Afik Yarimi, Nezah Balal
Summary: Falls are the leading cause of accidents among the elderly population. In recent years, radar has been widely employed in fall detection, providing superior sensing capabilities, small dimensions, low cost, non-intrusive sensing, and robustness. This paper presents a technique using low-power millimeter-wave radar to identify when a person is falling in real time, based on micro-Doppler shifts associated with the person's motion. Experimental results show high-resolution and accurate results using 94 GHz real radar data.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Zixuan Ou, Wenbin Ye
Summary: In this article, we propose a lightweight network called Tiny-RadarNet for extracting features from raw data. Unlike traditional neural networks, we use a unique parallel 1-D depthwise convolutions structure to eliminate the need for standard convolutions and achieve significant parameter reduction. Furthermore, we treat fall detection as a matching problem using metric learning technique and introduce a dual loss function to improve the network's robustness against unobserved human motions.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Victor G. Rizzi Varela, Davi V. Q. Rodrigues, Leya Zeng, Changzhi Li
Summary: This study proposes a radar-based solution for monitoring physical activities, capable of detecting, classifying, and counting repetitions of multiple individuals doing different exercises in front of the radar. The solution utilizes a single monostatic radar and extracts features using range-Doppler frames and micro-Doppler analysis. The feasibility and robustness of the solution were validated in realistic scenarios by adding static and moving clutter to the measurements.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Chemistry, Analytical
Nitin Kathuria, Boon-Chong Seet
Summary: This paper presents the design of a four-element antenna array on a flexible LCP substrate for non-contact vital signs monitoring, with a relatively compact size and high gain. The fabricated antenna array can detect breathing rate and heart rate relatively accurately using RF output power from a distance of approximately 60 cm. The effect of bending on antenna performance is also analyzed.
Article
Engineering, Electrical & Electronic
Jincheng Lu, Wen-Bin Ye
Summary: A novel multi-stage radar-based fall detection system is proposed in this work to achieve high accuracy while maintaining a low power consumption. The system includes three stages, each utilizing different methods and models to optimize detection performance and reduce complexity.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Biomedical
Marco Mercuri, Yiting Lu, Salvatore Polito, Fokko Wieringa, Yao-Hong Liu, Alle-Jan van der Veen, Chris Van Hoof, Tom Torfs
Summary: This research focuses on addressing indoor multipath propagation challenges by proposing a methodology based on accurate models of indoor multipaths and radar signals. The approach demonstrated accurate measurement of individual vital signs and localization in a challenging real-world office setting, showcasing potential applications in healthcare, assisted living, emergency rescue, and other fields.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Mengxia Chen, Zhaocheng Yang, Jialei Lai, Ping Chu, Jinghong Lin
Summary: This paper proposes a novel three-stage low-complexity human fall detection method using an impulse radio ultra-wideband (IR-UWB) radar. The method shows low computational complexity, relative robustness, and high fall detection accuracy under a low false alarm rate.
IEEE SENSORS JOURNAL
(2022)
Article
Optics
Ziqian Zhang, Yang Liu, Tegan Stephens, Benjamin J. J. Eggleton
Summary: Researchers have developed a photonic radar for non-contact vital sign detection, overcoming limitations of traditional monitoring methods. The radar achieves millimetre-level range resolution with a bandwidth of up to 30 GHz. The study also explores the use of optical signals generated by the system for LiDAR-based vital sign detection, offering potential for improved accuracy and system resilience.
Article
Chemistry, Analytical
Zhiqiang Gao, Luqman Ali, Cong Wang, Ruizhi Liu, Chunwei Wang, Cheng Qian, Hokun Sung, Fanyi Meng
Summary: This paper designs the extraction of the life activity spectrum based on the millimeter wave radar to detect target objects. The maximum likelihood estimation method is used to design the average early warning probability trigger function. Through filtering and Fourier transform, the heartbeat and respiration signals are successfully extracted.
Article
Computer Science, Information Systems
Mengqi Shen, Kwok-Leung Tsui, Maury A. Nussbaum, Sunwook Kim, Fleming Lure
Summary: Indoor fall monitoring for older adults is challenging due to accuracy requirements and privacy concerns. Doppler radar shows promise, but its application is limited by the line-of-sight restriction and similarity of Doppler signatures among different falls. To address these challenges, the researchers conducted an experimental study to obtain Doppler signals under different angles and developed a novel neural network called eMSFRNet. The eMSFRNet showed robustness to radar sensing angles and achieved high accuracy in both fall detection and classification of seven fall types.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Wei-Chih Su, Pin-Hsun Juan, De-Ming Chian, Tzyy-Sheng Jason Horng, Chao-Kai Wen, Fu-Kang Wang
Summary: This article presents a system combining SIL radar, FMCW, and SPA techniques for locating and monitoring multiple individuals' vital signs with high resolution and sensitivity. The system utilizes subharmonic upconverter/downconverter and a 1.675-2.175 GHz chirp signal for signal conversion, and provides a Doppler-weighted RAM for improved image discernibility.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2021)
Article
Engineering, Electrical & Electronic
Emanuele Cardillo, Changzhi Li, Alin Caddemi
Summary: The article introduces a new technique to remove radar self-motion effects for accurate detection of human vital signs without additional sensors, by extracting RSM from signals reflected by stationary clutters. The proposed technique requires accurate clutter range identification, with two automatic identification procedures for different radar motions. Besides precise vital sign detection, it offers a compact, lightweight, comfortable, and cost-effective solution.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Hafiza Irem Turkmen, Mine Elif Karsligil, Ismail Kocak
CURRENT MEDICAL IMAGING
(2019)
Review
Computer Science, Interdisciplinary Applications
H. Irem Turkmen, M. Elif Karsligil
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2019)
Article
Automation & Control Systems
Ayse Bilge Gunduz, Berk Taskin, Ali Gokhan Yavuz, Mine Elif Karsligil
Summary: The combination of colors is crucial in professional design. This study aims to extract dominant colors from images of salient objects by designing a modified architecture and applying clustering algorithms. The effectiveness of the proposed method has been demonstrated through comprehensive experimental survey.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Computer Science, Information Systems
Fuat Ogme, A. Gokhan Yavuz, M. Amac Guvensan, M. Elif Karsligil
Summary: The proposed method utilizes PCA and Autoencoder to extract discriminative features, clusters similar fraudulent transactions with K-Means algorithm, and identifies potential merchants involved in the scheme through retrospective analysis of transaction data. Tests show promising results in detecting compromise points without prior knowledge, pinpointing 7 out of 9 previously identified by the bank.
Proceedings Paper
Engineering, Electrical & Electronic
Berna Yilmaz, M. Elif Karsligil
2020 28TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
(2020)
Proceedings Paper
Engineering, Electrical & Electronic
Fuat Ogme, M. Elif Karsligil, A. Gokhan Yavuz, M. Amac Guvensan
2020 28TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
(2020)
Proceedings Paper
Engineering, Electrical & Electronic
Guven Asci, M. Elif Karsligil
2020 28TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
(2020)
Proceedings Paper
Engineering, Electrical & Electronic
Khadija Hanifi, M. Elif Karsligil
2020 28TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
(2020)
Proceedings Paper
Acoustics
Tasnim Zayet, M. Elif Karsligil
2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
(2017)
Proceedings Paper
Acoustics
Ilkin Huseynli, M. Elif Karsligil
2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
(2017)
Proceedings Paper
Acoustics
Khadija Hanifi, Hasan Bank, M. Elif Karsligil, A. Gokhan Yavuz, M. Amac Guvensan
2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
(2017)
Proceedings Paper
Acoustics
Alper Arik, Mesut Golcuk, Elif Mine Karsligil
2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
(2017)
Article
Computer Science, Information Systems
Baris Can, Ali Gokhan Yavuz, Elif M. Karsligil, M. Amac Guvensan