Heart Rate Readings Research Articles

IoT framework of telerehabilitation system with wearable sensors for diabetes mellitus patients

Physical activity is commonly used as a treatment for diabetes patients, although its effectiveness in improving cognitive functions such as learning, thinking, remembering, and decision making is not clear. Regular exercise can gradually improve metabolic abnormalities associated with pre-diabetes and assist patients with type-2 diabetes (T2D) in managing their pharmacological treatment. The usage of mobile health (mHealth) as a tool to help diabetes patients with their diabetes self-management have been demonstrated in previous studies and it can lead to reductions in glycosylated hemoglobin (HbA1c) levels. Heart rate readings during physical activity is beneficial for healthcare professionals (HCP) to ensure appropriate intensity levels for their patients is achieved. Additionally, the list of the tailored physical activities is long, and it is quite challenging for the T2D patients to remember. Therefore, Tele-DM is proposed, consisting of a smartwatch and mobile application that enable remote physiotherapy sessions for T2D patients. The smartwatch transfers the heart rate data to Tele-DM through Google Fit database. The system provides tailored exercise programs to help patients reduce their weight and HbA1c levels. With the ability to facilitate two-way communication between HCP and T2D patients, the Tele-DM system is designed to enable an effective remote rehabilitation process.

Power Saving Approach of a Smart Watch for Monitoring the Heart Rate of a Runner

Heart Rate (HR) monitoring in a smart watch is a battery consuming process. Therefore, some smart watches prevent continuous HR sampling during low-level physical activities for improving the power usage of batteries. However, high acceleration events like running require continuous HR sampling for recording the varying HR readings, which consumes a lot of battery power. Therefore, the challenge is to reduce the sampling during running while recording an individual’s HR variation (HRV). Our approach prevents continuous HR sampling for long-running events without missing important HR information. In this context, we analyze the existing real-life HRs and acceleration datasets recorded on humans during long runs. We design an adaptive HR sampling algorithm, A-HeaRing, from the extracted HR variation details. A-HeaRing reduces the battery power consumption of a smart watch by more than 50% while recording a running event. Additionally, we design a data regeneration system for missing HR readings. The regeneration system provides a minimum of 90% accuracy in the HR zone estimation.

Atracurium versus cisatracurium: A comparison of efficacy and safety of intubating dose in adult surgical patients

Abstract Background: Our study investigated and compared the properties of atracurium and cisatracurium, nondepolarizing neuromuscular blocking agents from the benzylisoquinolinium group. Both of these agents exhibit an intermediate duration of action. We studied the onset of neuromuscular blockade, intubating conditions, hemodynamic stability, and recovery following intubating doses. Materials and Methods: We conducted a study involving 40 patients undergoing general anesthesia, randomly assigned to two groups. Group A, consisting of 20 patients, received a dose of 0.6 mg/kg of atracurium, while Group C, also with 20 patients, received 0.15 mg/kg of cisatracurium. Throughout the surgery, we observed and recorded the time of onset of neuromuscular blockade, the intubating conditions, and the recovery following the administration of the first dose of neuromuscular blocking agents. Additionally, we continuously monitored the patient’s hemodynamic status until they recovered from the initial dose. Results: Group C exhibited a significantly faster onset of action (231.5 ± 31.2 s) than Group A (291.0 ± 14.1 s) for the administered neuromuscular blocking agents. The recovery duration following the intubating dose was notably shorter in Group A (31 ± 6.20 min) compared to Group C (50.5 ± 3.20 min). Additionally, in the cisatracurium group, all patients (100%) achieved “excellent” intubating conditions, whereas in the atracurium group, this was only the case for 60% of patients, and this difference was statistically significant. Furthermore, the atracurium group showed significantly higher heart rate and mean arterial pressure readings at different intervals than the cisatracurium group. Importantly, no adverse reactions were observed in any of the patients throughout the study. Conclusion: Compared to atracurium (0.6 mg/kg), cisatracurium at a dose of 0.15 mg/kg demonstrates superior effectiveness regarding the onset and duration of neuromuscular blockade and intubating conditions. Furthermore, cisatracurium offers a more favorable hemodynamic profile.

Enhanced sub-1 eV detection in organic photodetectors through tuning polymer energetics and microstructure.

One of the key challenges facing organic photodiodes (OPDs) is increasing the detection into the infrared region. Organic semiconductor polymers provide a platform for tuning the bandgap and optoelectronic response to go beyond the traditional 1000-nanometer benchmark. In this work, we present a near-infrared (NIR) polymer with absorption up to 1500 nanometers. The polymer-based OPD delivers a high specific detectivity D* of 1.03 × 1010 Jones (-2 volts) at 1200 nanometers and a dark current Jd of just 2.3 × 10-6 ampere per square centimeter at -2 volts.We demonstrate a strong improvement of all OPD metrics in the NIR region compared to previously reported NIR OPD due to the enhanced crystallinity and optimized energy alignment, which leads to reduced charge recombination. The high D* value in the 1100-to-1300-nanometer region is particularly promising for biosensing applications. We demonstrate the OPD as a pulse oximeter under NIR illumination, delivering heart rate and blood oxygen saturation readings in real time without signal amplification.

EFFECT OF COVID-19 ON BLOOD PRESSURE VARIABILITY IN HYPERTENSIVE PATIENTS

Objective: To investigate the influence of COVID-19 on blood pressure variability in hypertensive patients with known subclinical organ damage (SCOD) previously assessed by evaluation of brachial artery Flow Mediated Dilatation (FMD), carotid artery Intima Media Thickness (IMT), left ventricular mass indexed to BSA (LVMI), E/e` ratio, left atrial volume indexed to BSA (LAVI). Design and method: We assessed 108 hypertensive patients who had SARS-CoV-2 infection in the previously 3 months before evaluation. All subjects included where evaluated for the presence of SCOD in the last 12 months before COVID-19 and underwent a 24-hour noninvasive ABPM on a working day, performing usual daily activities and avoiding heavy physical exercise. BP and heart rate readings were obtained every 15 minutes during daytime and every 30 minutes during nighttime. Subjects recorded a journal of the activities performed and the time of retiring to bed, ABPM recordings being divided into ‘awake’ or ‘asleep’ periods based on diary entries and not on predefined time intervals. BP variability was calculated as the standard deviation (SD) of mean blood pressure. Results: The hypertensive patients with previously known subclinical disease (SCOD+) compared with those without it (SCOD–) had significantly higher systolic and diastolic BP after SARS-CoV-2 infection, and significantly increased variability of both systolic and diastolic BP. Also, they had a significantly reduced decrease of nocturnal systolic BP (table 1). The analysis for each marker of subclinical organ damage indicated that increased systolic BP variability in hypertensive COVID-19 patients was significantly correlated with carotid IMT (r = 0.517, p = 0.001), brachial artery FMD (r = 0.426, p = 0.008), LVMI (r = 0.397, p = 0.009), E/e` ratio (r = 0.543, p = 0.001), left atrial volume indexed to BSA (LAVI) (r = 0.478, p = 0.003) and that diastolic BP variability is significantly correlated with carotid IMT (r = 0.362, p = 0.09), brachial artery FMD (r = 0.491, p = 0.006), LVMI (r = 0.369, p = 0.008), E/e` ratio (r = 0.422, p = 0.005), left atrial volume indexed to BSA (LAVI) (r = 0.407, p = 0.002). Conclusions: Our study indicates that SARS-CoV-2 infection in hypertensive patients induces an increased blood pressure variability which is significantly correlated with the presence of previously diagnosed subclinical disease.

The quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics

We aimed to assess the frequency of value preferences in recording of vital signs in electronic healthcare records (EHRs) and associated patient and hospital factors. We used EHR data from Oxford University Hospitals, UK, between 01-January-2016 and 30-June-2019 and a maximum likelihood estimator to determine the prevalence of value preferences in measurements of systolic and diastolic blood pressure (SBP/DBP), heart rate (HR) (readings ending in zero), respiratory rate (multiples of 2 or 4), and temperature (readings of 36.0 °C). We used multivariable logistic regression to investigate associations between value preferences and patient age, sex, ethnicity, deprivation, comorbidities, calendar time, hour of day, days into admission, hospital, day of week and speciality. In 4,375,654 records from 135,173 patients, there was an excess of temperature readings of 36.0 °C above that expected from the underlying distribution that affected 11.3% (95% CI 10.6–12.1%) of measurements, i.e. these observations were likely inappropriately recorded as 36.0 °C instead of the true value. SBP, DBP and HR were rounded to the nearest 10 in 2.2% (1.4–2.8%) and 2.0% (1.3–5.1%) and 2.4% (1.7–3.1%) of measurements. RR was also more commonly recorded as multiples of 2. BP digit preference and an excess of temperature recordings of 36.0 °C were more common in older and male patients, as length of stay increased, following a previous normal set of vital signs and typically more common in medical vs. surgical specialities. Differences were seen between hospitals, however, digit preference reduced over calendar time. Vital signs may not always be accurately documented, and this may vary by patient groups and hospital settings. Allowances and adjustments may be needed in delivering care to patients and in observational analyses and predictive tools using these factors as outcomes or exposures.

Are Activity Wrist-Worn Devices Accurate for Determining Heart Rate during Intense Exercise?

The market for wrist-worn devices is growing at previously unheard-of speeds. A consequence of their fast commercialization is a lack of adequate studies testing their accuracy on varied populations and pursuits. To provide an understanding of wearable sensors for sports medicine, the present study examined heart rate (HR) measurements of four popular wrist-worn devices, the (Fitbit Charge (FB), Apple Watch (AW), Tomtom runner Cardio (TT), and Samsung G2 (G2)), and compared them with gold standard measurements derived by continuous electrocardiogram examination (ECG). Eight athletes participated in a comparative study undergoing maximal stress testing on a cycle ergometer or a treadmill. We analyzed 1,286 simultaneous HR data pairs between the tested devices and the ECG. The four devices were reasonably accurate at the lowest activity level. However, at higher levels of exercise intensity the FB and G2 tended to underestimate HR values during intense physical effort, while the TT and AW devices were fairly reliable. Our results suggest that HR estimations should be considered cautiously at specific intensities. Indeed, an effective intervention is required to register accurate HR readings at high-intensity levels (above 150 bpm). It is important to consider that even though none of these devices are certified or sold as medical or safety devices, researchers must nonetheless evaluate wrist-worn wearable technology in order to fully understand how HR affects psychological and physical health, especially under conditions of more intense exercise.

BLOOD PRESSURE VARIATIONS ASSOCIATED WITH AGEING IN SUB-SAHARAN AFRICA

Elderly persons who live in communities and appear to be in good health frequently experience postural hypotension, which is frequently asymptomatic. Uncertainty exists regarding the relationship between postural changes in blood pressure and numerical factors including age, gender, and body mass index. The goal of the current study is to identify the orthostatic blood pressure (OBP) changing patterns, symptoms, and related factors in various age groups. In this study, sixty participants ranging in age from 20 to 75 years old were used. To check for orthostatic hypotension in these groups, various blood pressure readings are taken in the lying and standing positions at intervals of one minute and three minutes. The findings demonstrated that in the elderly groups, symptoms of headache, blurred vision, dizziness, and lightheadedness were unrelated to orthostatic hypotension. These subjects' Body Mass Indexes were calculated based on their nutritional condition, and they were found to be 60% well-nourished, 6% under-nourished, and 34% overweight. The elderly person had systolic hypotension (P<0.01) more frequently than diastolic hypotension (P>0.05). In the senior group, standing hypotension was equally common in both sexes. BMI declines with aging in males as well, n=60. In all four groups, heart rate readings in the standing position were greater than the supine measurement. In the older population of Ndola which was the subject group of the study, 16.7% had OH. Age and the decline in diastolic blood pressure after three minutes of standing were positively correlated in all males. In all females, a positive link was seen between body mass index and a reduction in diastolic blood pressure after three minutes of standing. After 3 minutes of standing, all males showed a positive link between body mass index and a decrease in systolic blood pressure. Therefore, there is a link between body mass index and a drop in blood pressure readings when standing. On the basis of the current study, we draw the conclusion that orthostatic hypotension rises with age and that symptoms are unrelated to physical measurements.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0202/a.php" alt="Hit counter" /></p>

PS-C11-2: FACTORS AFFECTING HOME BLOOD PRESSURE AND HEART RATE VARIABILITY POST-COVID INFECTION

Objective: There is a scarcity of data on the factors that influence home blood pressure (BP) and heart rate (HR) variability. This study was undertaken to determine the factors that influence home BP and HR fluctuation post COVID infection in the urban Indian population. Designs and Methods: We conducted a cross-sectional study among 1000 patients between the ages of 30 and 80 who were previously infected with COVID-19 infection, but not hospitalized. These patients were guided and trained to measure BP at home. BP and HR readings were taken at home twice a day, in the morning and evening, for seven days (28 measurements). The SD of morning minus evening, and first minus second readings was used to calculate BP and HR variability. Results: Old age, cardiovascular illness, diabetes, and high home blood pressure were all found to be independent predictors of an increased morning than evening home blood pressure variability. Old age, and high home blood pressure were all independent determinants of greater day-to-day home blood pressure variability, while old age, female sex, cardiovascular disease, and high home blood pressure were all independent determinants of greater first versus second home blood pressure variability. Young age, and high home HR, on the other hand, were all independent drivers of increased morning vs evening variability. Young age, female sex, and a high home HR were also independent predictors of first versus second home HR variability. Conclusion: Considering home BP and HR fluctuation have prognostic value, it is critical for clinicians to understand the underlying reasons for these variables. Doctors should focus on alcohol, diabetes, and cardiovascular disease prevention counseling for their high-risk patients.

Cardiac arrest & heart failure preventive wearable smart chest belt

This abstract introduces a wearable smart chest belt designed to prevent cardiac arrest and heart failure. The proposed device utilizes advanced sensor technology to continuously monitor vital signs, including heart rate, blood pressure, and electrocardiogram (ECG) readings. Through real-time data analysis and machine learning algorithms, the chest belt can detect early warning signs of cardiac abnormalities, allowing for prompt intervention and preventive measures. The wearable device also incorporates a user-friendly interface, providing personalized health insights and recommendations to users. By leveraging the power of wearable technology, this cardiac arrest and heart failure preventive chest belt offers a proactive and convenient solution for individuals at risk, ultimately promoting cardiovascular health and reducing the incidence of life-threatening events. In conclusion, the cardiac arrest and heart failure preventive smart wearable belt that generates shocks below 15 bpm holds great promise in improving the management and prognosis of individuals at risk of cardiac events. With further advancements and refinements, this technology has the potential to revolutionize cardiovascular care by providing proactive interventions and empowering individuals to take control of their heart health. The development of the cardiac arrest and heart failure preventive smart wearable belt represents a significant advancement in preventive healthcare technology. By continuously monitoring heart rate and intervening with controlled shocks below 15 bpm, this innovative device has demonstrated its potential to prevent cardiac arrest and heart failure in high-risk individuals. The real-time monitoring and early detection capabilities of the wearable belt enable timely intervention, reducing the risk of life-threatening complications and improving patient outcomes.

Assisting Healthcare Using a Time-Series-Based Nonstationary Model for Smart Beds

Under any medical circumstance, the first and foremost requirement is to monitor physiological factors such as heart rate, blood pressure and oxygen level. Any breakdown in their coupling has been linked to ageing or illness. These physiological signals are nonstationary, and this paper analyses the transfer functions of nonstationary multidimensional time series of physiological signals. In this work, a method that integrates physiological modelling and functional elements into the smart bed for patients is proposed. This work includes experimentation on 10 smart bed patients. The proposed idea is validated and analysed to automatically capture any changes in the physiological signals due to postural changes, any impact of ageing or any requirement of a medical emergency. Next, it is demonstrated that the proposed method can be used to identify transient changes linked to medical emergencies for the given time-series data. These findings show the value of the proposed method in predicting the complicated vital-sign processes where conventional manual autoregulatory systems may fail in both healthy and pathological situations. The relation between the time series of physiological signals is an essential study field. A reliable time-varying model is presented to account for the possible nonstationarity of physiological data to determine the possibility of emergency care for patients. The suggested approach can identify variations and relations between signals because it is built as a dynamic model based on time-varying parameters. The technique used in this research includes readings of heart rate, blood pressure and oxygen level connected to the patient’s smart bed. The paper includes transient analysis and parametric evaluation as part of this work.

QRS Complex Detection On Heart Rate Variability Reading Using Discrete Wavelet Transform

Heart Rate Variability or heart rate in humans is used to monitor the heart rate in humans, the function of the heart rate monitor is to monitor the human heart rate. The purpose of making this tool is to compare the results of heart rate readings using the discrete wavelet transform method to facilitate the detection of R peak. This can be learned by evaluating and studying each decomposition result from level 1 to level 4 on Discrete Wavelet Transform processing using Haar mother wavelets. This study uses a raspberry pi 3B as a microcontroller as a data processor that is obtained from the ECG module. From this study, it can be concluded that in heart rate readings, level 2 decomposition details coefficient has the best value as data processing that helps for heart rate readings with an error value of 0.531%, HRV readings of 0.005 in comparison with phantom tools and a standard deviation of 0.039. The advantage of this tool is a good precision value in HRV and BPM readings. In reading the HRV of the respondent, it was found that each initial condition of the patient's HRV would be high due to the respondent's unstable condition. The disadvantage of this tool is that there is a delay in running the program, there is no display in the form of a signal in real time.

Early detection model of normal and abnormal blood flow using pulse Oximetry non-invasive of pregnant heart rate

The heart is an important organ in humans as an identification of early examinations in pregnant women carried out by doctors to determine normal and abnormal pregnancies in the fetus. Heart rate or BPM (beats per minute) is a parameter that indicates the condition of a person's heart. The normal human heart rate ranges from 60-100 beats per minute. In pumping blood throughout the body, the heart then holds it back after being cleaned by the lungs and this is closely related to the level of oxygen flowing in the bloodstream. Humans need sufficient oxygen levels in the body to survive. One of the vital monitoring tools for oxygen levels in the human body is pulse oximetry. Pulse oximetry is usually in units or rooms with high and rapid action cases such as the ICU. From these problems, it is necessary to make a research on a diagnostic instrument model for early detection of normal and abnormal blood flow using non-invasive pulse oximetry, a case study of the heart rate of pregnant women which can be identified early through the max 30100 sensor reading in the form of detecting the heart rate and oximeter, then processed by Arduino uno R3 where arduino uno processes data in the form of heart rate and oxymeter readings so that it can be displayed via a 16x2 LCD, the output is the identification of the value of the heart rate and oximeter input so that the normal and abnormal heart rate conditions are known. The purpose of this study is to detect early pregnant women and fetuses with normal or abnormal blood flow using non-invasive pulse oximetry in which case studies are implemented on the heartbeat of pregnant women. The method used in this study uses the hardware programming method by starting with project planning, research, part testing, mechanical design, electrical design, software design, functional test, integration, overall testing and optimization. The measurement results from the MAX30100 sensor are processed on Arduino UNO R3 and displayed on the LCD screen. The system as a whole can work with energy supply from the power supply. After measuring with a comparator that has been calibrated, the average error value of the measurement is 3.32 %.

Virtual Reality Glasses versus Midazolam in Alleviation of Child’s Anxiety during Dental Rehabilitation: Randomized Controlled Clinical Trial

Objective: To evaluate virtual reality glasses versus premedication with oral midazolam, and their effect on separation anxiety and postoperative behavioural changes in children experiencing dental rehabilitation under general anaesthesia. Introduction: Several children suffer anxiety when experiencing dental rehabilitation under general anaesthesia, which may be caused by separation from parents, and negative anticipation of surgical procedures. Midazolam (MDZ) is a generation of Benzodiazepines that have been widely used as a premedication. Whereas distraction is a common technique used to reduce pain and anxiety during short invasive procedures. Methodology: This was a randomized clinical trial; children aged 4-6 years who were healthy, uncooperative, and planned to be treated using general anaesthesia were randomly distributed between two groups (Group I), using the Virtual glasses and (Group II), given oral midazolam. The baseline heart rate (HR) was recorded twice. Ease of separation was assessed for all the participants using the Parental Separation Anxiety Scale (PSAS). The Postoperative behavioural changes were scored using (PHBQ) Questionnaire after 24 hours and 14 days after the operation. Results: Regression analysis showed that the type of intervention was non-significantly associated with the acceptability of separation. Males showed significantly less acceptable separation than females. There was a statistically significant increase in the heart rate readings in both groups when compared before and after separation. The parent-reported child morbidity following the surgery showed no significant difference except when regarding the children “who were upset at mentioning doctors, dentists or hospitals” where (P=0.000). Conclusion: VR and premedication with oral midazolam were both effective strategies for controlling preoperative anxiety in children during parental separation, with lots of advantages when using the VR distraction approach.

Technical note: a nose ring sensor system to monitor dairy cow cardiovascular and respiratory metrics.

Monitoring cardiovascular and respiratory measurements corresponds to the precision livestock farming (PLF) objective to continuously monitor and assess dairy cows' welfare and health. Changes in heart rate, breathing rate, and oxygen saturation (SpO2) are valuable metrics in human and veterinary medicine to assess stress, pain, illness, and detect critical conditions. The common way to measure heart rate is either manually or with a stethoscope. Under research conditions, heart rate is usually measured with a sports watch chest belt. Breathing rate is obtained by counting the cow's flank movements which is a time-consuming and labor-intensive method that requires training and is prone to human error. No devices are available on the market that enable practical and easy pulse oximetry in farm animals. This study presents a wireless nose ring sensor system (NoRS) composed of thermal and photoplothysmography sensors that attach to the nostrils of four Holstein dairy cows. The NoRS's thermocouple measured the cow's nasal cavity air temperature; an optic sensor measured the IR (660 nm) and RED (660 nm) signals reflected from the cow's nasal septum. Breathing was calculated from the thermocouple signal's center frequency with a fast Fourier transformation or the signal peak count (i.e., oscillations). The breathing rate was compared to breathing observed by concurrently counting the flank movements. Heart rate and SpO2 were measured by integrated pulse oximetry and heart rate monitor module (MAX30101 TinyCircuit) assembled on the NoRS circuit. Heart rate was also measured with FFT and by counting the number of peaks from the optic sensor's raw IR and RED signals. These measures were compared to an off-the-shelf hand-held pulse oximeter's heart rate and SpO2 readings during the same time. The comparisons revealed highly significant correlations for the heart rate readings where the strength of the correlation was sensitive to the method. The correlation between breathing rate and the veterinarian's visual observations was low, albeit significant. Thus, inhale-exhale cycle counting constitutes a more precise approach than flank movement counts. The hand-held device's 96% SpO2 is compatible with near-saturation values expected in healthy cows. The mean NoRS SpO2 reading was 3% less. After further piloting under field conditions, the NoRS will require no animal restraining to automatically and continuously record cows' breathing rate, heart rate, and SpO2.

Monitoring Driver’s Heart Rate Response Using Heart Rate Detection Device (HDD)

Introduction: Drowsiness driving is one factor contributing to road accidents resulting in fatalities of drivers and passengers. However, a warning system device to alert drivers about the drowsiness level has never been appropriately developed. This study aims to create a heart rate detection device that monitors drivers’ heart rate and notify them about their drowsiness, which will, in the long term can help to reduce the number of road accidents due to drowsiness. Methods: In this experimental research, ten participants (Mean Age= 24 Years-Old, SD=0.4) were attached to the developed heart rate detection device on the steering wheel of a driving simulator. The participants underwent four 30-min sessions on the driving simulator sessions and heart rate reading throughout the driving period to obtain the heart rate mean value from the first three sessions. The obtained heart rate mean value was set as a threshold value so that the alarm will trigger if the value of heart rate falls below the threshold value in the fourth session. Results: The results showed that the respondents’ average heart rate (bpm) decreased gradually the longer time they drove the car simulator. This study also revealed that the heart rate detection device successfully monitored the driver’s heart rate and notified them when they were at drowsiness level. Conclusion: Overall, the device should be more user friendly by improving the sensitivity of sensors in all parts of the steering wheel for better data collection.

Heart rate detection using single-channel Doppler radar system.

A number of algorithms have been developed to extract heart rate from physiological motion data with the Doppler radar system. Yet, it is very challenging to elimi-nate the noise associated with surroundings, especially with a single-channel Doppler radar system. However, single-channel Doppler radars provide the advantage of operating at lower power. Additionally, the heart rate extraction using single-channel Doppler radar has remained somewhat unexplored. This has motivated us to develop effective signal processing algorithms for signals received from single-channel Doppler radars. In this paper, we have proposed and studied three algorithms for estimating heart rate. The first algorithm is based on applying FFT on an FIR filtered signal. In the second algorithm, autocorrelation was performed on the filtered data. Thirdly, we used a peak finding algorithm in conjunction with a moving average preceded by a clipper to determine the heart rate. The results obtained were compared with the heart rate readings from a pulse oximeter. With a mean difference of 2.6 bpm, the heart rate from Doppler radar matched that from the pulse oximeter most frequently when the peak finding algorithm was used. The results obtained using autocorrelation and peak finding algorithm (with standard deviations of 2.6 bpm and 4.0 bpm) suggest that a single channel Doppler radar system can be a viable alternative to contact heart rate monitors in patients for whom contact measurements are not feasible.

Accuracy of a New Pulse Oximetry in Detection of Arterial Oxygen Saturation and Heart Rate Measurements: The SOMBRERO Study.

Early diagnosis and continuous monitoring of respiratory failure (RF) in the course of the most prevalent chronic cardio-vascular (CVD) and respiratory diseases (CRD) are a clinical, unresolved problem because wearable, non-invasive, and user-friendly medical devices, which could grant reliable measures of the oxygen saturation (SpO2) and heart rate (HR) in real-life during daily activities are still lacking. In this study, we investigated the agreement between a new medical wrist-worn device (BrOxy M) and a reference, medical pulseoximeter (Nellcor PM 1000N). Twelve healthy volunteers (aged 20–51 years, 84% males, 33% with black skin, obtaining, during the controlled hypoxia test, the simultaneous registration of 219 data pairs, homogeneously deployed in the levels of Sat.O2 97%, 92%, 87%, 82% [ISO 80601-2-61:2017 standard (paragraph EE.3)]) were included. The paired T test 0 and the Bland-Altman plot were performed to assess bias and accuracy. SpO2 and HR readings by the two devices resulted significantly correlated (r = 0.91 and 0.96, p < 0.001, respectively). Analyses excluded the presence of proportional bias. For SpO2, the mean bias was −0.18% and the accuracy (ARMS) was 2.7%. For HR the mean bias was 0.25 bpm and the ARMS3.7 bpm. The sensitivity to detect SpO2 ≤ 94% was 94.4%. The agreement between BrOxy M and the reference pulse oximeter was “substantial” (for SpO2 cut-off 94% and 90%, k = 0.79 and k = 0.80, respectively). We conclude that BrOxy M demonstrated accuracy, reliability and consistency in measuring SpO2 and HR, being fully comparable with a reference medical pulseoxymeter, with no adverse effects. As a wearable device, Broxy M can measure continually SpO2 and HR in everyday life, helping in detecting and following up CVD and CRD subjects.

Machine Learning Models and Videos of Facial Regions for Estimating Heart Rate: A Review on Patents, Datasets, and Literature

Estimating heart rate is important for monitoring users in various situations. Estimates based on facial videos are increasingly being researched because they allow the monitoring of cardiac information in a non-invasive way and because the devices are simpler, as they require only cameras that capture the user’s face. From these videos of the user’s face, machine learning can estimate heart rate. This study investigates the benefits and challenges of using machine learning models to estimate heart rate from facial videos through patents, datasets, and article review. We have searched the Derwent Innovation, IEEE Xplore, Scopus, and Web of Science knowledge bases and identified seven patent filings, eleven datasets, and twenty articles on heart rate, photoplethysmography, or electrocardiogram data. In terms of patents, we note the advantages of inventions related to heart rate estimation, as described by the authors. In terms of datasets, we have discovered that most of them are for academic purposes and with different signs and annotations that allow coverage for subjects other than heartbeat estimation. In terms of articles, we have discovered techniques, such as extracting regions of interest for heart rate reading and using video magnification for small motion extraction, and models, such as EVM-CNN and VGG-16, that extract the observed individual’s heart rate, the best regions of interest for signal extraction, and ways to process them.

Development of Low-Cost and Portable Pulse Oximeter Device with Improved Accuracy and Accessibility

PurposeIn a clinical setting, blood oxygen saturation is one of the most important vital sign indicators. A pulse oximeter is a device that measures the blood oxygen saturation and pulse rate of patients with various disorders. However, due to ethical concerns, commercially available pulse oximeters are limited in terms of calibration on critically sick patients, resulting in a significant error rate for measurement in the critical oxygen saturation range. The device’s accessibility in developing countries’ healthcare settings is also limited due to portability, cost implications, and a lack of recognized need. The purpose of this study was to develop a reliable, low-cost, and portable pulse oximeter device with improved accuracy in the critical oxygen saturation range.MethodsThe proposed device measures oxygen saturation and heart rate using the reflectance approach. The rechargeable battery and power supply from the smartphone were taken into account, and the calibration in critical oxygen saturation values was performed using Prosim 8 vital sign simulator, and by comparing with a standard pulse oximeter device over fifteen iterations.ResultsThe device’s prototype was successfully developed and tested. Oxygen saturation and heart rate readings were both accurate to 97.74% and 97.37%, respectively, compared with the simulator, and an accuracy of 98.54% for the measurement of blood oxygen saturation was obtained compared with the standard device.ConclusionThe accuracy of oxygen measurement attained in this study is significant for measuring oxygen saturation for patients in critical care, anesthesia, pre-operative and post-operative surgery, and COVID-19 patients. The advancements made in this research have the potential to increase the accessibility of pulse oximeter in resource limited areas.