The paper presents a hardware solution of the in vivo electrophysiological signals acquiring and processing, using a continuous data acquisition on PC. The originality of the paper comes from architecture proposal, with some new blocks, which selective amplify and filter biosignals. One of the major problems in the electrophysiological signals monitoring is the impossibility to record the weak signals from deep organs that are covered by noise and by strong cardiac or muscular artefact signals. The analogical processing block is based on a dynamic range compressor, containing the automatic gain control block, so that the high power signals are less amplified than the low components. The following block is a clipper since to capture all the transitions that escape from the dynamic range compressor. At clipper output a low-pass filter is connected since to abruptly cut the high specific bio-frequencies. The data vector recording is performing by strong internal resources microcontroller including ten bits A/D conversion port. Through some specific measurements and calibration the chain can be used to capture and then interprets the neuronal signal with well applications in public health monitoring like psychiatric disorders.
| Published in |
American Journal of Bioscience and Bioengineering (Volume 3, Issue 3-1)
This article belongs to the Special Issue Bio-Electronics: Biosensors, Biomedical Signal Processing, and Organic Engineering |
| DOI | 10.11648/j.bio.s.2015030301.13 |
| Page(s) | 14-21 |
| Creative Commons |
This is an Open Access article, 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 or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Healthcare, Compressor Technique, Bioinformatics, Signal Processing, Public Heath, Psychiatric
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APA Style
Florin Babarada, Cristian Ravariu, Dan Prelipceanu, Bogdan Patrichi, Daniela Manuc, et al. (2015). Electronic Tool Interferences with Electrophysiology for the Psychiatric Disorders Monitoring. American Journal of Bioscience and Bioengineering, 3(3-1), 14-21. https://doi.org/10.11648/j.bio.s.2015030301.13
ACS Style
Florin Babarada; Cristian Ravariu; Dan Prelipceanu; Bogdan Patrichi; Daniela Manuc, et al. Electronic Tool Interferences with Electrophysiology for the Psychiatric Disorders Monitoring. Am. J. BioSci. Bioeng. 2015, 3(3-1), 14-21. doi: 10.11648/j.bio.s.2015030301.13
AMA Style
Florin Babarada, Cristian Ravariu, Dan Prelipceanu, Bogdan Patrichi, Daniela Manuc, et al. Electronic Tool Interferences with Electrophysiology for the Psychiatric Disorders Monitoring. Am J BioSci Bioeng. 2015;3(3-1):14-21. doi: 10.11648/j.bio.s.2015030301.13
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Download@article{10.11648/j.bio.s.2015030301.13,
author = {Florin Babarada and Cristian Ravariu and Dan Prelipceanu and Bogdan Patrichi and Daniela Manuc and Aurora Salageanu and Iuliana Caras},
title = {Electronic Tool Interferences with Electrophysiology for the Psychiatric Disorders Monitoring},
journal = {American Journal of Bioscience and Bioengineering},
volume = {3},
number = {3-1},
pages = {14-21},
doi = {10.11648/j.bio.s.2015030301.13},
url = {https://doi.org/10.11648/j.bio.s.2015030301.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.bio.s.2015030301.13},
abstract = {The paper presents a hardware solution of the in vivo electrophysiological signals acquiring and processing, using a continuous data acquisition on PC. The originality of the paper comes from architecture proposal, with some new blocks, which selective amplify and filter biosignals. One of the major problems in the electrophysiological signals monitoring is the impossibility to record the weak signals from deep organs that are covered by noise and by strong cardiac or muscular artefact signals. The analogical processing block is based on a dynamic range compressor, containing the automatic gain control block, so that the high power signals are less amplified than the low components. The following block is a clipper since to capture all the transitions that escape from the dynamic range compressor. At clipper output a low-pass filter is connected since to abruptly cut the high specific bio-frequencies. The data vector recording is performing by strong internal resources microcontroller including ten bits A/D conversion port. Through some specific measurements and calibration the chain can be used to capture and then interprets the neuronal signal with well applications in public health monitoring like psychiatric disorders.},
year = {2015}
}
TY - JOUR T1 - Electronic Tool Interferences with Electrophysiology for the Psychiatric Disorders Monitoring AU - Florin Babarada AU - Cristian Ravariu AU - Dan Prelipceanu AU - Bogdan Patrichi AU - Daniela Manuc AU - Aurora Salageanu AU - Iuliana Caras Y1 - 2015/04/03 PY - 2015 N1 - https://doi.org/10.11648/j.bio.s.2015030301.13 DO - 10.11648/j.bio.s.2015030301.13 T2 - American Journal of Bioscience and Bioengineering JF - American Journal of Bioscience and Bioengineering JO - American Journal of Bioscience and Bioengineering SP - 14 EP - 21 PB - Science Publishing Group SN - 2328-5893 UR - https://doi.org/10.11648/j.bio.s.2015030301.13 AB - The paper presents a hardware solution of the in vivo electrophysiological signals acquiring and processing, using a continuous data acquisition on PC. The originality of the paper comes from architecture proposal, with some new blocks, which selective amplify and filter biosignals. One of the major problems in the electrophysiological signals monitoring is the impossibility to record the weak signals from deep organs that are covered by noise and by strong cardiac or muscular artefact signals. The analogical processing block is based on a dynamic range compressor, containing the automatic gain control block, so that the high power signals are less amplified than the low components. The following block is a clipper since to capture all the transitions that escape from the dynamic range compressor. At clipper output a low-pass filter is connected since to abruptly cut the high specific bio-frequencies. The data vector recording is performing by strong internal resources microcontroller including ten bits A/D conversion port. Through some specific measurements and calibration the chain can be used to capture and then interprets the neuronal signal with well applications in public health monitoring like psychiatric disorders. VL - 3 IS - 3-1 ER -
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