Normal Human Activities Research Articles

Dynamic and sustainable supramolecular biolubrication coatings through nanoarchitectonics with dynamic BN bonding.

Biological lubricating materials play a crucial role in normal human activities due to their extremely low coefficients of friction (COFs). However, synthetic friction materials typically exhibit higher friction coefficients and wear rates compared to natural lubricating materials. To address this issue, we propose a novel lubrication strategy: reducing the friction coefficient of synthetic lubricating materials through supramolecular dynamic exchange. The incorporation of B-N supramolecular dynamic bonds enhances the stability of the polymer network structure, resulting in superior mechanical properties and resilience. The dynamic behavior of B-N bonds during friction reduces the frictional resistance of mechanical interlocking networks in motion, thereby significantly improving the frictional performance of supramolecular coatings. We anticipate that elucidating the dynamic structure-performance relationship in supramolecular coatings will advance the development of supramolecular lubricating materials and inspire innovative approaches to constructing new lubricating materials.

Generalized and Improved Human Activity Recognition for Real-Time Wellness Monitoring

Human activity categorization using smartphone data can be useful for physicians in real-time data monitoring in sports or lifestyle monitoring. The goal of this research is to develop a methodology that can identify strong machine-learning classifiers applied to various human activity datasets. The first step is pre-processing the data, followed by feature extraction, selection, and classification. Relying on a single dataset does not yield high confidence in the findings. Instead, examining multiple datasets is crucial for a comprehensive understanding, as it avoids the pitfalls of basing conclusions on one dataset alone. Multiple datasets and classifiers are applied in different experiments to achieve improved and generalized human activity recognition performance. Experimental results of the support vector machine (SVM) with its generalized performance of 99% encourage us to use the trained SVM-based model to monitor normal human activities inside the home, in the park, in the gym, etc. enhancing wellness monitoring.

Structural simulation of Ti–Ha–CaCO3 biocomposites using finite element analysis (FEA) for biomechanical stability of hip implant

AbstractThe structural integrity of new biocomposite implants is critical in ensuring the success of biomedical implants under physiological loading conditions. Studying the stress distribution, deformation, and potential failure modes under different loading scenarios is complex, expensive, and time-consuming, as it involves repeated surgery on clinical assessment. The present study aims to investigate the biomechanical stability of hip implants made of a Ti–Ha–CaCO3 biocomposite using finite element analysis. The Ti–Ha–CaCO3 biocomposite was modeled and simulated using Solidworks. The model mesh was generated to represent the implant’s geometry accurately, and normal human activities (standing and jumping) were considered the boundary conditions with the lower part of the femur fixed. The model was subjected to static loading following ISO 7206-4 with an equivalent load of 2300 N according to ASTM F2996-13 standard. The Ti–Ha–CaCO3 biocomposite demonstrated outstanding biomechanical stability under loading circumstances. The maximum von Mises stress (354.7 MPa) observed with the GSB-femur model in the implant was below the yield strength of the titanium implant, indicating that the implant can withstand applied loads without experiencing permanent deformation. However, 74.11 MPa was obtained as acceptable von Mises stress using GSB intramedullary rods for bone fixation. The most stable implant is DSB, with the lowest displacement value of 2.68 mm. Low equivalent strains were achieved for all the implants, as the highest strain (0.012) was obtained in the simulation of the stem DSB-femur model. Low-stress signals (SS) were obtained for the implant-femur models, indicating they are suitable for replacing bone for that loading. The DSB (7.19) is the most suitable among the studied stem-femur models, and GSB (0.87) remains the suitable intramedullary rod-femur model with the lowest SS.

Measuring Chinese mobility behaviour during COVID-19 using geotagged social media data

COVID-19 caused widespread disruption to normal lives and human activities. In China, the mobility behaviour response to the COVID-19 pandemic at the intra-city and population group levels is largely unknown, mainly due to a lack of individual-level publicly available mobility data. Using 210 million geotagged posts from 10 million social media users, the study quantified the changes in stay-at-home and outings across amenities and groups in China during the pandemic. The users were compared to national census data to examine their representativeness. To validate the results externally, the geotagged data was performed post-stratified correction and further comparison with commonly used data sources. The findings reveal that (i) there was between 16.8% and 57.7% decrease in visits to places of work, retail and recreation sites, parks, transit stations, grocery stores, and pharmacies within one month of the outbreak; (ii) those who are young, have a bachelor’s degree or higher, and are unmarried experienced a greater decline in outings; (iii) people preferred to visit nearby locations, resulting in a 4.3% increase in visits to retail and recreational sites within a 3-kilometer radius of their homes. The data and findings could gain insight into the asymmetric impact of the pandemic on public infrastructure use and socio-demographic groups, helping design targeted policies to promote outdoor activities, stimulate economic recovery, and alleviate social inequality in vulnerable groups.

Effects of oil pollution on birds

As a non-renewable energy source, oil has an unshakable position in the development of human beings. Still, no one has noticed that the oil buried deep in the ground is also inextricably linked to the birds flying in the air. This article focuses on how oil, except diet, has been linked to bird deaths. The first research direction is to study the feather structure and function of birds. It is concluded that oil will damage the functionality of feathers and make the feathers of birds unable to function. The second research direction is about the inversely proportional relationship between the flight speed of birds and oil and the directly proportional relationship between energy consumption and oil. It is concluded that oil will affect the speed and energy consumption of birds and make birds more vulnerable to predation by natural enemies. The third research direction is the analysis of the damage degree of oil to birds' eggs and young. Based on these studies, it is possible to find out feasible methods that can effectively reduce the harm of oil extraction operations to birds without affecting normal human activities. Let birds have a way to reproduce healthily and safely without hindering human development.

An Effective Model for Predicting Phage-Host Interactions Via Graph Embedding Representation Learning With Multi-Head Attention Mechanism

In the treatment of bacterial infectious diseases, overuse of antibiotics may lead to not only bacterial resistance to antibiotics but also dysbiosis of beneficial bacteria which are essential for maintaining normal human life activities. Instead, phage therapy, which invades and lyses specific pathogenic bacteria without affecting beneficial bacteria, becomes more and more popular to treat bacterial infectious diseases. For the effective phage therapy, it requires to accurately predict potential phage-host interactions from heterogeneous information network consisting of bacteria and phages. Although many models have been proposed for predicting phage-host interactions, most methods fail to consider fully the sparsity and unconnectedness of phage-host heterogeneous information network, deriving the undesirable performance on phage-host interactions prediction. To address the challenge, we propose an effective model called GERMAN-PHI for predicting Phage-Host Interactions via Graph Embedding Representation learning with Multi-head Attention mechaNism. In GERMAN-PHI, the multi-head attention mechanism is utilized to learn representations of phages and hosts from multiple perspectives of phage-host associations, addressing the sparsity and unconnectedness in phage-host heterogeneous information network. More specifically, a module of GAT with talking-heads is employed to learn representations of phages and bacteria, on which neural induction matrix completion is conducted to reconstruct the phage-host association matrix. Results of comprehensive experiments demonstrate that GERMAN-PHI performs better than the state-of-the-art methods on phage-host interactions prediction. In addition, results of case study for two high-risk human pathogens show that GERMAN-PHI can predict validated phages with high accuracy, and some potential or new associated phages are provided as well.

Development of the recipe and technology of semi-finished mock cutlets of functional purpose

Increase in animal protein resources is of great importance on a global scale. Proteins of animal origin provide the human body with basic macroand micronutrients and support normal human life and activities. Poultry meat occupies a significant proportion in the state program of production and sale of animal proteins. From year to year, the growth and consumption of poultry meat (30...35 %) is constantly increasing. Mechanically deboned poultry meat is characterized by less technological potential and is in need of increase its functional and technological properties in the formation of food systems with specified properties.The article shows the possibility of expanding the assortment of meat chopped semi-finished products (cutlets) of functional purpose using a compositional mixture in a recipe that helps to increase biological and nutritional value.The purpose of the research is to develop the recipe and technology of mechanically deboned poultry meat semi-finished products (cutlets) of functional purpose using non-traditional raw materials, namely compositional mixture (CM).The qualitative and quantitative composition of the compositional mixture for cutlets of functional purpose from mechanically deboned poultry meat has been substantiated and selected.The influence of the dosage of the compositional mixture consisting of a solid Adygh cheese«Mate» (powder), oatmeal and garlic powder, on the consumer properties of mechanically deboned poultry meat has been investigated. The quality indicators (organoleptic and physico-chemical ones) cutlets of functional purposes have been investigated.The recipe and technology of functional cutlets has been developed where wheat bread is replaced completely (100%) with a compositional mixture and coating with oatmeal flour. This technology has shown the best quality indicators.

Coupling of multi-hydrochemical and statistical methods for identifying apparent background levels of major components and anthropogenic anomalous activities in shallow groundwater of the Liujiang Basin, China.

Natural background levels (NBLs) is a prerequisite for distinguishing anthropogenic groundwater pollution and judging the evolution of groundwater quality. However, due to regional differences of hydrogeochemitry and water-rock interaction, coupled with long-term anthropogenic activities, it is no longer accurate to assess NBLs with only statistical methods or without considering human impact. Herein, multi-hydrochemical and statistical methods were examined to identify apparent background levels and anthropogenic anomalous activities of shallow groundwater by selecting Liujiang Basin as a study area. The results showed that the differences in hydrochemical characteristics among each hydrogeological unit (HU) fully illustrated the necessity of rationally dividing HU for background value identification. The application of the concept of apparent background levels (ABLs), that is, incorporating normal human activities into the background levels, efficiently solved the problem of being unable to obtain pristine NBLs due to long-term human activities. The coupling of Hydrochemistry and Grubbs' test (Hydro-Grubbs) was confirmed as the optimal method in identifying and eliminating anthropogenic groundwater anomalies, performing sufficiently superiority when compared with purely statistical methods. It is mainly because the Hydro-Grubbs method not only considers the discreteness of the data itself, but also considers the internal connection and evolution process of the hydrochemical compositions. For the eliminated abnormal points, 91.0-93.6% of which have been effectively explained by pollution percentage index and the impact of coal mining, industrial activities, residents, agricultural activities, and septic tanks leakage, proving the rationality and reliability of Hydro-Grubbs method and ABLs evaluation result. This finding will assist in accurately identifying anthropogenic pollution on a regional scale and guiding future efforts to protect groundwater resources.

Human Health Risks and Air Quality Changes Following Restrictions for the Control of the COVID-19 Pandemic in Thailand.

The coronavirus (COVID-19) pandemic first impacted Thailand in early 2020. The government imposed lockdown measures from April to May 2020 to control the spread of infection. Daily lifestyles then morphed into a so-called new normal in which activities were conducted at home and people avoided congregation in order to prevent the spread of an infectious disease. This study evaluated the long-term air quality improvement which resulted from the restrictions enforced on normal human activities in Thailand. The air quality index (AQI) of six criteria pollutants and health risk assessments were evaluated in four areas, including metropolitan, suburban, industrial, and tourism areas in Thailand. The results showed that, after the restriction measures, the overall AQI improved by 30%. The subindex of each pollutant (sub-AQI) of most pollutants significantly improved (by 30%) in metropolitan areas after human activities changed due to the implementation of lockdown measures. With regard to industrial and tourism areas, only the sub-AQI of traffic-related pollutants decreased (34%) while the sub-AQIs of other pollutants before and after lockdown were similar. However, the changes in human activities were not clearly related to air quality improvement in the suburban area. The overall hazard index (HI) after lockdown decreased by 23% because of the reduction of traffic-related pollutants. However, the HI value remained above the recommended limits for the health of the adult residents in all areas. Therefore, strict regulations to control other pollutant sources, such as industry and open burning, will also be necessary for air quality improvement in Thailand.

Human Activity Recognition With Smartphone

Abstract: Human Activity Recognition (HAR) is designed to classify activities performed by human beings using responsive sensors inbuilt in smartphones that are affected from their movements. HAR is one of the most important technology that has wide applications in medical research, human survey system and security system, fitness etc. In this project we are predicting what a person is doing based on their trace movement using smartphone sensor. Movements include normal indoor human physical activities such as standing, sitting, walking, running, walking upstairs, walking downstairs. Smartphones has various built-in sensors like accelerometer and gyroscope. This system captures the raw sensor data from mobile sensors as input, process it and predicts a human activity using machine learning techniques. We analyze the performance of two classification algorithms that is Decision Tree (DT), Convolutional Neural Network (CNN). In this project, we build a robust activity detection system based on smartphones. Experiment results show that the classification rate of algorithms reaches 98%. In this project we propose a platform for identifying real-time human activity. Keywords: Machine Learning, Deep Learning, Activity Recognition, Smartphone, Accelerometer, Gyroscope, CNN, DT.

Layanan perpustakaan Skill Online dalam menghadapi pandemi Covid-19

The existence of the Covid-19 pandemic at the beginning of 2020 had an impact on normal human activities, including library activities that have been carried out so far. Activities to stop library services manually to avoid direct contact with users as an action to prevent and transmit Covid-19. The purpose of this service is to find out the concept of digital services that can be done and provide an analysis of the application of information communication for several online services. The research method used is community service activities, namely counseling, implementation and innovation services that are carried out online. The online skill library is a modern library that already uses an automated system in its operations and has a collection of library materials mostly in digital format that is stored in a computerized architecture and can be accessed via mobile phones. The result of this service is the need for online library services through the application of the online skill library concept with four main discussions, namely photoshop, kinemaster, mechanics and culinary. Several online skill libraries on the front pages of Facebook and Instagram provide information related to the latest information from tips on becoming a culinary entrepreneur from scratch, health literacy services in preventing transmission, and a database of research results related to Covid-19.

The Way of Severe Nursing of Respiratory System Failure.

Respiratory failure is the most common clinical symptom, seriously endangering people's health, which is mainly caused by a series of reasons, leading to serious respiratory dysfunction and severe pulmonary respiratory disorders, damaging the pulmonary airway function, and causing disability to maintain normal human gas exchange activities. At present, the main treatment of respiratory failure is to use the ventilator to help patients exchange gas and keep their breathing unobstructed. The nursing method is also around the artificial airway mechanical ventilation. The nursing of patients with respiratory failure is mainly respiratory nursing and psychological nursing. In this paper, the main research is to explore the way of severe nursing of respiratory failure. Before the nursing of respiratory failure, we should carry out nursing detection of the ventilator and test its performance, tightness, pipeline safety, and airway patency. Then carrying on the respiratory failure mechanical ventilation nursing and clarifying its mechanical ventilation nursing process is the main work of intensive care, at the same time, giving consideration to the psychological nursing of respiratory failure and implementing comprehensive nursing. In this paper, 50 patients were selected and divided into group A and group B; group A was given comprehensive nursing, and group B was given general nursing. The experimental results show that a series of situations in group A are more optimistic than those in group B. There was no doubt that the PH value of the two groups changed significantly 6 months after discharge. The pO2 value of group A was higher than that before discharge, while the pCO2 value of group B was unstable and increased. The pO2 value of group A was 55.52 before discharge and 62.36 six months after discharge. The pCO2 value of group A was 54.31 before discharge and 50.61 six months after discharge. The pCO2 value of group B was 55.23 before discharge and 57.34 six months after discharge.

HVD-LSTM based recognition of epileptic seizures and normal human activity.

In this paper, we detect the occurrence of epileptic seizures in patients as well as activities namely stand, walk, and exercise in healthy persons, leveraging EEG (electroencephalogram) signals. Using Hilbert vibration decomposition (HVD) on non-linear and non-stationary EEG signal, we obtain multiple monocomponents varying in terms of amplitude and frequency. After decomposition, we extract features from the monocomponent matrix of the EEG signals. The instantaneous amplitude of the HVD monocomponents varies because of the motion artifacts present in EEG signals. Hence, the acquired statistical features from the instantaneous amplitude help in identifying the epileptic seizures and the normal human activities. The features selected by correlation-based Q-score are classified using an LSTM (Long Short Term Memory) based deep learning model in which the feature-based weight update maximizes the classification accuracy. For epilepsy diagnosis using the Bonn dataset and activity recognition leveraging our Sensor Networks Research Lab (SNRL) data, we achieve testing classification accuracies of 96.00% and 83.30% respectively through our proposed method.

Respiratory droplet resuspension near surfaces: Modeling and analysis

Knowing the environmental spreading pathway of COVID-19 is crucial for improving safety practices, particularly for health care workers who are more susceptible to exposure. This paper focuses on the possible secondary transmission due to resuspension of virus-laden droplets from common surfaces, which several studies have shown to be possible under external disturbances. Such disturbances could be body motion during walking, running, clothes removal, or airflow in the environment. In this paper, a three-dimensional two-phase model is utilized to study respiratory droplet resuspension dynamics on various surfaces due to sudden agitation. The velocity range and variation during walking, surgical glove removal, and dropping an object are studied experimentally. A parametric study is performed to characterize the effects of droplet size and surface wettability on the minimum initial droplet velocity required for detachment from surfaces. The results are reported as average droplet velocity during the detachment process, total detachment time, and detached droplet volume. The obtained results indicate that respiratory droplets larger than 200 μm can detach from typical surfaces due to normal daily activities. Droplets are partially separated from hydrophilic surfaces with contact angle ≤90°, while the entire droplet is detached from hydrophobic surfaces with contact angle >90°. Furthermore, the minimum initial droplet velocity to induce the resuspension depends on the droplet size. Droplet velocity immediately after detachment is a function of droplet size, initial droplet velocity, and surface wettability. Bigger droplets have larger detached volume percentage as well as higher velocity after detachment compared to smaller droplets. Finally, a higher initial velocity is needed to separate droplets from hydrophilic surfaces as compared to hydrophobic surfaces. In accordance with the results, the droplet minimum initial velocity to cause detachment is 2 m s−1, while our experiments show that surface velocity can reach up to 3 m s−1 during normal human activities. We also develop an analytical model to predict the required kinetic energy to detach droplets from different surfaces, which is in good agreement with numerical results. The mechanism of droplet detachment is dictated by a competition between droplet kinetic energy induced by surface motion and surface energy due to droplet–surface interaction as well as droplet–vapor and surface–vapor interactions. We believe that the results of this fundamental study can potentially be used to suggest proper surface wettability and safe motion that reduce respiratory droplet resuspension from various surfaces.

BIOLOGICAL DISASTERS AND SOME PREVENTION METHOD SAMPLES IN TURKEY

Disaster is a natural, technological and human-based phenomenon that requires the coordination of many institutions and organisations and causes physical, economic and social losses for human rights, interrupts normal life and human activities. Biological disasters are situations caused by organic origin or biological carriers. These biological carriers can be disease-bearing microorganisms, toxins, and bioactive products. When this situations occur, many deaths can occur, as well as injuries, illness or health problems. Moreover, these biological factors can turn into agricultural production losses, pasture-grazing diseases, social and economic breakdowns or even an environmental disaster depending on the type. The emergence of all kinds of negative effects of pesticides, the abundance of natural enemies that can be exploited in nature and the increase of environmental awareness should be the reasons for focusing on an environmentally friendly, sustainable and cheap control method such as Biological Control. Entomopathogens used in biological control against insects include bacteria, fungi, viruses, protozoa and nematodes. In terms of biological disasters, insect infestation and epidemic diseases stand out among this group. The most important biological disasters are disasters caused by microorganisms, and COVID-19, which the whole world is trying to deal with today, is a global biological disaster. The epidemic started in Wuhan / China in late 2019 and is now spreading all over the world.

The application of wearable smart sensors for monitoring the vital signs of patients in epidemics: a systematic literature review.

Wearable smart sensors are emerging technology for daily monitoring of vital signs with the reducing discomfort and interference with normal human activities. The main objective of this study was to review the applied wearable smart sensors for disease control and vital signs monitoring in epidemics outbreaks. A comprehensive search was conducted in Web of Science, Scopus, IEEE Library, PubMed and Google Scholar databases to identify relevant studies published until June 2, 2020. Main extracted specifications for each paper are publication details, type of sensor, disease, type of monitored vital sign, function and usage. Of 277 articles, 11 studies were eligible for criteria. 36% of papers were published in 2020. Articles were published in 10 different journals and only in the Journal of Medical Systems more than one article was published. Most sensors were used to monitor body temperature, heart rate and blood pressure. Wearable devices (like a helmet, watch, or cuff) and body area network sensors were popular types which can be used monitoring vital signs for epidemic trending. 65% of total papers (n = 6) were conducted by the USA, Malaysia and India. Applying appropriate technological solutions could improve control and management of epidemic disease as well as the application of sensors for continuous monitoring of vital signs. However, further studies are needed to investigate the real effects of these sensors and their effectiveness.

Mechanism of traditional Chinese medicine balancing Yin-Yang by targeting ERα/ERβ and its application in treatment of menopausal syndrome

The coordination and unification of Yin and Yang are the basis of normal human life activities. Along with the age growth and aging of the body, women will suffer from menopausal syndrome during menopause. In addition to the significant changes in the genital system, there are also pathological manifestations in estrogen target points including bone, nerve and cardiovascular systems, due to the imbalance of Yin and Yang. Besides the insufficiency of estrogen, the main cause of menopausal syndrome is the changes in the response of target organs to estrogen. In other words, the biological effects mediated by estrogen receptor(ER) alpha and beta subtypes in target cells are often different or even opposite; the changes of expression level and ratio of ERα and ERβ are also important causes for the abnormal estrogenic effects in target organs and the imbalance of Yin and Yang of the body. Therefore, on one hand, the therapeutic mechanism of drugs is ER-mediated estrogenic effect. On the other hand, the drugs have a regulatory effect on ER subtype expression in target cells and Yin-Yang state in target organs and even organisms, so as to cause further changes in the response of target cells to estrogen or estrogenic components, and exert its therapeutic effects. This paper reviews the pharmacological mechanism of gynecological traditional Chinese medicine in harmonizing Yin and Yang in estrogen-positive target cells and the clinical efficacy in the following aspects, including estrogen and its mechanism, the estrogenic effect of ER in traditional Chinese medicine and the mechanism of ER subtype in balancing Yin and Yang and mediating and regulating the main target tissues in menopausal syndrome treatment.

Evaluation of decontamination methods for commercial and alternative respirator and mask materials – view from filtration aspect

This study aims to evaluate the filtration performance of three commercially available (3M 8210 respirator, Halyard 48207 surgical mask, and 3M 1820 procedure mask) and two alternative face mask and respirator materials (Halyard H600 sterilization wrap and Cummins EX101) after selected decontamination treatments, including isopropanol (IPA) treatments (soaking or spraying), ultraviolet germicidal irradiation (UVGI), and heat treatments (dry heat at 77 °C or steam heat). Both IPA soaking and spraying removed most electrostatic charges on all four electret materials (three commercial and one alternative), causing significant deterioration of filtration efficiency to unacceptable level. The other non-electret alternative material sustained its N95-grade performance after both IPA soaking and spraying treatments, demonstrating the possible application of IPA disinfection for non-electret alternative respirator/mask materials. UVGI preserved the filtration of all three commercially available respirator/mask materials after up to 10 treatments, suggesting it can be a possible decontamination method for hospital and clinic use without compromising respirator/mask performance. The considerations of the practical implementation of this method was discussed. Between the two heat treatment methods tested, dry heat showed better compatibility with electret material by sustaining both filtration efficiency and fit (tested on commercial respirator only), although adding moisture was reported in favor of virus inactivation. Heat treatment is easily accessible method for general publics to implement at home, while it is recommended to maintain the moisture level below saturation. Comparing to size-integrated method, the size-resolved fractional efficiency measurement technique, although more time consuming, proved to be a better method for evaluating respirator/mask filtration performance after decontaminations by providing more sensitive detection of performance degradation and the capability of distinguishing charge loss to other mechanisms causing efficiency deterioration. Detailed descriptions are provided in methodology part to emphasize the cares needed for an appropriate efficiency evaluation. The limited results in this study on worn masks made of alternative sterilization wrap indicated possible performance degradation of electret material caused by normal human wearing activities, suggesting the need of assessing respirator/mask decontamination strategy by testing practically worn-and-decontaminated/reused samples instead of unworn only-decontaminated counterparts.

Concept generation and integration in surgical pathology

This presentation emphasizes the importance of concept generation in the undergraduate medical education. It is primarily based on molecular genetic advances. It is implicated in the understanding of various normal human biomolecular activities based on the intrinsic molecular integration and unification of diverse biomolecular activities to provide best possible service for the survival of human being. Disruption of these molecular integration pathways results in various disease manifestations. The concept generation should form the basic foundation in surgical pathology teaching in the undergraduate medical education without which it remains a disjointed discourse.We have highlighted the process of concept generation and presented few examples and we aim to stimulate medical graduates to generate their own concepts based on their own observations. They should be able to integrate various associations with future molecular advances to enhance their understanding and improved clinical outcome as most treatment in near future will be based on molecular basis. Keywords: Concept generation, Integration, Concept mapping, Connections, Medical education, Narrative in medicine.

A wearable device for collecting multi-signal parameters of newborn

In recent years, wearable health monitoring equipment has developed rapidly, but most functions are relatively single and can only monitor certain physiological parameters of the human body. This paper designed a wearable multi-physiological parameter monitoring system, which can continuously monitor multiple physiological parameters of newborns for a long time without affecting the normal human activities. The hardware circuit uses MSP430F1611 single-chip microcomputer as the central processing unit. The single-chip computer program completes the calculation of multiple parameters and sends them to the Bluetooth module through the serial port. The Bluetooth module receives the data and transmits it through the module antenna. After testing, each function module works normally. The results of the heart rate measurement experiments show that more than 96% of the heart rate data is within ± 3 BPM (Beat Per Minute). The experimental results of arterial oxygen saturation measurement show that the error of arterial oxygen saturation is within ± 2%. The results of arterial blood pressure measurement experiments show that the error between systolic and diastolic blood pressure meets the standard.