Human Physiological Parameters Research Articles

Health risk assessment of residential overheating under the heat waves in Guangzhou

During extreme heatwave events, indoor overheating caused by power outages poses a significant threat to human health, especially for low-income groups exposed to hot and humid conditions for extended periods. However, currently, the definition and quantification standards for indoor overheating are not well-defined, and relying solely on thermal comfort indicators is insufficient to accurately assess the health risks associated with indoor overheating. This study proposes the use of maximum heat index (HImax) and heat index hazard hours when the heat index exceeds the caution level (HIHHCaution) to assess the health risk of indoor overheating. Taking various types of residential buildings in Guangzhou as examples, the study employs field surveys, simulation analysis, and statistical regression to analyze the impact of power outages during heatwaves on the indoor thermal environment and key human thermal physiological parameters, thereby establishing the basis for measuring indoor overheating and reference thresholds for assessing heat health risks. The results indicate that for young adults and the elderly, HIHHCaution exceeding 1174 °C·h and 850 °C·h respectively, or HImax nearing 55 °C, are likely to result in heat-related illnesses. In Guangzhou, most urban village housing with poor insulation cannot withstand the risk of power outages lasting more than a day during heatwaves, while old housing and commodity housing that meets the energy-efficiency standards of different periods still face varying degrees of indoor overheating risk. The findings enhance understanding of indoor overheating health risks and provide a scientific basis for strategies to improve living environments during heatwaves.

Quantitatively Predicting Effects of Exercise on Pharmacokinetics of Drugs Using a Physiologically Based Pharmacokinetic Model.

Exercise significantly alters human physiological functions, such as increasing cardiac output and muscle blood flow and decreasing glomerular filtration rate (GFR) and liver blood flow, thereby altering the absorption, distribution, metabolism, and excretion of drugs. In this study, we aimed to establish a database of human physiological parameters during exercise and to construct equations for the relationship between changes in each physiological parameter and exercise intensity, including cardiac output, organ blood flow (e.g., muscle blood flow and kidney blood flow), oxygen uptake, plasma pH and GFR, etc. The polynomial equation P = ΣaiHRi was used for illustrating the relationship between the physiological parameters (P) and heart rate (HR), which served as an index of exercise intensity. The pharmacokinetics of midazolam, quinidine, digoxin, and lidocaine during exercise were predicted by a whole-body physiologically based pharmacokinetic (WB-PBPK) model and the developed database of physiological parameters following administration to 100 virtual subjects. The WB-PBPK model simulation results showed that most of the observed plasma drug concentrations fell within the 5th-95th percentiles of the simulations, and the estimated peak concentrations (Cmax) and area under the curve (AUC) of drugs were also within 0.5-2.0 folds of observations. Sensitivity analysis showed that exercise intensity, exercise duration, medication time, and alterations in physiological parameters significantly affected drug pharmacokinetics and the net effect depending on drug characteristics and exercise conditions. In conclusion, the pharmacokinetics of drugs during exercise could be quantitatively predicted using the developed WB-PBPK model and database of physiological parameters. SIGNIFICANCE STATEMENT: This study simulated real-time changes of human physiological parameters during exercise in the WB-PBPK model and comprehensively investigated pharmacokinetic changes during exercise following oral and intravenous administration. Furthermore, the factors affecting pharmacokinetics during exercise were also revealed.

A microfluidic patch for wireless wearable electrochemical detection of sweat metabolites

Wearable sweat sensors provide an innovative detection method for analyzing human physiological and biochemical parameters and play an important role in detecting the potential risks of chronic diseases. Existing commercial wearable sensors (Apple iWatch, HUAWEI smart band) have problems such as single detection index (heart rate or blood pressure), and mainly focus on the physical information. This work studied an integrated microfluidic patch to simultaneously detect several biomarkers (pH, sodium ions, and uric acid) in sweat. We achieved the detection of pH level, sodium, and uric acid in linear ranges of 4–8, 0–160 mM, and 5–160 μM, respectively, covering well the clinically relevant ranges in the healthy human sweat. Laser engraving was chosen to prepare a microfluidic layer, and the sweat collection function was realized by combining hydrophilic and hydrophobic microfluidic synergy. It could efficiently collect the required sweat sample volume (80 μL) within 30 s while avoiding the contamination caused by directly contact with the skin. In addition, a wireless signal acquisition and transmission system was designed with the signal reading, processing, and wireless transmission functions, which can display the testing results in real time on Android phone-specific application software. We combined the wireless system with a microfluidic patch for on-body testing to verify the good wearability of the sweat sensor. This research realized the wireless data processing and transmission while improving sweat collection efficiency. In addition, it could detect various sweat physiological components in real-time, and provides a multiparameter, real-time, and portable sensing platform.

Effect of solar radiation on human thermal sensation and physiological parameters in a convection–radiation air conditioning environment

Effect of solar radiation on human thermal sensation and physiological parameters in a convection–radiation air conditioning environment

Metoda pomiaru temperatury ciała człowieka za pomocą kamery termowizyjnej

Measurement and monitoring of human physiological parameters play an important role in many applications such as health care, sports training and prevention of disease spread. Dynamic changes in physiological parameters can reveal not only changes in a patient’s physiological state and function, but also be used to assess a person’s activity status, fitness and fatigue. Body temperature is among the most important human physiological parameters for assessing basic vital functions, apart from heart rate, blood pressure and respiratory rate. In medical practice, various types of measuring instruments are used to measure temperature, such as liquid thermometers, electronic thermometers, non-contact ear thermometers, non-contact forehead thermometers. Liquid and electronic thermometers require the appropriate sensors to be connected to a person, which may be undesirable or impossible as, for example, in newborns or during sports training. Non-contact thermometers operate over short distances and often force a specific position of the person during the measurement. In addition, the above body temperature measurement techniques require direct supervision by medical personnel, which often reduces the effectiveness and efficiency of screening temperature measurement. In screening temperature measurements of a large number of people, especially those on the move, a measuring thermal imaging camera works well. The article presents a method for measuring human body temperature using a thermal imaging camera. The presented method is characterized by high accuracy of temperature measurement, which allows medical use of the obtained measurements. The measurement method has been tested on a test stand and for a selected test sample of people. The measurements and tests carried out confirmed the possibility of obtaining temperature measurement accuracy with an expanded uncertainty of less than 0.05 K with a resolution of less than 0.1 K.

Physiologically Based Pharmacokinetic Modeling and Clinical Extrapolation for Topical Application of Pilocarpine on Eyelids: A Comprehensive Study

Exploiting a convenient and highly bioavailable ocular drug delivery approach is currently one of the hotspots in the pharmaceutical industry. Eyelid topical application is seen to be a valuable strategy in the treatment of chronic ocular diseases. To further elucidate the feasibility of eyelid topical administration as an alternative route for ocular drug delivery, pharmacokinetic and pharmacodynamic studies of pilocarpine were conducted in rabbits. Besides, a novel physiologically based pharmacokinetic (PBPK) model describing eyelid transdermal absorption and ocular disposition was developed in rabbits. The PBPK model of rabbits was extrapolated to human by integrating the drug-specific permeability parameters and human physiological parameters to predict ocular pharmacokinetic in human. After eyelid topical application of pilocarpine, the concentration of pilocarpine in iris peaked at 2 h with the value of 18,724 ng/g and the concentration in aqueous humor peaked at 1 h with the value of 1,363 ng/mL. Significant miotic effect were observed from 0.5 h to 4.5 h after eyelid topical application of pilocarpine in rabbits, while that were observed from 0.5 h to 3.5 h after eyedrop instillation. The proposed eyelid PBPK model was capable of reasonably predicting ocular exposure of pilocarpine after application on the eyelid skin and based on the PBPK model, the human ocular concentration was predicted to be 10-fold lower than that in rabbits. And it was suggested that drugs applied on the eyelid skin could transfer into the eyeball through corneal pathway and scleral pathway. This work could provide pharmacokinetic and pharmacodynamic data for the development of eyelid drug delivery, as well as the reference for clinical applications.

Space Weather Effects on Heart Rate Variations: Sex Dependence

The effects of solar activity and the accompanying space weather events on human pathological conditions, physiological parameters and other psycho-physiological disturbances have been analyzed in numerous recent investigations. Moreover, many of these studies have particularly focused on the different physical reactions humans have, according to their sex, during variations in the physical environment. In the framework of the above, this work analyses heart rate data obtained from volunteers (687 men and 534 women) from three different regions (Athens, Piraeus and Heraklion) of Greece in relation to the geophysical activity and variations of environmental factors. Dst index and Ap index data, along with cosmic ray intensity data derived from the Athens Neutron Monitor Station (A.Ne.Mo.S.), were used. The study expands from April 2011 to January 2018, covering solar cycle 24. The ANalysis Of Variance (ANOVA) and the superimposed epochs methods were used in order to examine heart rate variations depending on sex. Results revealed that women tend to be more sensitive to physical environmental changes. Statistically significant results are related to the geomagnetic activity but were not obtained for cosmic ray variations.

Design of Wearable Human Physiological Parameter Acquisition System Based on Fiber Bragg Grating Sensors

Design of Wearable Human Physiological Parameter Acquisition System Based on Fiber Bragg Grating Sensors

Identification of Faulty Sensor Nodes in WBAN Using Genetically Linked Artificial Neural Network

Wireless Body Area Networks (WBANs) have risen as a promising innovation for checking humanphysiological parameters in real time. Be that as it may, the unwavering quality and precision of WBANs dependon the right working of sensor hubs. The distinguishing proof of defective sensor hubs is vital for guaranteeing thequality of information collected by WBANs. In this paper, we propose a novel approach to recognizing faultysensor hubs in WBAN employing a hereditarily linked artificial neural organize (GLANN). The GLANN isprepared to employ a crossbreed fuzzy-genetic calculation to optimize its execution in distinguishing defectivesensor hubs. The proposed approach is assessed employing a dataset collected from a real-world WBAN. Thecomes about appears that the GLANN-based approach beats existing strategies in terms of exactness andproficiency. The proposed approach has potential applications within the field of healthcare, where exact and solidobserving of human physiological parameters is basic for conclusion and treatment. By and large, this ponderpresents a promising approach to progressing the unwavering quality and exactness of WBANs by identifyingflawed sensor hubs utilizing GLANN .

Validation and verification framework and data integration of biosensors and invitro diagnostic devices: a position statement of the IFCC Committee on Mobile Health and Bioengineering in Laboratory Medicine (C-MBHLM) and the IFCC Scientific Division.

Advances in technology have transformed healthcare and laboratory medicine. Biosensors have emerged as a promising technology in healthcare, providing a way to monitor human physiological parameters in a continuous, real-time, and non-intrusive manner and offering value and benefits in a wide range of applications. This position statement aims to present the current situation around biosensors, their perspectives and importantly the need to set the framework for their validation and safe use. The development of a qualification framework for biosensors should be conceptually adopted and extended tocover digitally measured biomarkers from biosensors for advancing healthcare and achieving more individualized patient management and better patient outcome.

Geomagnetic and Cosmic Ray Activity Effect on Heart Rate during the Solar Cycle 24

The number of investigations relevant to the study of geomagnetic activity, solar events, and cosmic rays, i.e., space weather phenomena, and their impact on human health has increased dramatically over the past few years. Numerous studies examine the reaction of the cardiovascular, nervous, and other functional systems to variations observed in geospace. These studies examine the behavior of human physiological parameters not only during different levels of activity of the Sun and in the interplanetary space (from no activity to remarkably intense activity) but also through geomagnetic activity storms and Forbush decreases. Here, individuals from the Hippocratio General Hospital in Athens, the cardiology clinics of Nikaia General Hospital in Piraeus, and the Heraklion University Hospital in Crete, Greece, were assessed during the time period from 2011 until 2018. The heart rate of the individuals was recorded every hour via the Holter electrocardiogram method. Data were analyzed using the analysis of variance (ANOVA) and the method of superimposed epochs. The investigation covers not only the ascending but also the descending phase of the solar cycle 24 (lasting until 2019 and with its maximum in the year 2014).

Thermal Comfort Model Established by Using Machine Learning Strategies Based on Physiological Parameters in Hot and Cold Environments

The air-conditioning systems have become an indispensable part of our daily life for keeping the quality of life. However, to improve the thermal comfort and reduce energy consumption is crucial to use the air conditioners effectively with rapid development of artificial intelligence technology. This study explored the correlation between the response of human physiological parameters and thermal sensation voting (TSV) to evaluate the comfort level among various cold and hot stimulations. The variations of the three physiological parameters, which were body surface temperature, skin blood flow (SBF), and sweat area on the skin surface, and TSV values were all positively correlated with the stimulation amount under the stimulation of cold wind, hot wind, and heat radiation, but the relationship was not completely linear. Among the three physiological parameters, the forehead skin temperature has the closest relationship with TSV, followed by the SBF and sweat. Among three stimulations, the cold wind stimulation causes the closest relationship between TSV and forehead temperature, followed by the radiation and hot wind stimulations. Through three different machine learning models, namely, random forest (RF) model, support vector machine (SVM) model, and neural network (NN) model, the stimulation of cold wind, hot wind, and heat radiation was applied to investigate the variation of the three physiological parameters as the input of the models. Moreover, the models were evaluated and verified by TSV. The results revealed that among the three different machine learning methods, RF had the best accuracy. The established thermal comfort models can predict the real-time user’s thermal comfort feeling, so that air-conditioning equipment’s performance can be optimized to create a healthy and energy-saving comfortable environment.

Research on the Heating Effect of a Convection Radiator Based on a Human Thermophysiological Model

Forced convection is the most effective way to improve the thermal efficiency of a radiator under low-temperature conditions. This technical method differs significantly from the heating effects of general radiation and natural convection. Few studies have applied the objective evaluation method based on quantitative calculation to evaluate the effectiveness of indoor heating or optimize the technical parameters (air flow rate, air supply method, etc.) of heating systems. This article couples human metabolic factors with heating environmental factors and uses a 57-node human thermal physiological model to evaluate the effectiveness of forced convection radiator heating from the perspective of the local thermal comfort of the human body and demonstrates the feasibility of this scheme by comparing it with floor radiation heating. The research shows that the air supply speed of a radiator affects human thermal comfort. Continuing to increase the wind speed, at a speed of 3 m/s, the surface temperature of the human body reaches a high value and will then decrease, leading to a decrease in thermal comfort. Research on indoor air distribution shows that the use of bottom-side air supply provides better thermal comfort compared to top air supply. The local skin temperature distribution of the human body indicates that when the indoor average temperature is higher than 20 °C, the overall thermal comfort of convective radiator heating and floor radiant heating is comparable. The article provides a way of objectively calculating and directly quantifying the effect of heating equipment on human thermal physiological parameters.

Application of Smart Wearable Devices in Sports Performance Analysis and Enhancement

Abstract Sports characteristics and physiological signals serve as critical benchmarks for analyzing athletic performance and enhancing training methodologies. This study explores the design and development of an advanced smart wearable device system tailored for monitoring sports training. This system is engineered to track athletic performance in real-time by integrating embedded wearable devices with sophisticated software. It primarily encompasses the recognition of human movement states, detection of electrocardiogram (ECG) signals, and monitoring of respiratory signals, thereby facilitating comprehensive analysis of human physiological parameters and movement metrics. This, in turn, supports athletes in optimizing their training routines. Empirical results from the study indicate that the mean-square error for both ECG and respiratory signals recorded during testing approximated ±0.8Hz, falling within the predetermined error tolerance range. Additionally, analyses of joint angle variations during running activities confirmed the efficacy of the proposed smart wearable system in improving sports performance.

Conductive and Eco-friendly Biomaterials-based Hydrogels for Noninvasive Epidermal Sensors: A Review.

As noninvasive wearable electronic devices, epidermal sensors enable continuous, real-time, and remote monitoring of various human physiological parameters. Conductive biomaterials-based hydrogels as sensor matrix materials have good biocompatibility, biodegradability, and efficient stimulus response capabilities and are widely applied in motion monitoring, healthcare, and human-machine interaction. However, biomass hydrogel-based epidermal sensing devices still need excellent mechanical properties, prolonged stability, multifunctionality, and extensive practicality. Therefore, this paper reviews the common biomass hydrogel materials for epidermal sensing (proteins, polysaccharides, polyphenols, etc.) and the various types of noninvasive sensing devices (strain/pressure sensors, temperature sensors, glucose sensors, electrocardiograms, etc.). Moreover, this review focuses on the strategies of scholars to enhance sensor properties, such as strength, conductivity, stability, adhesion, and self-healing ability. This work will guide the preparation and optimization of high-performance biomaterials-based hydrogel epidermal sensors.

Research on electronic stethoscope system and signal processing algorithm

Stethoscopes have an important role in non-invasive diagnosis of cardiovascular and respiratory diseases, digestive diseases, and other kinds of diseases. The emergence of high-end diagnostic devices and new diagnostic methods have caused the status of the stethoscope to decline. However, stethoscope has the advantages of simple operation, mature auscultation theory and low cost, and thus is still widely used in medical diagnosis. This paper first introduces the design and application of electronic stethoscope solutions based on contact sensors and air coupling sensors, and then introduces advanced algorithms for digital signal processing for the diagnosis and treatment of different diseases, including heart sound noise reduction algorithm, heart sound segmentation algorithm and heart sound feature extraction and recognition algorithm. Finally, this paper summarizes the application of the electronic stethoscope system in medical testing, and its future development direction. In summary, the electronic stethoscope system is a reliable medical testing tool, which can convert sound signals into digital signals through complex signal processing algorithms for more accurate detection of human physiological parameters. The research of this paper will be of great value to the research and application of electronic stethoscopes.

What the future ocean has in common with an asthma attack

Ocean acidification and ocean deoxygenation are consequences of anthropogenic CO2 emissions that remain largely unknown to the general public. Mostly, because lay audiences are not familiar with the complex chain of physical and chemical processes that drive these phenomena. This demands that communicators find clear, simple and psychologically effective language to frame ocean health issues in familiar terms. From antiquity to the Renaissance, and independently across multiple cultures, premodern thinkers have conceptualized the Earth in terms of the human body. This is not surprising given that metaphor lies at the core of human understanding. Building on this premodern tradition, I found a system of mathematical equations that calculates the chemical composition of the human body or the ocean, when forced by human physiological or oceanographic parameters, respectively. Based on this result, I build an extended analogy that introduces the basic functioning of the oceanic CO2 and O2 cycles to the general public. The analogy incorporates ocean acidification and deoxygenation, that have parallels in the acidification and deoxygenation of the human body caused by an asthma attack, providing ocean health communicators with a tool that promotes interest in, and explains the origin of, declining ocean heath. Extending the analogy to the continental domain allows to see the Earth as a superorganism, a perspective that may help promote an environmentally healthier relationship between humanity and the Earth.

A feasibility study on using fNIRS brain signals to recognize personal thermal sensation and thermal comfort conditions.

Many studies have shown some relationships between thermal perception (including thermal sensation and thermal comfort) and human physiological parameters, such as brain signals. However, further research is still needed on how these parameters can help recognize the state of a human's personal thermal perception. This study aims to investigate the potential of using fNIRS brain signals to evaluate and predict personal thermal perception and cognitive performance in a steady-state temperature. The present study investigated changes in the fNIRS signal during ambient temperature manipulation. Thirty healthy young individuals were selected as the subjects, and they were exposed to two steady temperatures of 28.8 and 19 °C. After acclimatizing to either temperature, the oxy/deoxy-hemoglobin changes of the prefrontal cortex (PFC) were measured in both rest and cognitive task states using 16-channel fNIRS. Results showed that exposure to different temperatures was significantly associated with the brain signals recorded during the task state. Many significant correlations were discovered between fNIRS signals and thermal perceptionindices. Furthermore, subjects' performance changes led to changes in the fNIRS signals. Logistic regression showed that fNIRS can determine whether a person is thermally comfortable or uncomfortable.

Development of an Energy Harvesting System for the Conversion of Mechanical Energy of Human Movement into Electrical Energy and Its Integration into High Performance Wearable Clothing

In many smart textile development studies, sensors and electro-conductive yarns have been widely investigated and used as essential components, especially in the fields of medicine, sport, work wear, and special applications. Wearable sensors provide a means to monitor the wearer’s health through physiological measurements in a natural setting or are used to detect potential hazards and alert users and/or caretakers. The aim of the research is to develop a prototype of wearable electronics that consists of high-performance clothing with an integrated energy harvesting system for converting the mechanical energy of human movements into electrical energy. Within the framework of the research, a system for determining human physiological and/or environmental parameters and transmitting data was developed and integrated into clothing modified with sol–gel technology for indoor and outdoor use. Although the created flat inductive elements of the energy harvesting system retain their performance during the hydrothermal treatment process, at the same time, the other elements of the smart clothing system (especially electro-conductive yarns) rapidly lose their electrical conductivity. The modified knitwear provided a longer time between washing cycles to protect the embedded wearable electronics, and the impact of surface modification with sol–gel on wearing comfort was evaluated.

Nanomaterials‐Based Bioinspired Next Generation Wearable Sensors: A State‐of‐the‐Art Review

AbstractWith a constantly growing percentage of the population having access to high‐quality healthcare facilities, preventable pathogenic illnesses have been nearly eradicated in the developed parts of the world, which has led to a significant rise in the average human life expectancy over the last few decades. In such a highly developed world, age‐related illnesses will lead to an immense burden on healthcare providers. Remote health monitoring enabled by wearable sensors will play a significant role in the growth and evolution of Health 3.0 by providing intimate and valuable information to healthcare providers regarding the progression of disease in patients with critical life‐altering conditions. Especially, in the case of people suffering from neurodegenerative disorders, inexpensive and user‐friendly wearable sensors can enable physiotherapists monitor real‐time physiological parameters to design patient‐specific treatment plans. This review provides a comprehensive overview of the recent advances and emerging trends at the convergence of biomimicry and nanomaterial sensors, with a specific focus on wearable skin‐inspired mechanical sensors for applications in IoT‐enabled human physiological parameters monitoring. Skin‐inspired wearable mechanical sensors with relevance to the most common types of sensing mechanisms including piezoresistive, piezocapacitive, and triboelectric sensing are discussed along with their current challenges and possible future opportunities.