New directions in EEG measurement: an investigation into the fidelity of electrical potential sensor signals

Low frequency noise performance is the key indicator in determining the signal to noise ratio of a capacitively coupled sensor when used to acquire electroencephalogram signals. For this reason, a prototype Electric Potential Sensor device based on an auto-zero operational amplifier has been developed and evaluated. The absence of 1/f noise in these devices makes them ideal for use with signal frequencies ~10 Hz or less. The active electrodes are designed to be physically and electrically robust and chemically and biochemically inert. They are electrically insulated (anodized) and have diameters of 12 mm or 18 mm. In both cases, the sensors are housed in inert stainless steel machined housings with the electronics fabricated in surface mount components on a printed circuit board compatible with epoxy potting compounds. Potted sensors are designed to be immersed in alcohol for sterilization purposes. A comparative study was conducted with a commercial wet gel electrode system. These studies comprised measurements of both free running electroencephalogram and Event Related Potentials. Quality of the recorded electroencephalogram was assessed using three methods of inspection of raw signal, comparing signal to noise ratios, and Event Related Potentials noise analysis. A strictly comparable signal to noise ratio was observed and the overall conclusion from these comparative studies is that the noise performance of the new sensor is appropriate

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

Entwicklung einer berührungslosen EEG-Mütze mittels kapazitiver Elektroden

Non-contact capacitive electrodes for bioelectric diagnostics provide an interesting alternative to classical galvanically coupled electrodes. Such a low cost diagnostic system can be applied without preparation time and in mobile wireless environments. For even higher user comfort textile capacitive electrodes are preferable. In this work, a comprehensive model for the electronic noise properties and frequency dependent responses of PCB-based, as well as textile non-contact capacitive electrodes, is presented. A thorough study of the influence of the electrical components on the resulting noise properties of these electrodes, is provided by independently measuring the corresponding noise spectra. The most important low frequency noise source of capacitive electrode is the necessary high input bias resistance. By comparing the noise measurements with the theoretical noise model of the electrode, it is concluded that the surface of the electrode contributes to an additional 1/f-power noise. It is also found that the highest possible coupling capacitance is most favorable for low noise behavior. Therefore, we implemented electrodes with electrically conducting fabric surfaces. With these electrodes, it is possible to enlarge the surface of the electrode while simultaneously maintaining a small distance between the body and the electrode over the whole surface area, thus maximizing the capacitance. We also show that the use of textile capacitive electrodes, reduces the noise considerably. Furthermore, this thesis describes the construction of a capacitive non-contact textile electroencephalography measuring hat (cEEG hat) with seven measuring channels. This hat benefits from the low noise characteristics of the integrated developed textile capacitive electrodes. The measured noise spectrum of this cEEG hat shows low noise characteristics at low frequencies. This fulfills many requirements for measuring brain signals. The implemented cEEG hat is comfortable to wear during very long measurements and even during sleep periods. In contrast to common methods, the cEEG hat provides a possibility of measuring EEG signal during sleep outside laboratories and in the comfort of home. EEG sleep measurements shown in this work, are recorded inside a normal apartment. The possibility of brain computer interface application is also shown by measuring steady state visually evoked potentials (SSVEP) at different frequencies.Berührungslose, kapazitive Elektroden für bioelekrische Untersuchungen stellen eine interessante Alternative zu klassischen galvanisch gekoppelten Elektroden dar. Ein solches preisgünstiges Diagnosesystem kann ohne lange Vorbereitungszeit und in mobilen Umgebungen eingesetzt werden. Für gesteigerten Tragekomfort sind textile Elektroden von Vorteil. In dieser Arbeit wird eine umfassende Beschreibung der elektronischen Rauscheigenschaften und des frequenzabhängigen Verhaltens von sowohl platinenbasierten, als auch textilen kapazitiven Elektroden vorgestellt. Die Einflüsse aller elektronischen Komponenten auf die resultierenden Rauscheigenschaften werden durch Messungen der entsprechenden Rauschspektren untersucht. Die wichtigste niederfrequente Rauschquelle kapazitiver Elektroden stellt der notwendige und zugleich hohe Bias-Eingangswiderstand dar. Durch Vergleich der gemessenen Rauschspektren mit dem theoretischen Modell wird die Oberfläche der Elektroden als eine zusätzliche 1/f-Rauschquelle identifiziert. Dabei ist die größtmögliche Kopplungskapazität vorteilhaft für ein niedriges Rauschen. Deshalb setzen wir im Folgenden Elektroden aus elektrisch leitfähigen Textilien ein. Mit diesen Elektroden ist es möglich, die Oberfläche der Elektrode unter gleichzeitiger Beibehaltung eines kleinen Abstandes zum Körper zu vergrößern. Dies maximiert wiederum die Kapazität. Wir zeigen zudem, dass die Verwendung textiler kapazitiver Elektroden die Rauscheigenschaften deutlich verbessert. Desweiteren wird in dieser Arbeit die Konstruktion eines kapazitiven, berührungslosen EEG-Helmes (cEEG-Mütze) mit sieben Kanälen beschrieben. Dieser Helm profitiert von den guten Rauscheigenschaften der zuvor entwickelten und hier integrierten textilen Elektroden. Die gemessenen Rauschspektren zeigen ein niedriges Rauschen im unteren Frequenzbereich. Dies erfüllt viele Voraussetzungen für die Messung von Gehirnsignalen. Die erstellte cEEG-Mütze lässt sich während langer Messzeiten und Schlafperioden angenehm tragen. Im Gegensatz zu herkömmlichen Methoden ermöglicht sie Messungen außerhalb von Laboratorien und im gewohnten Umfeld. Alle in dieser Arbeit gezeigten Schlafmessungen wurden in einer normalen Wohnung aufgezeichnet. Außerdem wird die Einsatzmöglichkeit für sogenannte ”Gehirn-Computer-Schnittstellen” anhand der Messung von ”steady state visually evoked potentials” (SSVEP) Signalen bei verschiedenen Frequenzen demonstriert

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

Polypyrrole (PPy) Coated Patterned Vertical Carbon Nanotube (pvCNT) Dry ECG Electrode Integrated with a Novel Wireless Resistive Analog Passive (WRAP) ECG Sensor

Polypyrrole (PPy) Coated Patterned Vertical Carbon Nanotube (pvCNT) Dry ECG Electrode Integrated with a Novel Wireless Resistive Analog Passive (WRAP) ECG Senso

A Hybrid-Powered Wireless System for Multiple Biopotential Monitoring

Chronic diseases are the top cause of human death in the United States and worldwide. A huge amount of healthcare costs is spent on chronic diseases every year. The high medical cost on these chronic diseases facilitates the transformation from in-hospital to out-of-hospital healthcare. The out-of-hospital scenarios require comfortability and mobility along with quality healthcare. Wearable electronics for well-being management provide good solutions for out-of-hospital healthcare. Long-term health monitoring is a practical and effective way in healthcare to prevent and diagnose chronic diseases. Wearable devices for long-term biopotential monitoring are impressive trends for out-of-hospital health monitoring. The biopotential signals in long-term monitoring provide essential information for various human physiological conditions and are usually used for chronic diseases diagnosis. This study aims to develop a hybrid-powered wireless wearable system for long-term monitoring of multiple biopotentials. For the biopotential monitoring, the non-contact electrodes are deployed in the wireless wearable system to provide high-level comfortability and flexibility for daily use. For providing the hybrid power, an alternative mechanism to harvest human motion energy, triboelectric energy harvesting, has been applied along with the battery to supply energy for long-term monitoring. For power management, an SSHI rectifying strategy associated with triboelectric energy harvester design has been proposed to provide a new perspective on designing TEHs by considering their capacitance concurrently. Multiple biopotentials, including ECG, EMG, and EEG, have been monitored to validate the performance of the wireless wearable system. With the investigations and studies in this project, the wearable system for biopotential monitoring will be more practical and can be applied in the real-life scenarios to increase the economic benefits for the health-related wearable devices

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

Non Contact Heart Monitoring

Electrocardiograms are one of the most widely used methods for evaluating the structure-function relationships of the heart in health and disease. This book is the first of two volumes which reviews recent advancements in electrocardiography. This volume lays the groundwork for understanding the technical aspects of these advancements. The five sections of this volume, Cardiac Anatomy, ECG Technique, ECG Features, Heart Rate Variability and ECG Data Management, provide comprehensive reviews of advancements in the technical and analytical methods for interpreting and evaluating electrocardiograms. This volume is complemented with anatomical diagrams, electrocardiogram recordings, flow diagrams and algorithms which demonstrate the most modern principles of electrocardiography. The chapters which form this volume describe how the technical impediments inherent to instrument-patient interfacing, recording and interpreting variations in electrocardiogram time intervals and morphologies, as well as electrocardiogram data sharing have been effectively overcome. The advent of novel detection, filtering and testing devices are described. Foremost, among these devices are innovative algorithms for automating the evaluation of electrocardiograms. Permanenet links: Full chapter: http://www.intechopen.com/articles/show/title/non-contact-heart-monitoring Book: http://www.intechopen.com/books/show/title/advances-in-electrocardiograms-methods-and-analysi