Radar-based contactless heart beat detection with a modified Pan-Tompkins algorithm.

Using radar for non-contact measuring human vital signs has garnered significant attention due to its undeniable benefits. However, achieving reasonably good accuracy in contactless measurement senarios is still a technical challenge.The proposed method includes two stages.

Non-invasive acquisition of vital data in anesthetized rats using laser and radar application.

The aim of this study was to verify the possibility of obtaining vital sign information using a laser and radar sensor in a manner that is non-invasive and painless for test animals. A dataset was obtained from respiratory movement of anaesthetized male F344 rats, signals of laser and radar sensors were recorded simultaneously with vital data acquired with an integrated multiple-channel intraoperative monitor. In addition, respiratory movements were also video recorded, and used as reference data of respiration rate (RR; ref-RR).

Updating ``Medical radar signal dataset for non-contact respiration and heart rate measurement" with expanded data on laboratory rats under isoflurane anesthesia.

The dataset presented in this article is an update of the dataset provided by K. Edanami and G. Sun entitled "Medical Radar Signal Dataset for Non-Contact Respiration and Heart Rate Measurement" [1].

Study on the Autonomous Non-contact Measurement of Biometric Signals.

In this study, we developed a robot that can recognize and track a person, and autonomously measure two biological signals, respiration rate and heart rate, in a non-contact manner. Through experiments, we confirmed that both signals can be measured with high accuracy and that the robot can perform the measurement under conditions similar to those in actual workplaces. We also investigated factors that can affect the accuracy of the non-contact measurement and studied a method to evaluate the reliability of the measured signals.

Pulse rate variability estimation method based on imaging-photoplethysmography and application to telepsychiatry.

The worldwide adoption of telehealth services may benefit people who otherwise would not be able to access mental health support. In this paper, we present a novel algorithm to obtain reliable pulse and respiration signals from non-contact facial image sequence analysis. The proposed algorithm involved a skin pixel extraction method in the image processing part and signal reconstruction using the spectral information of RGB signal in the signal processing part.

Changes in alpha, theta, and gamma oscillations in distinct cortical areas are associated with altered acute pain responses in chronic low back pain patients.

Introduction: Chronic pain negatively impacts a range of sensory and affective behaviors. Previous studies have shown that the presence of chronic pain not only causes hypersensitivity at the site of injury but may also be associated with pain-aversive experiences at anatomically unrelated sites. While animal studies have indicated that the cingulate and prefrontal cortices are involved in this generalized hyperalgesia, the mechanisms distinguishing increased sensitivity at the site of injury from a generalized site-nonspecific enhancement in the aversive response to nociceptive inputs are not well known.

Major Depressive Disorder and Chronic Fatigue Syndrome Show Characteristic Heart Rate Variability Profiles Reflecting Autonomic Dysregulations: Differentiation by Linear Discriminant Analysis.

Major depressive disorder (MDD) and chronic fatigue syndrome (CFS) have overlapping symptoms, and differentiation is important to administer the proper treatment. The present study aimed to assess the usefulness of heart rate variability (HRV) indices. Frequency-domain HRV indices, including high-frequency (HF) and low-frequency (LF) components, their sum (LF+HF), and their ratio (LF/HF), were measured in a three-behavioral-state paradigm composed of initial rest (Rest), task load (Task), and post-task rest (After) periods to examine autonomic regulation.

Temporal pain processing in the primary somatosensory cortex and anterior cingulate cortex.

Pain is known to have sensory and affective components. The sensory pain component is encoded by neurons in the primary somatosensory cortex (S1), whereas the emotional or affective pain experience is in large part processed by neural activities in the anterior cingulate cortex (ACC). The timing of how a mechanical or thermal noxious stimulus triggers activation of peripheral pain fibers is well-known.

Remote sensing of vital signs by medical radar time-series signal using cardiac peak extraction and adaptive peak detection algorithm: Performance validation on healthy adults and application to neonatal monitoring at an NICU.

Background And Objective: Continuous monitoring of vital signs plays a pivotal role in neonatal intensive care units (NICUs). In this paper, we present a system for monitoring fully non-contact medical radar-based vital signs to measure the respiratory rate (RR), heart rate (HR), I:E ratio, and heart rate variability (HRV). In addition, we evaluated its performance in a physiological laboratory and examined its adaptability in an NICU.

Deep Learning Approach for Classifying Bacteria types using Morphology of Bacterial Colony.

The significant bottlenecks in determining bacterial species are much more time-consuming and the biology specialist's long-term experience requirements. Specifically, it takes more than half a day to cultivate a bacterium, and then a skilled microbiologist and a costly specialized machine are utilized to analyze the genes and classify the bacterium according to its nucleotide sequence. To overcome these issues as well as get higher recognition accuracy, we proposed applying convolutional neural networks (CNNs) architectures to automatically classify bacterial species based on some key characteristics of bacterial colonies.

An mHealth App for the Non-contact Measurement of Pulmonary Function Using the Smartphone's Built-in Depth Sensor.

The use of smartphones in clinical practice is referred to as mobile health (mHealth). This has attracted great interest in both academia and industry because of its potential to augment healthcare. In this study, we developed an mHealth app for the non-contact measurement of chest-wall movements using the iPhone ' s built-in depth sensor, thereby enabling a pulmonary self-monitoring function for personal use.

TFAP4 Activates IGF2BP1 and Promotes Progression of Non-Small Cell Lung Cancer by Stabilizing TK1 Expression through m6A Modification.

Unlabelled: Non-small cell lung cancer (NSCLC) is a well-known global health concern. TFAP4 has been reported to function as an oncogene. This study sought to investigate the molecular mechanism of TFAP4 in NSCLC development.

Development of a Novel Vital-Signs-Based Infection Screening Composite-Type Camera With Truncus Motion Removal Algorithm to Detect COVID-19 Within 10 Seconds and Its Clinical Validation.

To conduct a rapid preliminary COVID-19 screening prior to polymerase chain reaction (PCR) test under clinical settings, including patient's body moving conditions in a non-contact manner, we developed a mobile and vital-signs-based infection screening composite-type camera (VISC-Camera) with truncus motion removal algorithm (TMRA) to screen for possibly infected patients. The VISC-Camera incorporates a stereo depth camera for respiratory rate (RR) determination, a red-green-blue (RGB) camera for heart rate (HR) estimation, and a thermal camera for body temperature (BT) measurement. In addition to the body motion removal algorithm based on the region of interest (ROI) tracking for RR, HR, and BT determination, we adopted TMRA for RR estimation.

Closed-loop stimulation using a multiregion brain-machine interface has analgesic effects in rodents.

Effective treatments for chronic pain remain limited. Conceptually, a closed-loop neural interface combining sensory signal detection with therapeutic delivery could produce timely and effective pain relief. Such systems are challenging to develop because of difficulties in accurate pain detection and ultrafast analgesic delivery.

KBTBD7 promotes non-small cell lung carcinoma progression by enhancing ubiquitin-dependent degradation of PTEN.

The Kelch repeat and BTB domain containing 7 (KBTBD7) was first cloned in 2010. Its function as a transcriptional activator and a substrate adaptor during the ubiquitination process was soon found. KBTBD7 was shown to be involved in excessive inflammation after myocardial infarction, brain development, and neurofibromin stability.

Interictal EEG and ECG for SUDEP Risk Assessment: A Retrospective Multicenter Cohort Study.

Objective: Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality. Although lots of effort has been made in identifying clinical risk factors for SUDEP in the literature, there are few validated methods to predict individual SUDEP risk. Prolonged postictal EEG suppression (PGES) is a potential SUDEP biomarker, but its occurrence is infrequent and requires epilepsy monitoring unit admission.

Frequency Dependent Electrical Stimulation of PFC and ACC for Acute Pain Treatment in Rats.

As pain consists of both sensory and affective components, its management by pharmaceutical agents remains difficult. Alternative forms of neuromodulation, such as electrical stimulation, have been studied in recent years as potential pain treatment options. Although electrical stimulation of the brain has shown promise, more research into stimulation frequency and targets is required to support its clinical applications.

Medical Radar Signal Dataset for Non-Contact Respiration and Heart Rate Measurement.

Medical radars remotely measure the periodic movements of the chest wall induced by breathing and heartbeat and have been widely recognized in healthcare. To the best of our knowledge, no well-characterized medical radar datasets are shared publicly. Therefore, in this article, we provide non-contact respiratory and cardiac signal datasets measured using a medical radar and simultaneously measured reference signals using electrocardiogram (ECG) and respiratory belt transducer.

Evaluation of Remote Photoplethysmography Measurement Conditions toward Telemedicine Applications.

Camera-based remote photoplethysmography (rPPG) is a low-cost and casual non-contact heart rate measurement method suitable for telemedicine. Several factors affect the accuracy of measuring the heart rate and heart rate variability (HRV) using rPPG despite HRV being an important indicator for healthcare monitoring. This study aimed to investigate the appropriate setup for precise HRV measurements using rPPG while considering the effects of possible factors including illumination, direction of the light, frame rate of the camera, and body motion.

Non-contact Measurement of Pulse Rate Variability Using a Webcam and Application to Mental Illness Screening System.

The COVID-19 pandemic is a global health crisis. Mental health is critical in such uncertain situations, particularly when people are required to significantly restrict their movements and change their lifestyles. Under these conditions, many countries have turned to telemedicine to strengthen and expand mental health services.

Design and Evaluation of Digital Filters for Non-Contact Measuring of HRV using Medical Radar and Its Application in Bedside Patient Monitoring System.

A non-contact bedside monitoring system using medical radar is expected to be applied to clinical fields. Our previous studies have developed a monitoring system based on medical radar for measuring respiratory rate (RR) and heart rate (HR). Heart rate variability (HRV), which is essentially implemented in advanced monitoring system, such as prognosis prediction, is a more challenging biological information than the RR and HR.

Proof-of-principle Experiment on 24 GHz Medical Radar for Non-contact Vital Signs Measurement.

Medical radar for non-contact vital signs measurement exhibits great potential in both clinical and home healthcare settings. Especially during the corona virus spreading time, non-contact sensing more clearly shows the advantages. Many previous studies have concentrated on medical radar-based healthcare applications, but pay less attention to the working principles.