Heart Rate Detection Research Articles

Intelligent Application to Detect Heart Disease Issues and Treatment

Intelligent Application to Detect Heart Disease Issues and Treatment. It might have happened so many times that you or someone yours need doctors help immediately, but they are not available due to some reason. Intelligent application for detection heart rate disease is an end user support provide an online/offline consultation. Here, we propose an application that allows users to get instant guidance on their heart disease through an intelligent system. The application is fed with various details and the heart disease associated with those details. The application allows user to share their heart related issues. It then processes user specific details to check for various illness that could be associated with it. Here we use some intelligent data mining techniques to guess the most accurate illness that could be associated with patient’s details. Based on result, the can contact doctor accordingly for further treatment. The system allows user to view doctor’s details too. The system can be used for free heart disease consulting online or offline.

Interpretation of Telemetry Among Patients With a Left Ventricular Assist Device.

Scenario: This rhythm strip was obtained on a 45-year-old woman with a medical history of coronary artery disease, prior coronary artery bypass graft, heart failure with reduced ejection fraction, and an implanted left ventricular assist device (LVAD). She arrived at the emergency department with fatigue, weakness, nausea, and vomiting. Her LVAD was operating at a 4.3 L/min flow rate, 5600 rotations per minute (rpm) speed, and 4.2 W of power. Assessment of her vital signs in the emergency department showed low-grade fever, tachypnea (respirations, 20/min), and desaturation (oxygen saturation by pulse oximetry, 92%) on room air. She tested positive for COVID-19 and was admitted to the cardiac LVAD floor. The nurse was concerned about an asystole alarm from the bedside monitor.Sinus rhythm at a heart rate of 69/min, rS morphology in lead II most likely due to left axis deviation, and low QRS wave amplitude. Additionally, an electrical baseline artifact related to LVAD oscillations is apparent in both leads.In patients with an LVAD, the electrocardiogram (ECG) provides essential information such as rate and rhythm; however, excessive electrical artifact and low QRS amplitude impair more advanced ECG interpretation and impact the computerized algorithms, leading to many telemetry alarms.The most pronounced ECG change associated with LVAD implantation is electrical artifact. The electrical artifact on the ECG, seen as many short bold spikes, corresponds to the rotational speeds of the LVAD motor: the faster the motor is rotating, the higher the frequency of the electrical artifact. Commercially available LVADs run at different rotational speeds in 3 ranges: 2400-3200 rpm, 5000-6000 rpm, and 8800-10 000 rpm, corresponding to oscillating frequencies of 40-53.3 Hz, 83.3-100 Hz, and 146.7-166.7 Hz, respectively. The ECG filters are imperfect and are not necessarily designed for noise caused by an LVAD. Most ECG telemetry systems have a filter between 0.05 and 40 Hz, as seen on the telemetry strip.This ECG shows low-amplitude QRS complexes in both leads. QRS complexes with low amplitudes occur after LVAD implantation owing to surgical removal of the myocardium to place the motor, as well as ischemia and inflammation from the procedure. The removal of myocardium also alters myocyte depolarization, which may explain the negative QRS complex in lead II suggestive of a left electrical axis deviation but requiring a 12-lead ECG to confirm.In this case, a combination of electrical artifacts from the LVAD motor and low QRS amplitudes is responsible for the asystole alarm. Modern telemetry systems use computerized algorithms to determine heart rate and rhythm on the basis of the detection of the QRS complex and the R-R interval between successive QRS complexes. Common computerized algorithms for heart rate detection use strict QRS amplitude criteria (ie, unidirectional QRS >5 mm in >2 ECG leads). These algorithms work only on whichever leads are being monitored on the central telemetry monitoring system, in this case, leads II and V1. If the amplitude of the QRS complex is too low to be detected or is obscured by electrical artifact, the algorithms fail to detect the rate and rhythm, subsequently causing the asystole alarm. Although more advanced filters are necessary to filter out the electrical artifact caused by the LVAD motor, repositioning the ECG leads to areas with more myocardium not removed during LVAD implantation will also increase QRS complex amplitude.The most important nursing action with an asystole alarm is to assess the patient; this patient was alert and oriented with good perfusion according to Doppler pressure. Remember, a pulse may not be palpable in LVAD patients. As all potentially emergent findings had been ruled out, the underlying causes for the false asystole alarms could be addressed. To reduce the burden of unnecessary asystole alarms, nurses can change the leads being monitored to see if one lead has less artifact and greater QRS amplitude. Nurses can also move the limb electrodes more centrally toward the heart to increase QRS amplitude and should avoid placing the electrodes over bony prominences or edematous areas, which are associated with reduced QRS amplitude.Current American Heart Association practice standards for in-hospital ECG monitoring provide a class I recommendation for continuous bedside ECG monitoring for patients with an LVAD. However, LVADs are associated with a substantial number of false alarms, and research has shown that few patients have truly actionable alarms. Further research and refinement of clinical standards are necessary.

SMART WRIST PULSE OXIMETER

In the present day we live in, a catastrophic virus COVID-19 has drastically changed the day to day living of a human being. The virus causes hypoxemia (shortness of breath), sometimes even severe cases. Hypoxemia is caused due to low oxygen saturation (SpO2) levels and in order to monitor SpO2 levels we utilize the method of Pulse Oximetry. It has played a major role in monitoring oxygen levels in a continuous and accurate manner. Patients who are diagnosed during the early stages with the virus are able to monitor their SpO2 levels at home and take the prescribed medicines. This reduced the need for hospital beds and chaos during the pandemic as patients were able to self-isolate and monitor themselves. The principle that Oximetry is contingent on is light reflectance. The fingertip model is the most common technique used to display the blood oxygenation level. However, the finger model is not as comfortable and does not promote continuous monitoring of SpO2 levels. Factors such as nail polish can play a role in the accuracy of the reading. The proposed design is a non-invasive medical device that can measure the oxygen saturation level in a person’s blood. Wrist wearing is preferrable to finger models as it is a comfortable site for measuring than that of the latter, therefore enabling continuous monitoring of oxygen saturation level. Most devices in application today are inaccurate and used for non-clinical use. Therefore, it is aimed to achieve better accuracy by avoiding readings that are influenced by factors such as motion artifacts by utilizing sensors that are appropriate through an accelerometer and gyroscope. The sensors have been utilized to its maximum potential as the model also detects heart rate levels. Providing device connectivity to the proposed wrist pulse oximeter through a Wi-Fi module has advanced its functionality by transmitting notifications that alert an individual with the levels of oxygen saturation, fall detection and heart rate levels.

Design of a web laboratory interface for ECG signal analysis using MATLAB builder NE

Abstract An electrocardiogram (ECG) is a noninvasive test, determining any defect in the heart rate or rhythm or changes in the shape of the QRS complex is very significant to detect cardiac arrhythmia. In this study, novel web-ECG simulation tools were proposed using MATLAB Builder NE with WebFigure and ASP.NET platform. The proposed web-ECG simulation tools consisted of two components. First, involved the analyses of normal real ECG signals by calculating the P, Q, R, S, and T values and detecting heart rate, while the second part related to extracting the futures of several types of abnormality real ECG. For calculating the PQRST values, simple and new mathematical equations are proposed in the current study using MATLAB. The Web ECG is capable to plot normal ECG signals and five arrhythmia cases, so the users are able to calculate PQRST easily using the proposed simple method. ECG simulation tools have been tested for validity and educational contributions with 62 undergraduate and graduate students at the Al-Nahrain University-Biomedical Engineering Department, Iraq. The proposed ECG simulation tools have been designed for academic learning to be run easily by a student using only any web browsers without the need for installing MATLAB or any extra programs. The proposed tools could provide a laboratory course for ECG signal analysis using a few buttons, as well as increase and develop the educational skills of students and researchers.

Research on Heartbeat Detection Method of Ballistocardiogram Based on Bidirectional Long Short-term Memory Network

In order to improve the accuracy and generalization ability of extracting successive heartbeat cycle based on ballistocardiogram (BCG), this paper proposed a general method for detecting J peak of BCG signals by using bidirectional long short-term memory network. First, the clustering method is used to establish the sequence feature set of BCG signals in different sleeping positions, and the data set used contains a variety of different forms of BCG signals. Then, according to the Bidirectional LSTM (BiLSTM) many-to-many recognition model, the number of J peaks in the output sequence is counted to achieve real-time heartbeat detection. The results showed that the deviation rate of BCG heart rate detection was 0.27%, and there was no significant difference between BCG and ECG in the detection of heartbeat interval. Compared with other methods, this method has higher robustness and accuracy in detection effect, which provides a new idea for realizing high-precision unconstrained heartbeat detection.

A comparative study of common steps in video-based remote heart rate detection methods

Video-based remote heart rate detection is a promising technology that can offer convenient and low-cost heart rate monitoring within, but not limited to, the clinical environment, especially when attaching electrodes or pulse oximeters on a person is not possible or convenient. In this work, we examined common steps used in video-based remote heart rate detection algorithms, in order to evaluate their effect on the overall performance of the remote heart rate detection pipeline. Various parameters of the examined methods were evaluated on three public and one proprietary dataset in order to establish a video-based remote heart rate detection pipeline that provides the most balanced performance across various diverse datasets. The experimental evaluation demonstrated the effect and contribution of each step and parameter set on the estimation of the heart rate, resulting in an optimal configuration that achieved a best RMSE value of 9.51.

Implementation System of Health Care Kiosk for Detecting Cholesterol Disease, Uric Acid, Obesity and Hypoxia

The development of technological advances in the health sector in the last decades has grown very rapidly. Currently, most people do not receive routine medical check-ups because of the long lines of patients and the expensive rates they must pay to see a specialist doctor. This causes many people to ignore the importance of routine health checks as recommended by the National Health Agency. The purpose of this research is to make a device that can perform routine checks independently at home, using an Arduino microcontroller for checking cholesterol, uric acid, obesity, and hypoxia. This tool has several sensors, namely Ultrasonic & Load Cell sensors to measure weight and height, which are used to detect obesity through the BMI table. In addition, there is a Pulse and Oxygen in Blood Sensor (SPO2) sensor to detect heart rate and oxygen saturation to detect hypoxia using the fuzzy logic method. Cholesterol and uric acid examination using the Electrode Based biosensor method with a digital detection device (amperometric biosensor). Testing the Tsukamoto fuzzy logic method system obtained a data accuracy value of 100%, following the rules set for classifying hypoxic diseases. The trial phase was carried out as many as 10 trials, where 90% of patients did not experience hypoxia, and 10% had mild hypoxia. The results of testing the BMI table method system for obesity obtained a data accuracy value of 100% according to the calculation of the BMI calculator. In phase 10 trials, 30% of patients were lean, 50% obese, and 20% obese. The system test results use a range of values, each with a data accuracy value of 100% according to the classification of cholesterol and uric acid levels. Ten trials showed that 70% of patients were in normal condition, 20% of patients with low cholesterol, and 10% of patients were in high limits. As for gout, 70% of patients are in normal condition, and 30% of patients are in high uric acid condition.

Signal-to-Noise Ratio Enhancement in Cardiac Pulse Measurements Using Multitap CMOS Image Sensors With In-Pixel Temporal Redundant Samplings

Insufficient signal-to-noise ratio (SNR) limits the quality of cardiac pulses measured by multitap CMOS image sensors (CISs). We present an in-pixel temporal redundant samplings (TRS) method for enhancing the SNR through sampling the charges originated by one individual optical scene into the multiple storage taps in turn with the identical time window, enabling magnification of the image signal in shot noise domain. Modeling indicates that the linear SNR increases with a factor square root of TRS sampling number, which is also verified by characterization results utilizing a four-tap CIS. Application results show that the high-frequency (HF) noise components observed in the measured cardiac pulses can be attenuated by 67.9%, 48%, and 53.6% with heart rate detection accuracies up to 99.7%, 99.3%, and 98.7% by applying TRS modes under given conditions of stable ambient, background light (BGL) variation, and motion disturbance, respectively. Moreover, the proposed method is as well foreseeable to be extended to other multitap-involved imaging applications.

The Effect of Exercise Training on the Detection of Heart Rate and Body Temperature Sensors in Adolescents

The aim of this study is to study the effect of exercise training on heart rate and body temperature sensor detection in adolescents. For the methods of logical analysis, test, and mathematical statistics, this paper takes 60 students aged 13-15 in the experimental middle school as the research subjects to explore the characteristics of heart rate changes of middle school students under different high-intensity intermittent exercise schemes. Then, it analyzes the characteristics of heart rate change in exercise center and heart rate change in high-intensity intermittent exercise. The experimental results show that the high-intensity intermittent exercise of adolescents aged 13-15 presents the stage of rapid recovery and buffer recovery. Whether in the quiet heart rate buffer stage or the rapid heart rate increase stage, as well as the “extreme heart rate maintenance stage” and heart rate recovery stage, the heart rate change point of 15-year-old adolescents is 1-3 seconds later than that of 13-year-old and 14-year-old adolescents. In addition, in the heart rate maintenance stage of 15-year-old adolescents, the heart rate fluctuates greatly. The rapid recovery stage of boys is 1 minute, and the heart rate can reach the quiet heart rate after 4-5 minutes. The rapid recovery stage of girls is 1.5 minutes, and the heart rate can reach the quiet heart rate after 4-5 minutes. The older the age of high-intensity intermittent training of adolescents aged 13-15, the longer the rapid rise stage of heart rate change, and there was no significant change in quiet heart rate buffer stage and body temperature.

An accelerometer-derived ballistocardiogram method for detecting heart rate in free-ranging marine mammals.

ABSTRACTPhysio-logging methods, which use animal-borne devices to record physiological variables, are entering a new era driven by advances in sensor development. However, existing datasets collected with traditional bio-loggers, such as accelerometers, still contain untapped eco-physiological information. Here, we present a computational method for extracting heart rate from high-resolution accelerometer data using a ballistocardiogram. We validated our method with simultaneous accelerometer–electrocardiogram tag deployments in a controlled setting on a killer whale (Orcinus orca) and demonstrate the predictions correspond with previously observed cardiovascular patterns in a blue whale (Balaenoptera musculus), including the magnitude of apneic bradycardia and increase in heart rate prior to and during ascent. Our ballistocardiogram method may be applied to mine heart rates from previously collected accelerometery data and expand our understanding of comparative cardiovascular physiology.

HEART RATE DETECTION OF STRESS LEVELS FOR PREGNANT WOMEN

During pregnancy, there are changes because the fetus begins to grow and develop in the pregnant woman's stomach. Physiology greatly influences its development, especially in hormonal and metabolic changes that affect the psychological stress level of pregnant women. This study aims to determine the initial action to detect heart rate by looking at stress levels in pregnant women. The results of stress measurements are not normal when the heart rate is less than 60 bpm and more than 100 bpm, while in conditions of more than 60 bpm and less than 100 bpm, the results obtained are normal conditions. This study uses a hardware programming approach with the stages: Project Planning, Research, Component Testing, Mechanical System Design, Functional Test, Functional Test, Overall System Functional Test, System Optimization. The results show that this tool has worked well in monitoring heart rate when stressed in real-time using a pulse sensor displayed via telegram notifications in the form of total data. Still, because it is only in the form of notifications, there is no storage in the form of a database.

Sistem Sensor Detak Jantung Guna Mendukung Kebugaran Crew Saat Melaksanakan Dinas Jaga Mesin

The 2010 Manila Amendment Standard of Training Certification and Watchkeeping (STCW) regulation is to create and develop a system that can support the fitness of duty officers on duty. The officer's fitness is determined by the value of the heart rate at the start of watch duty. For that we need a system that can measure the heart rate quickly and precisely. This system must work effectively and accurately inform each officer's measurements. So this research was carried out with the aim of building an effective heart rate measurement. This system is supported by the Arduino Nano Microcontroller and an alarm system that provides information on the fitness of the officers. The method used is Research and Development which refers to ADDIE (Analysis, Design, Development, Implementation, and Evaluation). The result of this research is a heart rate measuring product that works very effectively. The required input consists of a grove-ear clip heart rate sensor as a heart rate detector in the form of a pulse signal and a vibrating DC motor with a buzzer as an alarm that generates a shock for the user of the device. The indications for this tool are using Bradycardia, Normal and Tachycardia heart conditions. So that this research is very much needed in supporting the testing of the fitness of tasks in carrying out the machine guard service properly and guaranteed.

A new principle of pulse detection based on terahertz wave plethysmography

This study presents findings in the terahertz (THz) frequency spectrum for non-contact cardiac sensing applications. Cardiac pulse information is simultaneously extracted using THz waves based on the established principles in electronics and optics. The first fundamental principle is micro-Doppler motion effect. This motion based method, primarily using coherent phase information from the radar receiver, has been widely exploited in microwave frequency bands and has recently found popularity in millimeter waves (mmWave) for breathe rate and heart rate detection. The second fundamental principle is reflectance based optical measurement using infrared or visible light. The variation in the light reflection is proportional to the volumetric change of the heart, often referred as photoplethysmography (PPG). Herein, we introduce the concept of terahertz-wave-plethysmography (TPG), which detects blood volume changes in the upper dermis tissue layer by measuring the reflectance of THz waves, similar to the existing remote PPG (rPPG) principle. The TPG principle is justified by scientific deduction, electromagnetic wave simulations and carefully designed experimental demonstrations. Additionally, pulse measurements from various peripheral body parts of interest (BOI), palm, inner elbow, temple, fingertip and forehead, are demonstrated using a wideband THz sensing system developed by the Terahertz Electronics Lab at Arizona State University, Tempe. Among the BOIs under test, it is found that the measurements from forehead BOI gives the best accuracy with mean heart rate (HR) estimation error 1.51 beats per minute (BPM) and standard deviation 1.08 BPM. The results validate the feasibility of TPG for direct pulse monitoring. A comparative study on pulse sensitivity is conducted between TPG and rPPG. The results indicate that the TPG contains more pulsatile information from the forehead BOI than that in the rPPG signals in regular office lighting condition and thus generate better heart rate estimation statistic in the form of empirical cumulative distribution function of HR estimation error. Last but not least, TPG penetrability test for covered skin is demonstrated using two types of garment materials commonly used in daily life.

Optimization of adaptive filter control parameters for non-invasive fetal electrocardiogram extraction.

This paper is focused on the design, implementation and verification of a novel method for the optimization of the control parameters of different hybrid systems used for non-invasive fetal electrocardiogram (fECG) extraction. The tested hybrid systems consist of two different blocks, first for maternal component estimation and second, so-called adaptive block, for maternal component suppression by means of an adaptive algorithm (AA). Herein, we tested and optimized four different AAs: Adaptive Linear Neuron (ADALINE), Standard Least Mean Squares (LMS), Sign-Error LMS, Standard Recursive Least Squares (RLS), and Fast Transversal Filter (FTF). The main criterion for optimal parameter selection was the F1 parameter. We conducted experiments using real signals from publicly available databases and those acquired by our own measurements. Our optimization method enabled us to find the corresponding optimal settings for individual adaptive block of all tested hybrid systems which improves achieved results. These improvements in turn could lead to a more accurate fetal heart rate monitoring and detection of fetal hypoxia. Consequently, our approach could offer the potential to be used in clinical practice to find optimal adaptive filter settings for extracting high quality fetal ECG signals for further processing and analysis, opening new diagnostic possibilities of non-invasive fetal electrocardiography.

Ubiquitous Electronic Health System - Rancang Bangun Smart Mouse dan Smart Watch Pengukur Denyut Jantung dan Suhu Tubuh

The purpose of this research is to design a Ubiquitous Electronic Health System to monitor health during activities. The Ubiquitous Electronic Health System is a health monitoring system and facilitator of human health support devices that are applied to devices commonly used in everyday life such as mirrors, chairs, computer mice, watches, mobile phones, and others by utilizing the Photoplethysmograph method. The equipment developed in this study consisted of a computer mouse and a watch that was added with a photodiode, infrared, and a DS18b20 sensor with functionality as a heart rate detector and body temperature measurement. into the body but the measurement or screening action is carried out with the help of sensors attached to the skin, measurements are carried out in real-time when the equipment is used daily, the measurement results can be seen on the mobile phone screen and desktop applications, the data obtained from the measurement results can then be sent to the server to be stored as a user's medical record which can be used by the user to carry out further examinations to the doctor. The parameters that are the points in this study are the number of heart beats per minute and the measurement of body temperature, these two parameters are tested by comparing the results of tests carried out by tools designed with oximeters and thermometers. The test results from the Ubiquitous Electronic Health System tool provide an accuracy of up to 98% for measuring heart rate and 85% for measuring body temperature. Design and schematic have been shown in this study.

Detection of Oxygen Levels (SpO2) and Heart Rate Using a Pulse Oximeter for Classification of Hypoxemia Based on Fuzzy Logic

This study made the digital system to perform screening (early prediction) of Hypoxemia using MAX30102 sensor with the fuzzy value from SpO2 level and heart rate. This research also uses the Internet of Things (IoT) system to gather data from devices to the cloud. Hypoxemia is a lack of oxygen in the blood flowing in the body. Hypoxemia conditions in the body due to lack of oxygen levels in the blood will cause an increased heart rate. Hypoxemia conditions that are not immediately recognized cause damage to cells, tissues, and organs. Hypoxemia is an essential condition because information about oxygen levels in the blood is closely related to health conditions. In this project, researchers built a Hypoxemia early detection system. From the research results, it is found that the accuracy rate of the system to detect hypoxemia is 80%, with 60% sensitivity and 100% specificity. Based on the experiment, this research is able to help screening detection (early prediction) of Hypoxemia.

Performance Evaluation of a Smart Bed Technology against Polysomnography

The Sleep Number smart bed uses embedded ballistocardiography, together with network connectivity, signal processing, and machine learning, to detect heart rate (HR), breathing rate (BR), and sleep vs. wake states. This study evaluated the performance of the smart bed relative to polysomnography (PSG) in estimating epoch-by-epoch HR, BR, sleep vs. wake, mean overnight HR and BR, and summary sleep variables. Forty-five participants (aged 22–64 years; 55% women) slept one night on the smart bed with standard PSG. Smart bed data were compared to PSG by Bland–Altman analysis and Pearson correlation for epoch-by-epoch HR and epoch-by-epoch BR. Agreement in sleep vs. wake classification was quantified using Cohen’s kappa, ROC analysis, sensitivity, specificity, accuracy, and precision. Epoch-by-epoch HR and BR were highly correlated with PSG (HR: r = 0.81, |bias| = 0.23 beats/min; BR: r = 0.71, |bias| = 0.08 breaths/min), as were estimations of mean overnight HR and BR (HR: r = 0.94, |bias| = 0.15 beats/min; BR: r = 0.96, |bias| = 0.09 breaths/min). Calculated agreement for sleep vs. wake detection included kappa (prevalence and bias-adjusted) = 0.74 ± 0.11, AUC = 0.86, sensitivity = 0.94 ± 0.05, specificity = 0.48 ± 0.18, accuracy = 0.86 ± 0.11, and precision = 0.90 ± 0.06. For all-night summary variables, agreement was moderate to strong. Overall, the findings suggest that the Sleep Number smart bed may provide reliable metrics to unobtrusively characterize human sleep under real life-conditions.

A Real‐Time Heart Rate Detection Algorithm Based on Peripheral Electrical Bioimpedance

Impedance cardiography (ICG) and peripheral bioimpedance may be useful for monitoring several cardiovascular parameters such as cardiac output, stroke volume, blood pressure and heart rate. It is a noninvasive and low‐cost method and could be useful for diagnosis and treatment in different clinical situations. This study involved 100 volunteers and their age ranging from 18 to 26 years. The acquired bioimpedance signal was pre‐processed and used to estimate the heart rate. Thus, heart rates of each subject were calculated and then compared with actual measurement from FUZZY model MP3 digital blood pressure monitor. The results showed high precision with a 1.38 mean error a high sensitivity of 99.81% and a positive predictivity value of 99.63%, respectively. Compared with six other methods selected from the literature review and which are initially dedicated to ECG signals, the proposed method has been found to be more efficient and more precise with an error in determining the percentile HR = 1.78%. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Heart rate prediction from facial video with masks using eye location and corrected by convolutional neural networks

Remote photoplethysmography (rPPG), which aims at measuring heart activities without any contact, has great potential in many applications. The emergence of novel coronavirus pneumonia COVID-19 has attracted worldwide attentions. Contact photoplethysmography (cPPG) methods need to contact the detection equipment with the patient, which may accelerate the spread of the epidemic. In the future, the non-contact heart rate detection will be an urgent need. However, existing heart rate measuring methods from facial videos are vulnerable to the less-constrained scenarios (e.g., with head movement and wearing a mask). In this paper, we proposed a method of heart rate detection based on eye location of region of interest (ROI) to solve the problem of missing information when wearing masks. Besides, a model to filter outliers based on residual network was conceived first by us and the better heart rate measurement accuracy was generated. To validate our method, we also created a mask dataset. The results demonstrated that after using our method for correcting the heart rate (HR) value measured with the traditional method, the accuracy reaches 4.65 bpm, which is 0.42 bpm higher than that without correction.

Skin-inspired flexible and high-performance MXene@polydimethylsiloxane piezoresistive pressure sensor for human motion detection

In recent years, flexible high-performance piezoresistive pressure sensors have attracted considerable attention for the important application potential in the emerging fields of smart robots, wearable electronics and electronic skin. Herein, inspired by human skin, a new strategy was proposed for the fabrication of a double-layer piezoresistive pressure sensor with wide sensing range and high sensitivity. It was based on the utilization of sandpaper as template and MXene for the constructions of micro-protrusion rough surface on polydimethylsiloxane film and electrically conductive pathways, respectively. The prepared sensor demonstrated high sensitivity of 2.6 kPa−1 in wide linear range of 0–30 kPa, fast response/recovery time of 40/40 ms and excellent repeatability. Importantly, the sensor was successfully applied for the real-time detection of radial artery heart rate, limb movement, handwriting and vocal cord vocalization. Moreover, the integrated device by the sensors had the capability of identifying and visualizing spatial pressure distribution. The findings conceivably stand out a new methodology to prepare flexible high-performance piezoresistive pressure sensors for wearable electronics, human-computer interaction, intelligent robots and health monitoring.