Photoplethysmography (PPG) is a low-cost and easy-to-implement method to measure vital signs, including heart rate (HR) pulse variability (PRV) which widely used as substitute of (HRV). The in various wearable devices. For example, Samsung smartwatches are PPG-based open-source wristbands remote well-being monitoring fitness applications. However, PPG highly susceptible motion artifacts environmental noise. A validation study required investigate the accuracy devices free-living...

Accurate peak determination from noise-corrupted photoplethysmogram (PPG) signal is the basis for further analysis of physiological quantities such as heart rate. Conventional methods are designed noise-free PPG signals and insufficient with low signal-to-noise ratio (SNR). This paper focuses on enhancing noise-resiliency proposes a robust detection algorithm distorted due to noise motion artifact. Our based convolutional neural networks (CNNs) dilated convolutions. We train evaluate...

Respiration Rate (RR) is a biomarker for several illnesses that can be extracted from biosignals, such as photoplethysmogram (PPG) and accelerometers. Smartwatch-based PPG signals are more prone to noise interference, particularly within their lower frequency spectrum where respiratory data embedded. Therefore, existing methods insufficient extracting RR collected wrists reliably. Additionally, accelerometer sensors embedded in smartwatches capture respiration-induced motion integrated with...

Abstract Background Photoplethysmography (PPG) is a low-cost and easy-to-implement method to measure vital signs, including heart rate (HR) variability (HRV). The widely used in various wearable devices. For example, Samsung smartwatches are PPG-based open-source wristbands remote well-being monitoring fitness applications. However, PPG highly susceptible motion artifacts environmental noise. A validation study required investigate the accuracy of devices free-living conditions. Objective We...

Photoplethysmography (PPG) is a non-invasive technique used in wearable devices to collect various vital signs, including heart rate and variability. The signal highly susceptible motion artifacts, which inevitable health monitoring may lead inaccurate decision-making. Studies the literature proposed time series analysis, decomposition, machine learning methods reconstruct PPG signals or reduce noise. However, they are limited short-term noisy noise caused by certain physical activities. In...

The rapid development of wearable technology has enabled remote photoplethysmography (PPG)-based health monitoring in everyday settings, offering real-time and continuous cardiovascular parameters, such as heart rate (HR) variability (HRV). However, PPG signals collected daily life are prone to artifacts noise, posing challenges HR HRV extraction. existing extraction methods cannot effectively handle noisy ensure accurate results. Additionally, current Python packages were primarily designed...

Respiratory rate (RR) serves as an indicator of various medical conditions, such cardiovascular diseases and sleep disorders. Several studies have employed signal processing machine learning techniques to extract RR from biosignals, photoplethysmogram (PPG). These estimation methods were mostly designed for finger-based PPG collected subjects in stationary situations (e.g., hospitals). In contrast signals, wrist-based are more susceptible noise, particularly their low frequency range, which...

Sleep is crucial for physical, mental, and emotional well-being. Physical activity sleep are known to be interrelated; however, limited research has been performed investigate their interactions in long-term. Conventional studies have presented quality prediction, focusing on a single aspect, such as efficiency. In addition, the relationship between daily physical yet explored, despite activities being utilized previous prediction. this paper, we develop an Extreme Gradient boosting method...

Respiratory rate (RR) serves as an indicator of various medical conditions, such cardiovascular diseases and sleep disorders. These RR estimation methods were mostly designed for finger-based PPG collected from subjects in stationary situations (e.g., hospitals). In contrast to signals, wrist-based are more susceptible noise, particularly their low frequency range, which includes respiratory information. Therefore, the existing struggle accurately extract when data wrist area under...

The concept of Quality Life (QoL) refers to a holistic measurement an individual's well-being, incorporating psychological and social aspects. Pregnant women, especially those with obesity stress, often experience lower QoL. Physical activity (PA) has shown the potential enhance However, pregnant women who are overweight obese rarely meet recommended level PA. Studies have investigated relationship between PA QoL during pregnancy using correlation-based approaches. These methods aim discover...

The concept of Quality Life (QoL) refers to a holistic measurement an individual's well-being, incorporating psychological and social aspects. Pregnant women, especially those with obesity stress, often experience lower QoL. Physical activity (PA) has shown the potential enhance However, pregnant women who are overweight obese rarely meet recommended level PA. Studies have investigated relationship between PA QoL during pregnancy using correlation-based approaches. These methods aim discover...

Abstract In this paper, a novel SIW microwave sensor is designed to accurately determine the broadband complex permittivity of medium loss and dispersive liquids using number higher order modes in 11–20 GHz. To achieve accuracy characterization, equipped with some methods such as Photonic Band Gap method, slow-wave via, new feedline, which enhances quality factor for TE 1,0, n modes. The operating principle based on cavity perturbation technique, resonant properties are utilized extract...

<div>Accurate peak determination from noise-corrupted photoplethysmogram (PPG) signal is the basis for further analysis of physiological quantities such as heart rate and variability. In past decades, many methods have been proposed to provide reliable detection. These detection include rule-based algorithms, adaptive thresholds, processing techniques. However, they are designed noise-free PPG signals insufficient with low signal-to-noise ratio (SNR). This paper focuses on enhancing...

This work presents a novel microwave sensor that is specially designed for retrieval of complex permittivity. The operating frequency range the C band (4.54 GHz) and tapered feeding topology implemented to achieve higher quality factor coupling. equipped with multiple techniques such as Photonic Band Gap, Slow-Wave vias, which enhances sensitivity significantly. These increase interaction between material under test electric field. By utilizing slow-wave via, miniaturization 35% achieved....

In this paper, we study the spectral efficiency (SE) and energy (EE) of wireless-powered full-duplex (FD) heterogeneous networks (HetNets).In particular, consider a two-tire HetNet with half duplex (HD) massive multiple-input multiple-output (MIMO) macrocell base stations (MBSs), FD small cell (SBSs) user equipments (UEs).UEs rely on harvesting (EH) from radio frequency signals to charge their batteries for communication serving stations.During phase, UEs are associated MBSs/SBSs based mean...

<div>Accurate peak determination from noise-corrupted photoplethysmogram (PPG) signal is the basis for further analysis of physiological quantities such as heart rate and variability. In past decades, many methods have been proposed to provide reliable detection. These detection include rule-based algorithms, adaptive thresholds, processing techniques. However, they are designed noise-free PPG signals insufficient with low signal-to-noise ratio (SNR). This paper focuses on enhancing...

<div>Accurate peak determination from noise-corrupted photoplethysmogram (PPG) signal is the basis for further analysis of physiological quantities such as heart rate and variability. In past decades, many methods have been proposed to provide reliable detection. These detection include rule-based algorithms, adaptive thresholds, processing techniques. However, they are designed noise-free PPG signals insufficient with low signal-to-noise ratio (SNR). This paper focuses on enhancing...

<div>Accurate peak determination from noise-corrupted photoplethysmogram (PPG) signal is the basis for further analysis of physiological quantities such as heart rate and variability. In past decades, many methods have been proposed to provide reliable detection. These detection include rule-based algorithms, adaptive thresholds, processing techniques. However, they are designed noise-free PPG signals insufficient with low signal-to-noise ratio (SNR). This paper focuses on enhancing...