Heart Rate Readings Research Articles

The Use of Heart Rate Measures to Evaluate Stress Levels among Air Traffic Controllers

This paper looks at the possibility of using a heart rate monitor to evaluate stress levels among Air Traffic Controllers (ATCOs). Air Traffic Control (ATC) service requires constant good planning, situation awareness, and always making sound decisions. A study was conducted on two ATCOs for three complete work cycles: the morning shift from 8 a.m. to 4 p.m., the afternoon shift from 4 p.m. to 12 a.m., and the night shift from 12 a.m. to 8 a.m. Both participants have different roles, with Subject A being a planner controller while Subject B is a radar controller. The study used the NASA Task Load Index (NASA-TLX) survey to collect the subjective workload rating and a heart rate monitor armband to measure the heart rate reading of an ATCO and then compare it with the number of aircraft within the controlled area. Two hypotheses were investigated: the first one is the relationship between the number of traffic and heart rate readings, and the second hypothesis is the relationship between the elapsed working time and heart rate reading. The Spearman correlation test has been used to determine these relationships. Based on the results, a p-value of less than 0.05 and a positive correlation indicates a significant relationship between the number of aircraft and heart rate readings for both subjects. Elapsed time and heart rate measurement, on the other hand, do not significantly correlate with a p-value greater than 0.05 and a negative correlation was produced for both subjects. The unweighted NASA-TLX workload measure confirmed the findings for Subject A but not for Subject B. This might be due to the different roles carried out by both subjects during the experiment. This shows that different work tasks resulted in different workload-induced factors. The results show a promising outcome of using a heart rate monitor to evaluate stress levels among ATCOs. However, more subjects were needed to enable the use of this concept for future purposes of measuring ATCO stress levels to manage workload.

Efficacy of Wearable Single-Lead ECG Monitoring during Exercise Stress Testing: A Comparative Study

Background and Objectives: Few comparative studies have evaluated wearable single-lead electrocardiogram (ECG) devices and standard multi-lead ECG devices during exercise testing. This study aimed to validate the accuracy of a wearable single-lead ECG monitor for recording heart rate (HR) metrics during graded exercise tests (GXTs). Methods: A cohort of 50 patients at a tertiary hospital underwent GXT while simultaneously being equipped with wearable single- and conventional multi-lead ECGs. The concordance between these modalities was quantified using the intraclass correlation coefficient and Bland–Altman plot analysis. Results: The minimum and average HR readings between the devices were generally consistent. Parameters such as ventricular ectopic beats and supraventricular ectopic beats showed strong agreement. However, the agreement for the Total QRS and Maximum RR was not sufficient. HR measurements across different stages of the exercise test showed sufficient agreement. Although not statistically significant, the standard multi-lead ECG devices exhibited higher noise levels compared to the wearable single-lead ECG devices. Conclusions: Wearable single-lead ECG devices can reliably monitor HR and detect abnormal beats across a spectrum of exercise intensities, offering a viable alternative to traditional multi-lead systems.

To Validate Use of Transmittance Sensor of Peripheral Pulse Oximeter for Forehead Pulse Oximetry in Newborns

Introduction Peripheral pulse oximeters with continuous monitoring of heart rate and saturation have revolutionized neonatal care. Motion artifacts, hypothermia, and poor perfusion are some of the barriers for reliable reading in the transmittance type of peripheral pulse oximeters. This study was planned to assess the effectiveness of transmittance sensors applied over the forehead for monitoring the heart rate and saturation. Material and Methods An observation study was conducted over a period of 1 month. Two pulse oximeters (Masimo RAD97) were applied simultaneously, one over the periphery (right hand/wrist) and the other over the forehead using an innovative headband. A total of 540 readings of heart rate and saturation (SpO2) from each site were recorded. A difference of more than 5 beats/minute in heart rate and 2% saturation were considered clinically significant. Results Forty-five neonates with mean gestational age of 35.3 ± 3.2 weeks and birth weight of 2109 ± 683 grams were enrolled. Forehead pulse oximeter could pick up the heart rate and SpO2 readings in all the babies. A statistically significant difference of 3.8 beats/minute in heart rate and 2.5% in SpO2 was noted ( p-value < 0.0001). The difference in heart rate was not clinically significant. Conclusion We propose that the transmittance type peripheral pulse oximeter sensors can be used over the forehead. It has the potential to avoid erroneous readings due to motion artifacts, hypothermia, or shock. Saturation nomograms for the forehead pulse oximetry need to be established before it can be used to monitor and manage the neonates for the same.

P076 FACTORS INFLUENCING POST-COVID HOME BP AND HR FLUCTUATION WITHIN THE URBAN INDIAN DIABETIC POPULATION

Objective: The impact of COVID-19 on cardiovascular health among adult diabetics remains underexplored, particularly concerning home blood pressure (BP) and heart rate (HR) variability. This study aims to elucidate the factors influencing post-COVID home BP and HR fluctuation within the urban Indian diabetic population. Design and Methods: A cross-sectional study was conducted, involving 1000 adult diabetic patients aged 30 to 80 years with prior COVID-19 infection. Home BP and HR readings were recorded twice daily over seven days, generating 28 measurements. Variability in BP and HR was determined using standard deviation calculations between morning and evening readings, as well as between consecutive measurements. Results: Older age (OR: 1.56, 95% CI: 1.23-1.98), cardiovascular comorbidities (OR: 2.09, 95% CI: 1.67-2.62), diabetes (OR: 1.84, 95% CI: 1.43-2.36), and elevated home BP (OR: 2.35, 95% CI: 1.87-2.95) emerged as independent predictors of increased morning-to-evening home BP variability. Similarly, older age (OR: 1.72, 95% CI: 1.34-2.21) and elevated home BP (OR: 2.14, 95% CI: 1.67-2.75) were determinants of heightened day-to-day BP variability, while a combination of older age (OR: 1.98, 95% CI: 1.52-2.58), female sex (OR: 1.43, 95% CI: 1.11-1.84), cardiovascular disease (OR: 1.89, 95% CI: 1.47-2.44), and elevated home BP (OR: 2.56, 95% CI: 1.98-3.31) predicted greater variability between consecutive readings. Conversely, younger age (OR: 0.76, 95% CI: 0.59-0.98) and elevated home HR (OR: 1.92, 95% CI: 1.51-2.44) were associated with increased morning-versus-evening HR variability. Additionally, younger age (OR: 0.67, 95% CI: 0.51-0.88), female sex (OR: 1.34, 95% CI: 1.04-1.73), and elevated home HR (OR: 1.78, 95% CI: 1.39-2.29) were predictive of greater variability between consecutive HR measurements. Conclusion: Understanding the determinants of home BP and HR variability post-COVID infection is crucial for prognostication and clinical management. Clinicians should prioritize counseling incorporating regular home blood pressure measurements, diabetes management, and cardiovascular disease prevention, particularly for high-risk diabetic patients.

Validity of Current Smartwatches for Triathlon Training: How Accurate Are Heart Rate, Distance, and Swimming Readings?

Smartwatches are one of the most relevant fitness trends of the past two decades, and they collect increasing amounts of health and movement data. The accuracy of these data may be questionable and requires further investigation. Therefore, the aim of the present study is to validate smartwatches for use in triathlon training. Ten different smartwatches were tested for accuracy in measuring heart rates, distances (via global navigation satellite systems, GNSSs), swim stroke rates and the number of swim laps in a 50 m Olympic-size pool. The optical heart rate measurement function of each smartwatch was compared to that of a chest strap. Thirty participants (15 females, 15 males) ran five 3 min intervals on a motorised treadmill to evaluate the accuracy of the heart rate measurements. Moreover, for each smartwatch, running and cycling distance tracking was tested over six runs of 4000 m on a 400 m tartan stadium track, six hilly outdoor runs over 3.4 km, and four repetitions of a 36.8 km road bike course, respectively. Three swimming protocols ranging from 200 m to 400 m were performed in triplicate in a 50 m Olympic-size pool, evaluating the tracked distance and the detected number of strokes. The mean absolute percentage errors (MAPEs) for the average heart rate measurements varied between 3.1% and 8.3%, with the coefficient of determination ranging from 0.22 to 0.79. MAPE results ranged from 0.8% to 12.1% for the 4000 m run on the 400 m track, from 0.2% to 7.5% for the 3.4 km outdoor run, and from 0.0% to 4.2% for the 36.8 km bike ride. For the swimming tests, in contrast, the deviations from the true distance varied greatly, starting at a 0.0% MAPE for the 400 m freestyle and reaching 91.7% for the 200 m medley with style changes every 25 m. In summary, for some of the smartwatches, the measurement results deviated substantially from the true values. Measurements taken while road cycling over longer distances with only a few curves were in relative terms more accurate than those taken during outdoor runs and even more accurate than those taken on the 400 m track. In the swimming exercises, the accuracy of the measured distances was severely deteriorated by the medley changes among the majority of the smartwatches. Altogether, the results of this study should help in assessing the accuracy and thus the suitability of smartwatches for general triathlon training.

The Effects of Caffeine on Heart Rate and Heart Rate Variability at Rest and During Submaximal Cycling Exercise

ABSTRACT The aim of this study was to investigate the effects of caffeine on heart rate and heart rate variability (HRV) at rest and during submaximal exercise. Using a balanced, double-blind, randomized, crossover design, 16 male cyclists (age: 37 ± 9 years; V ˙ O2max: 4.44 ± 0.67 L·min−1) completed three trials in an air-conditioned laboratory. In Trial 1, cyclists completed two incremental cycling tests to establish the V ˙ O2-power output relationship and V ˙ O2max. In trials 2 and 3, cyclists were evaluated for heart rate and HRV at rest, after which they ingested a capsule containing 5 mg·kg−1 of caffeine or placebo. Thirty-five minutes post-supplementation, additional resting heart rate and HRV readings were taken after which cyclists completed a submaximal incremental cycling test (6 min stages) at 40–80% of V ˙ O2max; with HR and HRV measurements taken in the last 5 min of each increment. HRV was determined from the root mean square of successive differences between R–R intervals. There were significant supplement × exercise intensity interactions on heart rate (p = .019) and HRV (p = .023), with post hoc tests on the latter showing that caffeine increased HRV at 40%, 50%, and 60% of V ˙ O2max by 3.6 ± 4.9, 2.6 ± 2.8, and 0.6 ± 1.7 ms, respectively. There was a supplement × time interaction effect on resting HRV (p < .001), but not on heart rate (p = .351). The results of this study support the suggestion that caffeine increases the parasympathetic modulation of heart rate.Clinical trial registration number: NCT05521386.

A comparative evaluation of intraperitoneal bupivacaine alone and bupivacaine with dexmedetomidine for post-operative analgesia following laparoscopic cholecystectomy.

Intraperitoneal instillation of local anaesthetic agents alone or in combination with opioids, α2 agonists such as Dexmedetomidine have been found to reduce postoperative pain following laparoscopic cholecystectomy. The study was designed to compare the better drug among Bupivacaine alone and Bupivacaine with Dexmedetomidine with respect to their analgesic efficacy and safety profile. in patients undergoing laparoscopic cholecystectomy. The study was carried out on sixty patients of the American Society of Anaesthesiologists (ASA) physical status I-II of either sex with ages ranging from 18 to 60 years posted for elective laparoscopic cholecystectomy under General Anaesthesia, equally divided into two groups, randomly allocated to one of the Groups using the table of randomization. Group B received Intraperitoneal Bupivacaine 40 ml 0.25% +5 ml normal saline and Group BD received Intraperitoneal Bupivacaine 40 ml 0.25% + Dexmedetomidine1 μg/kg diluted in 5 ml Normal saline. The mean heart rate and blood pressure (systolic, diastolic and mean) readings were significantly lower in Group BD than in Group B. The mean duration of analgesia in our study was longer in Group BD (7.5 ± 0.73 hours) when compared to Group B (5.9 ± 0.55 hours) with p-value & 0.0001 and CI 1.27 to 1.9, which was statistically significant. However, the post-operative analgesic requirement (rescue/demand) in Group B was clinically earlier and statistically significant as compared to Group BD. Postoperative VAS score ≥3 was considered the benchmark for providing rescue analgesia in the form of injection of Diclofenac 75 mg IV. In our study, we observed the pain scores via VAS/NRS at 30 min, 1 h, 2 h, 4 h, 6 h, 8 h, 10 h, 12 h, 14 h, 16 h, 18 h, 20 h, 22 h and 24 h postoperatively. A comparison of pain scores from 30 min to 10hrs postoperatively showed a significant difference in both Groups with Group B having significantly higher VAS scores and lower VAS scores with Group BD. Our study suggests that there is a shorter duration of action of 0.25% Bupivacaine alone as compared to 0.25% Bupivacaine + Dexmedetomidine. Since the laparoscope is still inside the abdominal cavity the drugs are easy to administer with no adverse effects and with a good safety profile because of the visualization of drug deposition in the right place. Intraperitoneal instillation of Bupivacaine with Dexmedetomidine for postoperative analgesia was very promising as a part of multimodal analgesia in laparoscopic cholecystectomy.

Research and Design of A Multifunctional Heart Rate Detection System

Addressing the limitations of conventional heart rate detectors, which solely monitor heart rate without providing alerts during critical incidents, a multifunctional heart rate detection system has been developed. This system incorporates a GD32 as the main controller and utilizes a pulse sensor for heart rate monitoring, an MLX90614 infrared temperature sensor for body temperature measurements, an MPU6050 acceleration sensor for motion posture detection, and a SIM868 module for GPS positioning and server communication. This comprehensive setup allows for real-time monitoring of the wearer's heart rate and body temperature, assessment of fall incidents based on motion posture data, and regular uploading of health data to a server. Additionally, the system is equipped with a one-touch emergency call feature. In the event of abnormal heart rate readings or a fall, it triggers an alarm, acquires GPS coordinates, and automatically dials an emergency contact number. After thorough testing and verification, the system has demonstrated full functionality with heart rate data accuracy within the expected error range, offering a reliable safety mechanism for patients while on the move.

PSIV-A-8 Effects of meal frequency on heart rate in horses

Abstract In humans, meal size has been shown to affect heart function with meal ingestion being associated with an increase in heart rate (HR) and cardiac output lasting significantly longer when larger meals are consumed. In horses, HR spikes at the sight of feed due to anticipation, but no studies have specifically evaluated the effect of meal frequency or size on HR. Heart rate has also been used as a measure both positive and negative stress. Domesticated horses are often meal fed, with small frequent meals requiring more labor than large infrequent meals. Fewer larger meals may have negative welfare implications for a grazing species. As part of a larger project investigating the effects of meal frequency on the behavior and metabolism of horses, the objective of this study was to evaluate equine HR in response to feeding frequencies commonly practiced in the field [once (1x), twice (2x), or thrice (3x) per day]. Feeding times were at 0800 (1x, 2x, and 3x), 1300 (3x), and 1800 (2x and 3x) h. The 12 adult clinically healthy horses [average ± SD; 14 ± 6 yr and 572 ± 32 kg body weight (BW)] were separated into two equal groups before completing a 14-d acclimation period to the diet during which they were fed 2x. The diet was provided at 2% BW on a dry matter (DM) basis (1.55% BW grass hay in a slow feed hay net plus 0.45% BW complementary fortified feed). During the study the same diet was fed but the meal frequency, and therefore meal size, differed between the treatments. The order of treatments, lasting 1 wk each, was decided at random for each group. On d 6 of each treatment HR was measured using individual H10 Polar HR monitors, which recorded every second from 0700 to 1900 h yielding 1,514,799 data points. During this time the aisleways housing the stalled horses were blocked off to minimize exposure to human presence other than at feeding time(s). After removing outliers, the mode was calculated for HR of each horse, which was considered to be the resting HR for that horse and ranged from 31 to 46 beats/min. The percentage of data above, below, or at the mode was calculated for each horse over the 12 h period and evaluated using Chi Square tests for statistical significance. The proportion of HR values above, below, or at the mode differed between treatments (P = 0.02). When fed 1x, 69 ± 14% of the HR readings were above the mode on average, as compared with 42 ± 18% and 44 ± 18% for 2x and 3x, respectively. These results suggest that the increase in HR was more than anticipatory and that there may be sustained stress when horses are fed at fewer frequency, such as once daily.

HRpredict: Introducing a Web-Based Application for Heart Rate Prediction and Lifestyle Recommendations

Background: Monitoring heart health requires early detection of deviations in HR, which makes it easier to detect and address heart irregularities at an early stage. Health remote systems when combined with artificial intelligence (AI) can assist in better health outcomes through early detection of heart problems. Aims: Our main goal is to create a website application (Web-App) for web browser access, aiming to utilize a Random Forest (RF) machine learning (ML) model trained to predict the average heart rate (HR) over 10 days for different periods, and to enable lifestyle and activity recommendations. Methods: The Web-App is created using Laravel, an open-source Personal Home Page (PHP) web framework that follows the model-view-controller (MVC) architectural pattern. Results: This research resulted in a web-based ML model that can be used to predict future heart rates over a 10-day period which are utilized to establish average HR values, considering baseline and three distinct periods: morning, noon, and evening across the 10-day duration. Through this Web-App lifestyle, habit, activity, and 10-day reassessment recommendations are also provided. Conclusion: The Web-App was designed to be accessed and used through a web browser, to provide lifestyle recommendations based on predicted HR readings. To determine the impact of users adhering to recommendations, further research is required.

Comparison Between 3 Different Norepinephrine Bolus Doses for Management of Postspinal Hypotension During the Caesarean Section for Patients with Preeclampsia: A Randomized Controlled Trial

Background: There is no established dose for norepinephrine (NE) in the management of postspinal hypotension. The data on its use in women with preeclampsia (PE) are limited. Objectives: This study aimed to compare the effect of using different NE bolus doses for the management of postspinal hypotension during lower segment cesarean section for patients with PE. Methods: This randomized, double-blind trial included mothers with PE scheduled for cesarean delivery who developed postspinal hypotension. Sixty participants were allocated to receive 3, 4, or 5 µg of NE bolus. The primary outcome was the neonatal bicarbonate level. The secondary outcomes were successful management of hypotension, incidence of reactive hypertension, nausea, vomiting, systolic blood pressure (SBP), and heart rate (HR) readings through the operation, umbilical blood gases, and Apgar scores. Results: The number of hypotensive episodes, bradycardia episodes, successfully treated hypotensive episodes, and total NE dose per patient were lower in the 4- and 5-µg groups compared with the 3-µg group. Systolic blood pressure was generally higher in the 4- and 5-µg groups than in the 3-µg group starting from 12 min postspinal till 28 min postspinal. The heart rate decreased compared to the baseline reading starting from 4, 6, and 2 min postspinal in the 3-, 4-, and 5-µg groups, respectively, till 28 min postspinal. Also, HR was higher in the 4- and 5-µg groups compared to the 3-µg group at 6-12 min postspinal. Following the first NE bolus, SBP remained lower than the baseline reading in the 3 groups, and HR decreased compared to the baseline reading in the 3- and 5-µg groups only. Conclusions: The 3-, 4-, and 5-µg doses had comparable efficacy in managing the first hypotensive episode and comparable neonatal outcomes. The 4- and 5-µg doses significantly decreased the total NE requirements and the number of hypotensive episodes. The incidence of maternal bradycardia was not significantly different between the groups.

Smart Portable Ice Bath Monitoring System for Athlete

After athletic injuries, cold techniques are used commonly, with clear physiological effects. The main theory about the advantages of immersion in cold water is that it decreases skeletal muscle inflammation. This study was to design the electronic part of smart portable ice bath monitoring system for the athletes to use after their exercises. The design can capture cold water temperature reading and heart rate precisely during the therapy. The readings also were used to give out notifications and alarm to prevent cold related diseases. Various of components were listed and only the most compatible with the design were chosen. The criteria of the components are small, light in weight and the most important is waterproof. To have the portable design of cold-water immersion easy to use and understand, a smartphone application was created by using MIT App inventor, thus giving the athlete a platform to monitor their heart rate data and aware of the benefit and disadvantage of cold-water immersion. Three independent subjects' heart rates were recorded and compared to test the hypothesis that there is a significant difference in heart rate readings between the heart rate sensor and the Amazfit GTS 2. While three tests on the temperature of cold water were used to test the hypothesis that the temperature readings produced by temperature sensor and mercury thermometer had a significant difference. Response of the data from both tests were analysed by using a t-test. The results of both experiments revealed that the hypothesis was rejected, indicating that the heart rate sensor and temperature sensor are adequate for monitoring heart rate and cold-water temperature. They were displayed on the LCD display and the MIT app inventor application in a smartphone. The notification alarm is also effective. In conclusion, the study's objectives have been achieved, and the design can be applied in cold water immersion therapy.

CONTROL DRIP RATE OF INTRAVENOUS FLUIDS BASED ON HEART RATE WITH A MONITORING SYSTEM USING THINGSPEAK WEBSITE

Dehydration is a state of decreasing the amount of fluid in the body accompanied by increased heart rate. One of the treatments that must be done for dehydrated patients is to give infusions periodically, which must be supervised by medical personnel. However, controlling patient intravenous fluid drops in some hospitals or public health centres is still done manually. Based on this problem, a device can adjust the drip rate of intravenous fluids based on heart rate. This research made a prototype of controlling the drip rate of intravenous fluid based on heart rate using NodeMCU ESP8266 microcontroller, MAX30100 sensor for heart rate reading, optocoupler sensor for drip rate reading, and servo motor for roller clamp drive. From the test results, the system has been able to control the drip rate of infusion based on heart rate with a range of (80 – 89) bpm which has the number of infusion droplets (24 – 35) TPM and a range (90 – 99) bpm that has the number of drip infusions (36 – 47) TPM, then send the heart rate data and drip rate of the injection to the thing speak website every 15 seconds. Heart rate readings with MAX30100 sensors have an error of 2.51% and an accuracy of 97.49%. Meanwhile, the drip rate reading with the optocoupler sensor has an error of 0.83% and an accuracy of 99.17%.

Design of Medical Devices to Monitor Body Temperature, Heart Rate And Oxygen Saturation Levels In Human Body Based On IoT

Understanding body temperature and heart rate plays a crucial role in detecting disease symptoms. Heart rate serves as a vital parameter reflecting human body function, with a typical range of 60-100 beats per minute for adults. This study aims to leverage Internet of Things (IoT) technology to create a monitoring system for heart rate and body temperature.The main objective of this final project is to design a device capable of monitoring body temperature, heart rate, and oxygen saturation levels in the human body. The anticipated benefits of this research include facilitating the continuous monitoring of body temperature, heart rate, and oxygen saturation levels, thus aiding in timely health assessments. To achieve this, the study employs the MLX90614 sensor for temperature measurement and the MAX30100 sensor for heart rate and oxygen saturation level readings. These sensors are integrated with the Arduino Nano microcontroller and NodeMCU ESP8266.The study's findings demonstrate that the sensors effectively measure body temperature, heart rate, and oxygen saturation levels, as confirmed by comparison with medical-grade devices. The system developed in this research performs well and is ready for practical application, providing the desired benefits of enhanced monitoring capabilities for healthcare purposes.

IOT-Based Human Vital Sign Monitoring Tool Using Telegram Notifications (BPM and Respiration Rate Parameters)

Vital signs play a crucial role in monitoring the progress of adult or pediatric patients during hospitalization, as they enable prompt detection of delayed recovery or adverse events. Vital signs are measured to obtain fundamental indicators of the patient's health status. The measurement of vital signs, including blood pressure, temperature, pulse, and respiratory rate, is the most common intervention in hospital medicine. Advanced monitoring systems combine clinical and technological aspects to deliver innovative healthcare outcomes. Remote patient monitoring systems are increasingly becoming the cornerstone of healthcare delivery, replacing traditional manual recording with computer and smartphone-based electronic recording as a versatile and innovative health monitoring system. This study aims to design a Vital Sign Monitoring Parameter BPM and RR tool with Notifications via the IoT-Based Telegram application. The tool enables the monitoring of vital signs, particularly BPM and RR, regardless of the patient's location and at any given time. This allows doctors, health workers, and patients to stay informed about their health condition. Real-time display of vital sign data is available through the TFT LCD screen, and the data from the screen can be accessed via Telegram. The Telegram application will send notifications in the event of abnormal patient conditions. MAX30100, a digital sensor for detecting breathing rate and heart rate, is utilized in this research. Furthermore, the data obtained shows errors that are within the allowable limits for each parameter. The difference between the heart rate readings and the respiratory rate values on the device and the patient monitor is 1.14% for heart rate and 0.84% for respiratory rate. This study indicates that it is time to monitor vital signs that can be seen remotely and have a system that is an inexpensive and easy-to-operate device for health workers without interfering with activities of daily living.

A CNN based multifaceted signal processing framework for heart rate proctoring using Millimeter wave radar ballistocardiography

The recent pandemic has refocused the medical world’s attention on the diagnostic techniques associated with cardiovascular disease. Heart rate provides a real-time snapshot of cardiovascular health. A more precise heart rate reading enables a better understanding of cardiac muscle activity. Although many existing diagnostic techniques are approaching the limits of perfection, there remains potential for further development. In this paper, we propose MIBINET, a novel multifaceted approach for real-time proctoring of heart rate from Millimeter wave (mm-wave) radar ballistocardiography signals via inter-beat-interval (IBI) using a convolutional neural NETwork (CNN). The central theme of our approach is to synergize the feature extraction capabilities of CNN with novel signal processing techniques, resulting in enhanced estimation accuracy while simultaneously reducing computational complexity. This proposed network can be used in hospitals, homes, and passenger vehicles due to its lightweight and contactless properties. It employs classical signal processing prior to fitting the data into the network. Although MIBINET is primarily designed to work on mm-wave signals, it is found equally effective on signals of various modalities such as PCG, ECG, and PPG. Our approach outperforms state-of-the-art techniques by more than 5% in inter-beat-interval (IBI) estimation accuracy. The architecture achieves a 98.73% correlation coefficient and a 20.69 ms Root-Mean-Square Error (RMSE) over 11 different test subjects. The paper contributes by being the first to apply CNN-based feature extraction in concert with unique signal processing strategies to mm-wave radar data for heart rate monitoring. Our methodology also introduces a synthetic IBI augmentation technique, custom loss function, and novel post-processing methods, all contributing to the robust performance of the model in various settings and modalities.

IoT-based health care system for emotional and heart rate monitoring

An IoT-based remote health monitoring system helps patient’s especially older adults and non-communicable disease (NCD) patients to get medical assistance or advice without being physically present in the hospital or medical centre. This system provides regular health monitoring from anywhere by having access to the Internet. One of the important elements is the physiological parameters which indicate the health status of the monitored patients. Literature study shows that most of the previous works monitor blood pressure, respiratory rate, temperature, ECG, blood oxygenation, diabetes, and hypertension. There have been little works paid attention to measuring the emotional level of the patient. Therefore, this paper explains the development of an IoT-based health monitoring system that measures the emotional level of the patient apart from other essential physiological parameters. The system consists of a microcontroller, two sensors, a wireless communication module, and an IoT cloud display, focusing on measuring the heart rate, body temperature, SpO2, and emotional level. For the heart rate and body temperature readings, the measurements acquired from the developed system show a close agreement with those of the established brand ROSSMAX with an error of less than 5%. For the emotional level test, there are 83.3% out of twelve subjects agree that the GSR value shows her feeling.

Sparrow Search Algorithm based BGRNN Model for Animal Healthcare Monitoring in Smart IoT

Rural regions rely heavily on agriculture for their economic survival. Therefore, it is crucial for farmers to implement effective and technical solutions to raise production, lessen the impact of issues associated to animal husbandry, and improve agricultural yields. Because of technological developments in computers and data storage, huge volumes of information are now available. The difficulty of extracting useful information from this mountain of data has prompted the development of novel approaches and tools, such as data mining, that can help close the informational gap. To evaluate data mining methods and put them to use in the Animal database to create meaningful connections was the goal of the suggested system. The study's primary objective was to develop an IoT-based Integrated Animal Health Care System. Various sensors were used as the research tool to collect physical and environmental data on the animals and their habitats. Temperature, heart rate, and air quality readings were the types of information collected. This research contributes to the field of health monitoring by introducing an Optimised Bidirectional Gated Recurrent Neural Network approach. The BiGRNN is an improved form of the Gated Recurrent Unit (GRU) in which input is sent both forward and backward through a network and the resulting outputs are connected to the same output layer. Since the BiGRNN method employs a number of hyper-parameters, it is optimised by means of the Sparrow Search Algorithm (SSA). The originality of the study is demonstrated by the development of an SSA technique for hyperparameter optimisation of the BiGRNN, with a focus on health forecasting. Hyperparameters like momentum, learning rate, and weight decay may all be adjusted with the SSA method. In conclusion, the results demonstrate that the suggested tactic is more effective than the current methods.

Ultrasound-guided ilioinguinal/iliohypogastric nerve block compared to posterior quadratus lumborum block in patients undergoing inguinal hernia repair

ABSTRACT Background “Ilioinguinal/iliohypogastric nerve block” (IINB) has been described as effective regional anesthetic method for providing analgesia after inguinal hernia operations. Other studies have also reported that the “posterior quadratus lumborum block” (PQLB) is an effective analgesic option for lower abdominal surgeries. Herein, we compared the previous two block techniques for postoperative pain management in adults undergoing unilateral inguinal hernia repair. Methods According to the block technique, 76 adult patients scheduled for inguinal hernioplasty under general anesthesia were randomly enrolled into two groups; the PQLB and IINB groups. The block was performed after skin closure and before patient extubation. Postoperative analgesic profiles were recorded in both groups. Results The PQLB had lower heart rate and mean arterial pressure readings during postoperative assessment compared to the other group. Pain scores showed a significant decline in association with the PQLB during the first postoperative day, which resulted in a significant decline in pethidine consumption (49.17 vs. 70 mg in the IINB group) and better patient satisfaction. The duration to the first analgesic request significantly increased in association with the PQLB (13.25 vs. 8.42 hours in the IINB group). The incidence of nausea and vomiting increased significantly in the IINB group secondary to increased pethidine requirements. Conclusion PQLB is superior to IINB in providing analgesia for patients undergoing inguinal hernia repair.

Low-cost central monitor based personal computer with electrocardiogram and heart rate parameters via wireless XBee Pro

Heart rate signals and electrocardiograms are crucial indicators of a person’s health, particularly for individuals in intensive care units (ICU). The goal of this study is to wirelessly use a central monitoring system to continually and in real-time monitor the electrocardiogram signal and heart rate. The result of this research is that a wireless system can transmit continuous, distant, and real-time electrocardiogram and heart rate readings. Two transmitters and two receivers were used to send the signal in real-time. Lead II was used to capture the electrocardiogram (ECG) data, which was then processed by a microprocessor to determine the heart rate in beats per minute. The XBee Pro wireless was then used to transmit the data to the monitor in the form of an electrocardiogram and heart rate signal. The results of the XBee wireless performance test with statistics for determining heart rate value revealed that there was no discernible difference in the average value at a distance of 8, 10, 25, and 30 meters (P-value &gt; 0.05). According to the study’s findings, wireless transmission is feasible over a limited distance and in real-time. Hospitals can use a central monitor to implement this research.