Soft, comfortable polymer dry electrodes for high quality ECG and EEG recording

Conventional gel electrodes are widely used for biopotential measurements, despite important drawbacks such as skin irritation, long set-up time and uncomfortable removal. Recently introduced dry electrodes with rigid metal pins overcome most of these problems; however, their rigidity causes discomfort and pain. This paper presents dry electrodes offering high user comfort, since they are fabricated from EPDM rubber containing various additives for optimum conductivity, flexibility and ease of fabrication. The electrode impedance is measured on phantoms and human skin. After optimization of the polymer composition, the skin-electrode impedance is only similar to 10 times larger than that of gel electrodes. Therefore, these electrodes are directly capable of recording strong biopotential signals such as ECG while for low-amplitude signals such as EEG, the electrodes need to be coupled with an active circuit. EEG recordings using active polymer electrodes connected to a clinical EEG system show very promising results: alpha waves can be clearly observed when subjects close their eyes, and correlation and coherence analyses reveal high similarity between dry and gel electrode signals. Moreover, all subjects reported that our polymer electrodes did not cause discomfort. Hence, the polymer-based dry electrodes are promising alternatives to either rigid dry electrodes or conventional gel electrodes

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

Clinical Applications of Electrical Impedance Tomography in Stroke and Traumatic Brain Injury

Electrical Impedance Tomography (EIT) is a medical imaging technology which uses voltage measurements on the boundaries to reconstruct internal conductivity changes. When applied to imaging brain function, EIT is challenged by the unique geometry of the head and the high variability in the conductivities of brain tissue. Stroke and Trau-matic Brain Injury (TBI) are two of the leading causes of death and long-term disability worldwide. It has been suggested that EIT, which is already in clinical use primarily as a means of assessing lung function, could be used as a pre-hospital diagnostic tool for stroke and TBI, and for bedside monitoring for brain injury patients. The main aim of this PhD thesis is to bring the application of EIT in brain injury closer to regular clinical use. Chapter 1 introduces the concepts of EIT, stroke and TBI, and provides a comprehensive review of clinically relevant neuroimaging techniques and the current state of brain EIT. Chapter 2 presents the results of a series of lab experiments designed to investigate the characteristics and mechanisms of drift in measured boundary voltages, which is the key technical barrier to brain monitoring with EIT. Ex-periments were conducted on lab phantoms, vegetable skin, and healthy human subjects. Chapter 3 describes a feasibility study of monitoring for brain injury with EIT over several hours, using noise recorded on real healthy volunteers. This study also compares the performance of different electrode types. Chapter 4 presents a clinical pilot study performed on acute stroke patients. Multi-frequency (MF) EIT data were record-ed on patients and healthy controls to create the first of its kind clinical EIT dataset to be used as a resource for future research for the EIT community. Finally, the ability to identify stroke patients is demonstrated on the clinical EIT dataset

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