A Review: Recent Progress in the Design and Development of Nonlinear Radars

This paper presents an extensive review of nonlinear response-based radar systems. Nonlinear radars are generally used for clutter suppression purposes. These radars detect the nonlinear response generated by diodes and transistors are used as a tag for target localization. Utilizing the nonlinearity properties of these devices, these radars have been used for purposes including locating humans trapped in earthquakes and avalanches, identifying migratory patterns of animals, examining the flight pattern of bees, and detecting bugs in electronic devices. This paper covers the utilization of these radars in human vital signs monitoring, detecting targets in a clutter-rich environment, etc. State-of-the-art nonlinear radars’ high-level architectures, design challenges, and limitations are discussed here. Recent works and results obtained by the authors are also summarized.

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Efficient End-to-End Sentence-Level Lipreading with Temporal Convolutional Networks

Applied Sciences ◽

10.3390/app11156975 ◽

2021 ◽

Vol 11 (15) ◽

pp. 6975

Author(s):

Tao Zhang ◽

Lun He ◽

Xudong Li ◽

Guoqing Feng

Keyword(s):

Performance Improvement ◽

State Of The Art ◽

Error Rates ◽

Convolutional Network ◽

Convolutional Networks ◽

Sentence Level ◽

End To End ◽

High Level ◽

Improved Accuracy ◽

Talking Face

Lipreading aims to recognize sentences being spoken by a talking face. In recent years, the lipreading method has achieved a high level of accuracy on large datasets and made breakthrough progress. However, lipreading is still far from being solved, and existing methods tend to have high error rates on the wild data and have the defects of disappearing training gradient and slow convergence. To overcome these problems, we proposed an efficient end-to-end sentence-level lipreading model, using an encoder based on a 3D convolutional network, ResNet50, Temporal Convolutional Network (TCN), and a CTC objective function as the decoder. More importantly, the proposed architecture incorporates TCN as a feature learner to decode feature. It can partly eliminate the defects of RNN (LSTM, GRU) gradient disappearance and insufficient performance, and this yields notable performance improvement as well as faster convergence. Experiments show that the training and convergence speed are 50% faster than the state-of-the-art method, and improved accuracy by 2.4% on the GRID dataset.

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Longitudinal remotely mentored self-performed lung ultrasound surveillance of paucisymptomatic Covid-19 patients at risk of disease progression

The Ultrasound Journal ◽

10.1186/s13089-021-00231-9 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Andrew W. Kirkpatrick ◽

Jessica L. McKee ◽

John M. Conly

Keyword(s):

At Risk ◽

Lung Ultrasound ◽

Point Of Care ◽

Human Life ◽

Vital Signs ◽

Home Monitoring ◽

Cost Effective ◽

Care Providers ◽

Vital Signs Monitoring ◽

Ultrasound Probes

AbstractCOVID-19 has impacted human life globally and threatens to overwhelm health-care resources. Infection rates are rapidly rising almost everywhere, and new approaches are required to both prevent transmission, but to also monitor and rescue infected and at-risk patients from severe complications. Point-of-care lung ultrasound has received intense attention as a cost-effective technology that can aid early diagnosis, triage, and longitudinal follow-up of lung health. Detecting pleural abnormalities in previously healthy lungs reveal the beginning of lung inflammation eventually requiring mechanical ventilation with sensitivities superior to chest radiographs or oxygen saturation monitoring. Using a paradigm first developed for space-medicine known as Remotely Telementored Self-Performed Ultrasound (RTSPUS), motivated patients with portable smartphone support ultrasound probes can be guided completely remotely by a remote lung imaging expert to longitudinally follow the health of their own lungs. Ultrasound probes can be couriered or even delivered by drone and can be easily sterilized or dedicated to one or a commonly exposed cohort of individuals. Using medical outreach supported by remote vital signs monitoring and lung ultrasound health surveillance would allow clinicians to follow and virtually lay hands upon many at-risk paucisymptomatic patients. Our initial experiences with such patients are presented, and we believe present a paradigm for an evolution in rich home-monitoring of the many patients expected to become infected and who threaten to overwhelm resources if they must all be assessed in person by at-risk care providers.

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TELECOVID: Remote Vital Signs Monitoring of COVID-19 Risk Patients in Home Isolation With an In-Ear Wearable

IEEE Pervasive Computing ◽

10.1109/mprv.2021.3066825 ◽

2021 ◽

Vol 20 (2) ◽

pp. 58-62

Author(s):

Melanie Baldinger ◽

Axel Heinrich ◽

Tim Adams ◽

Eimo Martens ◽

Michael Dommasch ◽

...

Keyword(s):

Vital Signs ◽

Vital Signs Monitoring ◽

Risk Patients

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Caged-electron States and Split-electron States in Endohedral Alkali C60

Physical Chemistry Chemical Physics ◽

10.1039/d1cp01341f ◽

2021 ◽

Author(s):

yifan yang ◽

Lorenz S Cederbaum

Keyword(s):

State Of The Art ◽

Electronic States ◽

Electron States ◽

The Common ◽

High Level

The low-lying electronic states of neutral X@C60(X=Li, Na, K, Rb) have been computed and analyzed by employing state-of-the-art high level many-electron methods. Apart from the common charge-separated states, well known...

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2-D Localization, Angular Separation and Vital Signs Monitoring Using a SISO FMCW Radar for Smart Long-term Health Monitoring Environments

IEEE Internet of Things Journal ◽

10.1109/jiot.2021.3051580 ◽

2021 ◽

pp. 1-1

Author(s):

Marco Mercuri ◽

Giulia Sacco ◽

Rainer Hornung ◽

Peng Zhang ◽

Huib Visser ◽

...

Keyword(s):

Health Monitoring ◽

Vital Signs ◽

Angular Separation ◽

Fmcw Radar ◽

Vital Signs Monitoring

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Systematic Review on Human Skin-Compatible Wearable Photoplethysmography Sensors

Applied Sciences ◽

10.3390/app11052313 ◽

2021 ◽

Vol 11 (5) ◽

pp. 2313

Author(s):

Inho Lee ◽

Nakkyun Park ◽

Hanbee Lee ◽

Chuljin Hwang ◽

Joo Hee Kim ◽

...

Keyword(s):

Systematic Review ◽

Health Care ◽

Real Time ◽

Human Skin ◽

State Of The Art ◽

Electronic Devices ◽

Semiconducting Materials ◽

Physiological Conditions ◽

Technological Developments ◽

Monitoring Technologies

The rapid advances in human-friendly and wearable photoplethysmography (PPG) sensors have facilitated the continuous and real-time monitoring of physiological conditions, enabling self-health care without being restricted by location. In this paper, we focus on state-of-the-art skin-compatible PPG sensors and strategies to obtain accurate and stable sensing of biological signals adhered to human skin along with light-absorbing semiconducting materials that are classified as silicone, inorganic, and organic absorbers. The challenges of skin-compatible PPG-based monitoring technologies and their further improvements are also discussed. We expect that such technological developments will accelerate accurate diagnostic evaluation with the aid of the biomedical electronic devices.

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Textile-based fiber optic sensors for health monitoring: A systematic and citation network analysis review

Textile Research Journal ◽

10.1177/00405175211036206 ◽

2021 ◽

pp. 004051752110362

Author(s):

Ka-Po Lee ◽

Joanne Yip ◽

Kit-Lun Yick ◽

Chao Lu ◽

Chris K Lo

Keyword(s):

Network Analysis ◽

Fiber Optic ◽

Vital Signs ◽

Citation Network ◽

Fiber Optic Sensors ◽

Superior Performance ◽

Vital Signs Monitoring ◽

Wear Comfort ◽

Citation Network Analysis ◽

Research Domains

Receptivity towards textile-based fiber optic sensors that are used to monitor physical health is increasing as they have good flexibility, are light in weight, provide wear comfort, have electromagnetic immunity, and are electrically safe. Their superior performance has facilitated their use for obtaining close to body measurements. However, there are many related studies in the literature, so it is challenging to identify the knowledge structure and research trends. Therefore, this article aims to provide an objective and systematic literature review on textile-based fiber optic sensors that are used for monitoring health issues and to analyze their trends through a citation network analysis. A full-text search of journal articles was conducted in the Web of Science Core Collection, and a total of 625 studies was found, with 47 that were used as the sample. Also, CitNetExplorer was used for analyzing the research domains and trends. Three research domains were identified, among them, “Flexible sensors for vital signs monitoring” is the largest research cluster, and most of the articles in this cluster focus on respiratory monitoring. Therefore, this area of study should probably be on the academic radar. The collection of data on textile-based fiber optic sensors is invaluable for evaluating degree of rehabilitation, detecting diseases, preventing accidents, as well as gauging the performance and training successfulness of athletes.

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