Electrocardiogram Measurement System Research Articles

2D metal-organic frameworks for ultraflexible electrochemical transistors with high transconductance and fast response speeds.

Electrochemical transistors (ECTs) have shown broad applications in bioelectronics and neuromorphic devices due to their high transconductance, low working voltage, and versatile device design. To further improve the device performance, semiconductor materials with both high carrier mobilities and large capacitances in electrolytes are needed. Here, we demonstrate ECTs based on highly oriented two-dimensional conjugated metal-organic frameworks (2D c-MOFs). The ion-conductive vertical nanopores formed within the 2D c-MOFs films lead to the most convenient ion transfer in the bulk and high volumetric capacitance, endowing the devices with fast speeds and ultrahigh transconductance. Ultraflexible device arrays are successfully used for wearable on-skin recording of electrocardiogram (ECG) signals along different directions, which can provide various waveforms comparable with those of multilead ECG measurement systems for monitoring heart conditions. These results indicate that 2D c-MOFs are excellent semiconductor materials for high-performance ECTs with promising applications in flexible and wearable electronics.

ECG Measurement System for Vehicle Implementation and Heart Disease Classification Using Machine Learning

The 12-lead electrocardiogram (ECG) method can diagnose more cardiovascular disease than the single-lead method, but it is difficult to use in daily life because numerous electrodes must be attached to the body. As an aging society approaches, electrocardiography is expanding its use in daily life, even to the heart disease monitoring system for passengers in vehicles. This study proposes a single-lead ECG measurement system implemented in the steering wheel of the vehicle and a machine learning model to classify the driver’s heart health status. For the ECG measurement system, an algorithm to obtain stable ECG signals is proposed along with the measurement hardware. It uses the range and interval of the ECG signal to determine stability under noisy conditions caused by vehicle vibration and the driver movement. To classify four classes of heart diseases (normal, atrial fibrillation, other rhythms, noise), a two-stage machine learning structure is proposed. To train the machine learning models with an optimal feature subset, 188 features were extracted from the single-lead ECG dataset, and a sequential wrapper-type feature selection was conducted. As a result, when the naïve Bayes model using ten features was located in the first step and the support vector machine using 13 features in the second step, the proposed two-stage classification structure returned the best score <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</i> 1 <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>NAO</i></sub> = 0.7898 and real-time classification performances (0.86 seconds on average).

Development and Optimization of Silicon-Dioxide-Coated Capacitive Electrode for Ambulatory ECG Measurement System.

This paper presents a silicon-dioxide-coated capacitive electrode system for an ambulatory electrocardiogram (ECG). The electrode was coated with a nano-leveled (287 nm) silicon dioxide layer which has a very high resistance of over 200 MΩ. Due to this high resistance, the electrode can be defined as only a capacitor without a resistive characteristic. This distinct capacitive characteristic of the electrode brings a simplified circuit analysis to achieve the development of a high-quality ambulatory ECG system. The 240 um thickness electrode was composed of a stainless-steel sheet layer for sensing, a polyimide electrical insulation layer, and a copper sheet connected with the ground to block any electrical noises generated from the back side of the structure. Six different diameter electrodes were prepared to optimize ECG signals in ambulatory environment, such as the amplitude of the QRS complex, amplitude of electromagnetic interference (EMI), and baseline wandering of the ECG signals. By combining the experimental results, optimal ambulatory ECG signals were obtained with electrodes that have a diameter from 1 to 3 cm. Moreover, we achieved high-quality ECG signals in a sweating simulation environment with 2 cm electrodes.

Respiratory Rate Estimation Using U-Net-Based Cascaded Framework From Electrocardiogram and Seismocardiogram Signals.

At-home monitoring of respiration is of critical urgency especially in the era of the global pandemic due to COVID-19. Electrocardiogram (ECG) and seismocardiogram (SCG) signals-measured in less cumbersome contact form factors than the conventional sealed mask that measures respiratory air flow-are promising solutions for respiratory monitoring. In particular, respiratory rates (RR) can be estimated from ECG-derived respiratory (EDR) and SCG-derived respiratory (SDR) signals. Yet, non-respiratory artifacts might still be present in these surrogates of respiratory signals, hindering the accuracy of the RRs estimated. In this paper, we propose a novel U-Net-based cascaded framework to address this problem. The EDR and SDR signals were transformed to the spectro-temporal domain and subsequently denoised by a 2D U-Net to reduce the non-respiratory artifacts. We have shown that the U-Net that fused an EDR input and an SDR input achieved a low mean absolute error of 0.82 breaths per minute (bpm) and a coefficient of determination (R2) of 0.89 using data collected from our chest-worn wearable patch. We also qualitatively provided insights on the complementariness between EDR and SDR signals and demonstrated the generalizability of the proposed framework. ECG and SCG collected from a chest-worn wearable patch can complement each other and yield reliable RR estimation using the proposed cascaded framework. We anticipate that convenient and comfortable ECG and SCG measurement systems can be augmented with this framework to facilitate pervasive and accurate RR measurement.

Novel Stable Capacitive Electrocardiogram Measurement System.

This study presents a noncontact electrocardiogram (ECG) measurement system to replace conventional ECG electrode pads during ECG measurement. The proposed noncontact electrode design comprises a surface guard ring, the optimal input resistance, a ground guard ring, and an optimal voltage divider feedback. The surface and ground guard rings are used to reduce environmental noise. The optimal input resistor mitigates distortion caused by the input bias current, and the optimal voltage divider feedback increases the gain. Simulated gain analysis was subsequently performed to determine the most suitable parameters for the design, and the system was combined with a capacitive driven right leg circuit to reduce common-mode interference. The present study simulated actual environments in which interference is present in capacitive ECG signal measurement. Both in the case of environmental interference and motion artifact interference, relative to capacitive ECG electrodes, the proposed electrodes measured ECG signals with greater stability. In terms of R–R intervals, the measured ECG signals exhibited a 98.6% similarity to ECGs measured using contact ECG systems. The proposed noncontact ECG measurement system based on capacitive sensing is applicable for use in everyday life.

Capacitively Coupled Electrode Array Sensors for Body Posture and ECG Measurement During Sleep

Holter electrocardiographs, which are commonly used for long-term electrocardiographic measurements, are not necessarily suitable for long-term measurements during sleep because the electrodes are directly attached to the skin, causing discomfort and constraint feelings. To handle this problem, electrocardiogram measurement using capacitively coupled electrodes, which do not require direct skin contact, could be an alternative. However, this method requires precise positioning of the electrodes on specific parts of the body, which makes it difficult to work robustly in response to physical body differences and postural variations such as turning over. Therefore, the authors have been working on the realization of a novel electrocardiogram measurement system using capacitively coupled electrodes arranged in an array. The major feature of this system is the ability to measure both body posture and electrocardiogram with common electrodes arranged in an array, and by selecting the most effective electrodes based on the measured posture, it can make electrocardiogram measurements corresponding to the posture changes. In this paper, as the core of the system, a new sensor that can measure both body posture and electrocardiogram with common arrayed electrodes has been designed and implemented. From the experimental results, it was confirmed that the subject's posture on the electrode array could be obtained from the distribution of capacitance, and also the electrocardiogram of the subject could be obtained with the same electrodes as well.

Facile Fabrication of Flexible Electrodes and Immobilization of Silver Nanoparticles on Nanoscale Silicate Platelets to Form Highly Conductive Nanohybrid Films for Wearable Electronic Devices.

This study investigated films with remarkably high electrical conductivity after they were easily prepared from organic/inorganic nanohybrid solutions containing an organic polymeric dispersant and two-dimensional nanoscale silicate platelets as the inorganic stabilizer dispersed with silver nanoparticles. Transmission electron microscopy shows that the production of silver nanoparticles synthesized by the in situ chemical reduction of AgNO3 in an aqueous solution by N,N-dimethylformamide results in an average silver nanoparticle diameter of circa 20 nm. Thin films of silver nanoparticles were prepared on a 1-μm-thick film with a low sheet resistance of 8.24 × 10−4 Ω/sq, achieved through the surface migration of silver nanoparticles and prepared by sintering at 300 °C to form an interconnected network. This was achieved with a silver nanoparticle content of 5 wt%, using nanoscale silicate platelets/polyoxyethylene-segmented polyimide/AgNO3 at a weight ratio of 1:10:35. During sintering, the color of the hybrid film changed from gold to milky white, suggesting the migration of silver nanoparticles and the formation of an interconnected network. The results show promise for the fabrication of novel silver-based electrocardiogram electrodes and a flexible wireless electrocardiogram measurement system for wearable electronics.

A Novel 12-Lead Electrocardiographic System for Home Use: Development and Usability Testing.

BackgroundCardiovascular diseases (CVD) are the leading cause of morbidity and mortality worldwide. Early diagnosis is of pivotal importance for patients with cardiac arrhythmias and ischemia to minimize the consequences like strokes and myocardial infarctions. The chance of capturing signals of arrhythmias or ischemia is substantially high when a 12-lead electrocardiogram (ECG) can be recorded at the moment when a patient experiences the symptoms. However, until now, available diagnostic systems (Holter monitors and other wearable ECG sensors) have not enabled patients to record a reliable 12-lead ECG at home.ObjectiveThe objective of this project was to develop a user-friendly system that enables persons with cardiac complaints to record a reliable 12-lead ECG at home to improve the diagnostic process and, consequently, reduce the time between the onset of symptoms and adequate treatment.MethodsUsing an iterative design approach, ECGraph was developed. The system consists of an ECG measurement system and a mobile app, which were developed with the help of several concept tests. To evaluate the design, a prototype of the final design was built and a final technical performance test and usability test were executed.ResultsThe ECG measurement system consists of a belt and 4 limb straps. Ten wet Ag/AgCl electrodes are placed in the belt to optimize skin-electrode contact. The product is controlled via an app on the mobile phone of the user. Once a person experiences symptoms, he or she can put on the belt and record ECGs within a few minutes. Short instructions, supported by visualizations, offer guidance during use. ECGs are sent wirelessly to the caregiver, and the designated expert can quickly interpret the results. Usability tests with the final prototype (n=6) showed that the participants were able to put on the product within 8 minutes during first-time use. However, we expect that the placement of the product can be executed faster when the user becomes more familiar with the product. Areas of improvement focus mainly on confidence during product use. In the technical performance test, a 12-lead ECG was made and reproduced 6 times.ConclusionsWe developed a new 12-lead ECG system for home use. The product is expected to be more user-friendly than current hospital ECG systems and is designed to record more reliable data than current ECG systems for home use, which makes it suitable for expert interpretation. The system has great potential to be incorporated into an outpatient practice, so that arrhythmias and ischemia can be diagnosed and treated as early as possible.

Carbon nanotube-based self-adhesive polymer electrodes for wireless long-term recording of electrocardiogram signals

In this study, the concept of polymer electrodes integrated with a wireless electrocardiogram (ECG) system was described. Polymer electrodes for long-term ECG measurements were fabricated by loading high content of carbon nanotubes (CNTs) in polydimethylsiloxane. Silver nanoparticles (Ag NPs) were added to increase the flexibility of the polymer and the conductivity of the electrode. An ECG electrode patch was fabricated by integrating the electrodes with an adhesive polydimethylsiloxane (aPDMS) layer. Holes in the electrode filled with aPDMS can enable robust contact between the electrode and skin, reducing motion artifacts. A wireless ECG measurement system was developed and adapted to the polymer electrodes. The polymer electrodes combined with the measurement system were successfully applied in wireless, long-term recording of ECG signals. An eleven-day continuous test showed that the ECG signal did not degrade over time. The results of attach/detach tests demonstrated that the ECG signal was affected by motion artifacts after six attach/detach cycles. The electrodes produced are flexible and exhibit good ECG performance, and therefore can be used in wearable medical monitoring systems. The approach proposed in this study holds significant promise for commercial application in medical fields.

X-ray 이미지를 활용한 증강현실 기반 심전도 측정시스템 개발

X-ray 이미지를 활용한 증강현실 기반 심전도 측정시스템 개발

Biosignal PI, an affordable open-source ECG and respiration measurement system.

Bioimedical pilot projects e.g., telemedicine, homecare, animal and human trials usually involve several physiological measurements. Technical development of these projects is time consuming and in particular costly. A versatile but affordable biosignal measurement platform can help to reduce time and risk while keeping the focus on the important goal and making an efficient use of resources. In this work, an affordable and open source platform for development of physiological signals is proposed. As a first step an 8–12 leads electrocardiogram (ECG) and respiration monitoring system is developed. Chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 for patient safety. The result shows the potential of this platform as a base for prototyping compact, affordable, and medically safe measurement systems. Further work involves both hardware and software development to develop modules. These modules may require development of front-ends for other biosignals or just collect data wirelessly from different devices e.g., blood pressure, weight, bioimpedance spectrum, blood glucose, e.g., through Bluetooth. All design and development documents, files and source codes will be available for non-commercial use through project website, BiosignalPI.org.

침대 패드 형태의 용량성 전극에서 측정된 심전도 신호를 처리하기 위한 자동 잡음 제거 및 피크 검출 알고리즘

Recent technological advances have increased interest in personal health monitoring. Electrocardiogram(ECG) monitoring is a basic healthcare activity and can provide decisive information regarding cardiovascular system status. In this study, we developed a capacitive ECG measurement system that can be included within a cloth mattress pad. The device permits ECG data to be obtained during sleep by using capacitive electrodes. However, it is difficult to detect R-wave peaks automatically because signals obtained from the system can include a high level of noise from various sources. Because R-peak detection is important in ECG applications, we developed an algorithm that can reduce noise and improve detection accuracy under noisy conditions. Algorithm reliability was evaluated by determining its sensitivity(Se), positive predictivity(+P), and error rate(Er) by using data from the MIT-BIH Polysomnographic Database and from our capacitive ECG system. The results showed that Se = 99.75%, +P = 99.77%, and Er = 0.47% for MIT-BIH Polysomnographic Database while Se = 96.47%, +P = 99.32%, and Er = 4.34% for our capacitive ECG system. Based on those results, we conclude that our R-peak detection method is capable of providing useful ECG information, even under noisy signal conditions.

Highly sensitive driver health condition monitoring system using nonintrusive active electrodes

Abstract The proposed electrocardiogram (ECG) measurement system uses a nonintrusive ECG sensor with electrically active electrodes to measure an ECG signal without any noise effects. In this manner, the optimal position and size of the active electrodes attached to a car seat can be selected from several practical scenarios considering the physical position of the subject's heart to minimize the noise effects for the nonintrusive ECG measurement system in the car. The ECG signals from a clothed and seated occupant of the automobile are measured at a sampling rate of 100 Hz. A signal conditioning circuit was also designed to reduce the noise effects generated by the internal circuitry. The ECG signals are measured and transmitted wirelessly to a base station connected to a server PC in a personal area network for signal processing. The driver's condition is monitored wirelessly and analyzed by performing a heart rate variability analysis in the time and frequency domains.

Real Time Drowsiness Detection by a WSN based Wearable ECG Measurement System

Whether a person is feeling sleepy or reasonably awake is important safety information in many areas, such as humans operating in traffic or in heavy industry. The changes of body signals have been mostly researched by looking at electroencephalogram(EEG) signals but more and more other medical signals are being examined. In our study, an electrocardiogram(ECG) signal is measured at a sampling rate of 100 Hz and used to try to distinguish the possible differences in signal between the two states: awake and drowsy. Practical tests are conducted using a wireless sensor node connected to a wearable ECG sensor, and an ECG signal is transmitted wirelessly to a base station connected to a server PC. Through the QRS complex in the ECG analysis it is possible to obtain much information that is helpful for diagnosing different types of cardiovascular disease. A program is made with MATLAB for digital signal filtering and graphing as well as recognizing the parts of the QRS complex within the signal. Drowsiness detection is performed by evaluating the R peaks, R-R interval, interval between R and S peaks and the duration of the QRS complex..

Capacitive electrocardiogram measurement system in the driver seat

Capacitive electrocardiogram measurement system in the driver seat

Bluetooth기반의 센서네트워크를 이용한 효율적인 심전도 측정시스템 설계

The convergence tendency accelerates the realization of the ubiquitous healthcare (u-Healthcare) between the technology including the power generaation and IT-BT-NT of the ubiquitous computing technology. By rapidly analyzing a large amount of collected from the sensor network with processing and delivering to the medical team an u-Healthcare can provide a patient for an inappropriate regardless of the time and place. As to the existing u-Healthcare, since the sensor node all transmitted collected data by using with the Zigbee protocol the processing burden of the base node was big and there was many communication frequency of the sensor node. In this paper, the u-Healthcare system in which it can efficiently apply to mobile apparatuses it provided the transfer rate in which it is superior to the bio-signal delivery where there are the life and direct relation which by using the Bluetooth instead of the Zigbee protocol and in which it is variously used in the ubiquitous environment was designed. Moreover, by applying the EEF(Embedded Event Filtering) technique in which data in which it includes in the event defined in advance selected and it transmits with the base node, the communication frequency and were reduced. We confirmed to be the system in which it is efficient through the simulation result than the existing Electrocardiogram Measurement system.

Design of a Microcontroller-Based ECG Measurement System to Detect QRS Complex with dECG in Real-Time

An electrocardiogram (ECG) cycle reflects the different electrical activities within the heart. For instance, the QRS complex of the ECG reflects the electrical activity within the heart during the ventricular contraction, and it often has a long duration (>120 ms) in heart failure patients. It is possible to obtain much information that is helpful for diagnosing different types of cardiovascular disease by examining the timing and the shape of these waves. This paper presents a low computational-complexity QRS complex detection algorithm, which can easily be implemented in a general microcontroller. The algorithm adopts the derivative of the electrocardiogram to accurately identify the peaks (the Q-, R-, and S-peaks) and calculate the heart rate and the duration of the QRS complex in real-time. Finally, we apply the detection algorithm to design a microcontroller-based ECG measurement instrument, and test it with 12 electrocardiogram samples (with heart rates from 49.59 to 155.44 beats per minute). The experimental results show that the maximum relative error of the measured R-R interval with the new QRS complex detection algorithm is only 1.58%, while the more detailed experimental data will be discussed at the end of this paper. The low computational-complexity QRS complex detection algorithm and the microcontroller-based ECG measurement system developed in this work have good potential for use in portable and inexpensive diagnostic instruments.

Wireless and Non-contact ECG Measurement System – the “Aachen SmartChair”

This publication describes a measurement system that obtains an electrocardiogram (ECG) by capacitively coupled electrodes. Fordemonstration purposes, this measurement system was integrated into an off-the-shelf office chair (so-called “Aachen SmartChair”).Whereas in usual clinical applications adhesive, conductively-coupled electrodes have to be attached to the skin, the described system is able to measure an ECG without direct skin contact through the cloth. A wireless communication module was integrated for transmitting theECG data to a PC or to an ICU patient monitor. For system validation, a classical ECG with conductive electrodes and an oxygensaturation signal (SpO2) were obtained simultaneously. Finally, system-specific problems of the presented device are discussed.

Handheld electrocardiogram measurement instrument using a new peak quantification method algorithm built on a system-on-chip embedded system

This article reports on the new design and development of an electrocardiogram (ECG) measurement instrument built on a system-on-chip (SOC) embedded system. A new approach using the peak quantification method (PQM) for measuring the human heart rate is described. A computer, some medical equipment, and other facilities are often required for conducting the traditional ECG measurements. However, the monitors of such instruments have some disadvantages, e.g., bulky, not very easy to transport, expensive, and so forth. Hence, we propose a new design for ECG measurement which is built on an embedded system. Our system adopts a SOC and ECG detection circuits to carry out a real-time, low-cost, and compact ECG measurement system. Regarding heart rate computation, the experimental results show that the new PQM algorithm, when applied to heart rate measurements, yields error smaller than 1bpm. In addition, the correlation coefficient between the measured and actual heartbeats can reach 0.94 when the heart rate is less than 153bpm. It shows that the use of the PQM algorithm gives an extremely high degree of accuracy.

Application of InP Neural Network to ECG BeatClassification

This paper presents an application of a hybrid neural network structure to the classification of the electrocardiogram (ECG) beats. Three different feature extraction methods are comparatively examined: discrete cosine transform, wavelet transform and a direct method. Classification performances, training times and the numbers of nodes of Kohonen network, Restricted Coulomb Energy (RCE) network and the hybrid neural network are presented. To increase the classification performance and to decrease the number of nodes, the hybrid neural network is trained by Genetic Algorithms (GAs). Ten types of ECG beats obtained from the MIT-BIH database and from a real-time ECG measurement system are classified with a success of 98% by using the hybrid neural network structure and discrete cosine transform together.