Reduction of Motion Artifacts and Improvement of R Peak Detecting Accuracy Using Adjacent Non-Intrusive ECG Sensors

Non-intrusive electrocardiogram (ECG) monitoring has many advantages: easy to measure and apply in daily life. However, motion noise in the measured signal is the major problem of non-intrusive measurement. This paper proposes a method to reduce the noise and to detect the R peaks of ECG in a stable manner in a sitting arrangement using non-intrusive sensors. The method utilizes two capacitive ECG sensors (cECGs) to measure ECG, and another two cECGs located adjacent to the sensors for ECG are added to obtain the information on motion. Then, active noise cancellation technique and the motion information are used to reduce motion noise. To verify the proposed method, ECG was measured indoors and during driving, and the accuracy of the detected R peaks was compared. After applying the method, the sum of sensitivity and positive predictivity increased 8.39% on average and 26.26% maximally in the data. Based on the results, it was confirmed that the motion noise was reduced and that more reliable R peak positions could be obtained by the proposed method. The robustness of the new ECG measurement method will elicit benefits to various health care systems that require noninvasive heart rate or heart rate variability measurements.1145Ysciescopu

Wearable and Nearable Biosensors and Systems for Healthcare

Biosensors and systems in the form of wearables and “nearables” (i.e., everyday sensorized objects with transmitting capabilities such as smartphones) are rapidly evolving for use in healthcare. Unlike conventional approaches, these technologies can enable seamless or on-demand physiological monitoring, anytime and anywhere. Such monitoring can help transform healthcare from the current reactive, one-size-fits-all, hospital-centered approach into a future proactive, personalized, decentralized structure. Wearable and nearable biosensors and systems have been made possible through integrated innovations in sensor design, electronics, data transmission, power management, and signal processing. Although much progress has been made in this field, many open challenges for the scientific community remain, especially for those applications requiring high accuracy. This book contains the 12 papers that constituted a recent Special Issue of Sensors sharing the same title. The aim of the initiative was to provide a collection of state-of-the-art investigations on wearables and nearables, in order to stimulate technological advances and the use of the technology to benefit healthcare. The topics covered by the book offer both depth and breadth pertaining to wearable and nearable technology. They include new biosensors and data transmission techniques, studies on accelerometers, signal processing, and cardiovascular monitoring, clinical applications, and validation of commercial devices

Graphene textile smart clothing for wearable cardiac monitoring

Wearable electronics is a rapidly growing field that recently started to introduce successful commercial products into the consumer electronics market. Employment of biopotential signals in wearable systems as either biofeedbacks or control commands are expected to revolutionize many technologies including point of care health monitoring systems, rehabilitation devices, human–computer/machine interfaces (HCI/HMIs), and brain–computer interfaces (BCIs). Since electrodes are regarded as a decisive part of such products, they have been studied for almost a decade now, resulting in the emergence of textile electrodes. This study reports on the synthesis and application of graphene nanotextiles for the development of wearable electrocardiography (ECG) sensors for personalized health monitoring applications. In this study, we show for the first time that the electrocardiogram was successfully obtained with graphene textiles placed on a single arm. The use of only one elastic armband, and an “all-textile-approach” facilitates seamless heart monitoring with maximum comfort to the wearer. The functionality of graphene textiles produced using dip coating and stencil printing techniques has been demonstrated by the non-invasive measurement of ECG signals, up to 98% excellent correlation with conventional pre-gelled, wet, silver/silver-chloride (Ag / AgCl) electrodes. Heart rate have been successfully determined with ECG signals obtained in different situations. The system-level integration and holistic design approach presented here will be effective for developing the latest technology in wearable heart monitoring devices

Five day attachment ECG electrodes for longitudinal bio-sensing using conformal tattoo substrates

State-of-the-art ECG (electrocardiography) uses wet Silver/Silver-Chloride (Ag/AgCl) electrodes where a conductive gel is used to provide a esistive, low impedance, connection to the skin. These electrodes are very easy to apply, but have a significant number of limitations for personalized and preventative healthcare. In particular that the gel dries out giving a limited connection time. This paper presents ECG electrodes manufactured using the inkjet printing of Silver nanoparticles onto a conformal tattoo substrate. The substrate maintains a high quality connection to the body for many days at a time allowing ECG monitoring over periods not previously possible without electrode re-attachment. The design and manufacture of the conformal electrodes is presented, together with detailed characterization of the electrode performance in terms of the Signal to Noise Ratio and baseline wander. The Signal to Noise Ratio is shown to still be over 30 dB five days after the initial electrode attachment

Tutorial. Surface EMG detection, conditioning and pre-processing: Best practices

This tutorial is aimed primarily to non-engineers, using or planning to use surface electromyography (sEMG) as an assessment tool for muscle evaluation in the prevention, monitoring, assessment and rehabilitation fields. The main purpose is to explain basic concepts related to: (a) signal detection (electrodes, electrode–skin interface, noise, ECG and power line interference), (b) basic signal properties, such as amplitude and bandwidth, (c) parameters of the front-end amplifier (input impedance, noise, CMRR, bandwidth, etc.), (d) techniques for interference and artifact reduction, (e) signal filtering, (f) sampling and (g) A/D conversion, These concepts are addressed and discussed, with examples. The second purpose is to outline best practices and provide general guidelines for proper signal detection, conditioning and A/D conversion, aimed to clinical operators and biomedical engineers. Issues related to the sEMG origin and to electrode size, interelectrode distance and location, have been discussed in a previous tutorial. Issues related to signal processing for information extraction will be discussed in a subsequent tutorial

A Survey Study of the Current Challenges and Opportunities of Deploying the ECG Biometric Authentication Method in IoT and 5G Environments

The environment prototype of the Internet of Things (IoT) has opened the horizon for researchers to utilize such environments in deploying useful new techniques and methods in different fields and areas. The deployment process takes place when numerous IoT devices are utilized in the implementation phase for new techniques and methods. With the wide use of IoT devices in our daily lives in many fields, personal identification is becoming increasingly important for our society. This survey aims to demonstrate various aspects related to the implementation of biometric authentication in healthcare monitoring systems based on acquiring vital ECG signals via designated wearable devices that are compatible with 5G technology. The nature of ECG signals and current ongoing research related to ECG authentication are investigated in this survey along with the factors that may affect the signal acquisition process. In addition, the survey addresses the psycho-physiological factors that pose a challenge to the usage of ECG signals as a biometric trait in biometric authentication systems along with other challenges that must be addressed and resolved in any future related research.

The Assessment and Reduction of Motion Artifact in Dry Contact Biopotential Electrodes

The connecting interface between biopotential monitoring systems and the human body is the electrode. Conventional medical electrodes use gel to improve skin-electrode contact and glue to provide secure attachment of the electrode to the skin. However, this type of electrode is neither reusable nor user-friendly when implemented in wearable monitoring systems. For wearable monitoring systems, the best type of electrode to use, as seen from the point of view of user comfort and ease of use of the wearable system, is the un-gelled electrode. The un-gelled electrode foregoes conductive gel and attachment glue and instead uses body moisture and clothing pressure to provide contact and secure attachment. The drawback of un-gelled electrodes is that they are susceptible to the wearer’s movements, namely, to motion artifact.Solving the issue of motion artifact will improve signal quality and reliability for wearable systems and, due to integration and reusability, would reduce costs. These two factors, when combined, would enable the widespread use of wearable monitoring systems in both the medical context and the consumer-user context. One effect of this will be a reduction in load and costs on health care systems due to improved preventive monitoring and better monitoring of patients in the recovery and rehabilitation phase. A second effect, combined with the information exchanging channels between individuals, will be unforeseen developments in health science due to what can be called the crowdsourcing of some aspect of physical and mental health and fitness.This thesis aims to further state-of-the art wearable physiological monitoring by aiding motion artifact research and electrode design. To accomplish this aim, investigations into the programmable and repeatable generation of electrode movement in order to generate motion artifact, the effect of impedance current frequency on the relationship between skin-electrode interface impedance and electrode movement and motion artifact, the effect of using an electrode support structure and how its design affects the motion artifact, and the effects of garment parameters such as tightness are presented in this thesis.A system that generates known and programmable motion of the electrode under controlled circumstances was designed, tested, and after the verification of system functionality, used in subsequent investigations. The presented system generates accurate motion of the electrode and the electrode motion can be observed as both motion artifact and skin-electrode impedance changes.A real time impedance spectroscopy study of 24 impedance current frequencies between 25 Hz and 1 MHz was done on electrodes subject to accurately known motion generated by the designed system in order to find the impedance current frequencies most suited to motion artifact studies.During this research, a hypothesis was formed that states that an electrode with a structural design that restricts epidermis deformation by trapping the epidermis under the electrode area can reduce motion artifact. Different electrode support structures were designed in order to test this hypothesis. The electrodes with support structures were subjected to system-generated motion and the resulting data were analyzed for the verification of support structure functionality and the hypothesis.Electrodes that were supported by a tight garment-mimicking elastic straps were studied under subjectgenerated movement and at various clothing tightness levels. The same study was used to understand the effect of using padding between the garment and the electrode.The motion artifact generation system was seen to be successful in accurately generating electrode motion, thus motion artifact, which was programmable and repeatable. The electrode mounting force monitoring proved to be an important functionality as the mounting force was seen to affect the motion artifact.Skin-electrode impedance was found to correlate well with electrode motion in current frequencies between 17 kHz and 1 MHz. While the correlation between impedance and motion artifact was lower than the correlation between impedance and electrode motion, it was also highest in this frequency band.Electrode support structure design is seen to be an important factor to consider when designing the electrode, and the electrodes that came closest to fulfilling the design criteria of the hypothesis were the best functioning electrodes. The hypothesis is seen to be promising and electrodes that distributed skin deformation over a large area and/or restrict epidermis deformation were found to reduce motion artifact.In the presented studies, the pressures under those electrodes that were found to be the most effective in reducing motion artifact differed between experiments yet stayed in a range between 5 mmHg -36 mmHg (0.66 kPa – 4.80 kPa). A simple guideline is that the electrode should be attached firmly but not so firmly that it becomes uncomfortable. This guideline fitted well with the pressure levels found for each experiment.The presented Motion Artifact Generation and Assessment System can be used for research or commercial purposes, furthering the research on motion artifact and aiding in the successful design of motion artifact resilient electrodes. The issue of which are the best current frequencies to use to measure skin-electrode interface impedance in motion artifact research has been clarified. Possible means of reducing motion artifact at its origin by using structural electrode designs that restrict epidermis deformation is hypothesized and proven worthy of further research. The importance of garment design and guidelines for use are given and tightness recommendations presented. The thesis presents methodology for the furthering of the understanding of motion artifact and electrode design that will eventually make wearable monitoring systems widespread over a large range of applications and a large number of users

Human Body–Electrode Interfaces for Wide-Frequency Sensing and Communication: A Review

Several on-body sensing and communication applications use electrodes in contact with the human body. Body–electrode interfaces in these cases act as a transducer, converting ionic current in the body to electronic current in the sensing and communication circuits and vice versa. An ideal body–electrode interface should have the characteristics of an electrical short, i.e., the transfer of ionic currents and electronic currents across the interface should happen without any hindrance. However, practical body–electrode interfaces often have definite impedances and potentials that hinder the free flow of currents, affecting the application’s performance. Minimizing the impact of body–electrode interfaces on the application’s performance requires one to understand the physics of such interfaces, how it distorts the signals passing through it, and how the interface-induced signal degradations affect the applications. Our work deals with reviewing these elements in the context of biopotential sensing and human body communication

Low Power Circuits for Smart Flexible ECG Sensors

Cardiovascular diseases (CVDs) are the world leading cause of death. In-home heart condition monitoring effectively reduced the CVD patient hospitalization rate. Flexible electrocardiogram (ECG) sensor provides an affordable, convenient and comfortable in-home monitoring solution. The three critical building blocks of the ECG sensor i.e., analog frontend (AFE), QRS detector, and cardiac arrhythmia classifier (CAC), are studied in this research. A fully differential difference amplifier (FDDA) based AFE that employs DC-coupled input stage increases the input impedance and improves CMRR. A parasitic capacitor reuse technique is proposed to improve the noise/area efficiency and CMRR. An on-body DC bias scheme is introduced to deal with the input DC offset. Implemented in 0.35m CMOS process with an area of 0.405mm2, the proposed AFE consumes 0.9W at 1.8V and shows excellent noise effective factor of 2.55, and CMRR of 76dB. Experiment shows the proposed AFE not only picks up clean ECG signal with electrodes placed as close as 2cm under both resting and walking conditions, but also obtains the distinct -wave after eye blink from EEG recording. A personalized QRS detection algorithm is proposed to achieve an average positive prediction rate of 99.39% and sensitivity rate of 99.21%. The user-specific template avoids the complicate models and parameters used in existing algorithms while covers most situations for practical applications. The detection is based on the comparison of the correlation coefficient of the user-specific template with the ECG segment under detection. The proposed one-target clustering reduced the required loops. A continuous-in-time discrete-in-amplitude (CTDA) artificial neural network (ANN) based CAC is proposed for the smart ECG sensor. The proposed CAC achieves over 98% classification accuracy for 4 types of beats defined by AAMI (Association for the Advancement of Medical Instrumentation). The CTDA scheme significantly reduces the input sample numbers and simplifies the sample representation to one bit. Thus, the number of arithmetic operations and the ANN structure are greatly simplified. The proposed CAC is verified by FPGA and implemented in 0.18m CMOS process. Simulation results show it can operate at clock frequencies from 10KHz to 50MHz. Average power for the patient with 75bpm heart rate is 13.34W

Blind Source Separation for the Processing of Contact-Less Biosignals

(Spatio-temporale) Blind Source Separation (BSS) eignet sich für die Verarbeitung von Multikanal-Messungen im Bereich der kontaktlosen Biosignalerfassung. Ziel der BSS ist dabei die Trennung von (z.B. kardialen) Nutzsignalen und Störsignalen typisch für die kontaktlosen Messtechniken. Das Potential der BSS kann praktisch nur ausgeschöpft werden, wenn (1) ein geeignetes BSS-Modell verwendet wird, welches der Komplexität der Multikanal-Messung gerecht wird und (2) die unbestimmte Permutation unter den BSS-Ausgangssignalen gelöst wird, d.h. das Nutzsignal praktisch automatisiert identifiziert werden kann. Die vorliegende Arbeit entwirft ein Framework, mit dessen Hilfe die Effizienz von BSS-Algorithmen im Kontext des kamera-basierten Photoplethysmogramms bewertet werden kann. Empfehlungen zur Auswahl bestimmter Algorithmen im Zusammenhang mit spezifischen Signal-Charakteristiken werden abgeleitet. Außerdem werden im Rahmen der Arbeit Konzepte für die automatisierte Kanalauswahl nach BSS im Bereich der kontaktlosen Messung des Elektrokardiogramms entwickelt und bewertet. Neuartige Algorithmen basierend auf Sparse Coding erwiesen sich dabei als besonders effizient im Vergleich zu Standard-Methoden.(Spatio-temporal) Blind Source Separation (BSS) provides a large potential to process distorted multichannel biosignal measurements in the context of novel contact-less recording techniques for separating distortions from the cardiac signal of interest. This potential can only be practically utilized (1) if a BSS model is applied that matches the complexity of the measurement, i.e. the signal mixture and (2) if permutation indeterminacy is solved among the BSS output components, i.e the component of interest can be practically selected. The present work, first, designs a framework to assess the efficacy of BSS algorithms in the context of the camera-based photoplethysmogram (cbPPG) and characterizes multiple BSS algorithms, accordingly. Algorithm selection recommendations for certain mixture characteristics are derived. Second, the present work develops and evaluates concepts to solve permutation indeterminacy for BSS outputs of contact-less electrocardiogram (ECG) recordings. The novel approach based on sparse coding is shown to outperform the existing concepts of higher order moments and frequency-domain features