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A high-performance 8 nV/√Hz 8-channel wearable and wireless system for real-time monitoring of bioelectrical signals
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s12984-019-0629-2.pdf | Published version | 5.46 MB | Adobe PDF | View/Open |
Title: | A high-performance 8 nV/√Hz 8-channel wearable and wireless system for real-time monitoring of bioelectrical signals |
Authors: | Petkos, K Koutsoftidis, S Guiho, T Degenaar, P Jackson, A Greenwald, S Brown, P Denison, T Drakakis, E |
Item Type: | Journal Article |
Abstract: | Background: It is widely accepted by the scientific community that bioelectrical signals, which can be used for the identification of neurophysiological biomarkers indicative of a diseased or pathological state, could direct patient treatment towards more effective therapeutic strategies. However, the design and realisation of an instrument that can precisely record weak bioelectrical signals in the presence of strong interference stemming from a noisy clinical environment is one of the most difficult challenges associated with the strategy of monitoring bioelectrical signals for diagnostic purposes. Moreover, since patients often have to cope with the problem of limited mobility being connected to bulky and mains-powered instruments, there is a growing demand for small-sized, high-performance and ambulatory biopotential acquisition systems in the Intensive Care Unit (ICU) and in High-dependency wards. Finally, to the best of our knowledge, there are no commercial, small, battery-powered, wearable and wireless recording-only instruments that claim the capability of recording electrocorticographic (ECoG) signals. Methods: To address this problem, we designed and developed a low-noise (8 nV/√Hz), eight-channel, battery-powered, wearable and wireless instrument (55 × 80 mm2). The performance of the realised instrument was assessed by conducting both ex vivo and in vivo experiments. Results: To provide ex vivo proof-of-function, a wide variety of high-quality bioelectrical signal recordings are reported, including electroencephalographic (EEG), electromyographic (EMG), electrocardiographic (ECG), acceleration signals, and muscle fasciculations. Low-noise in vivo recordings of weak local field potentials (LFPs), which were wirelessly acquired in real time using segmented deep brain stimulation (DBS) electrodes implanted in the thalamus of a non-human primate, are also presented. Conclusions: The combination of desirable features and capabilities of this instrument, namely its small size (~one business card), its enhanced recording capabilities, its increased processing capabilities, its manufacturability (since it was designed using discrete off-the-shelf components), the wide bandwidth it offers (0.5 – 500 Hz) and the plurality of bioelectrical signals it can precisely record, render it a versatile and reliable tool to be utilized in a wide range of applications and environments. |
Issue Date: | 10-Dec-2019 |
Date of Acceptance: | 26-Nov-2019 |
URI: | http://hdl.handle.net/10044/1/75400 |
DOI: | 10.1186/s12984-019-0629-2 |
ISSN: | 1743-0003 |
Publisher: | BioMed Central |
Start Page: | 1 |
End Page: | 24 |
Journal / Book Title: | Journal of NeuroEngineering and Rehabilitation |
Volume: | 16 |
Issue: | 1 |
Copyright Statement: | © 2019 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
Keywords: | Science & Technology Technology Life Sciences & Biomedicine Engineering, Biomedical Neurosciences Rehabilitation Engineering Neurosciences & Neurology Neurological disorders Bioelectrical signals Analog front-end High-performance Wearable Wireless Bioinstrumentation DEEP BRAIN-STIMULATION ATRIAL-FIBRILLATION AMPLIFIER DISORDERS DESIGN DEVICE Analog front-end Bioelectrical signals Bioinstrumentation High-performance Neurological disorders Wearable Wireless Animals Deep Brain Stimulation Electrodiagnosis Equipment Design Humans Signal Processing, Computer-Assisted Wearable Electronic Devices Wireless Technology Animals Humans Electrodiagnosis Deep Brain Stimulation Equipment Design Signal Processing, Computer-Assisted Wireless Technology Wearable Electronic Devices 0903 Biomedical Engineering 1109 Neurosciences Rehabilitation |
Publication Status: | Published |
Article Number: | 156 |
Online Publication Date: | 2019-12-10 |
Appears in Collections: | Bioengineering Faculty of Engineering |