Electroencephalography applied compression algorithms qualitative analysis. Saraiva, A., A., Castro, F., M., d., J., Nascimento, R., C., de Melo, R., T., Moura Sousa, J., V., Valente, A., & Fonseca Ferreira, N., M. Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, Taylor and Francis Ltd., 2019. doi abstract bibtex The objective of this work is study, implementation and evaluation of compression techniques used in bioelectrical signals, applied to electroencephalography. For that, the fundamental concepts of Fast Walsh Hadamard Transform (FWHT), the Discrete Cosine Transform (DCT) and the Discrete Wavelet Transform (DWT), in essence, the mathematical models were studied. In these systems, the applicability and principles of operation were considered the Peak Signal to Noise Ratio (PSNR), Signal to Noise Ratio (SNR), Mean Absolute Error (MAE) and mean squared error. Later, it is proposed the implementation of the compression algorithms. For the implementation of the techniques, computational tools of tests were developed, and for the purposes of validation and comparison of the results were used, with the appropriate adaptations, and described in the work, being these among the most recognised in terms of evaluation of signal quality. Finally, we present the results and the conclusions, where we sought a compromise of the implementations between the estimated percentage of DCT and the level of degradation of the signal provided by the compression application. In this sense, it was verified that they presented satisfactory results.
@article{
title = {Electroencephalography applied compression algorithms qualitative analysis},
type = {article},
year = {2019},
keywords = {Compression,algorithms,electroencephalography,signal},
publisher = {Taylor and Francis Ltd.},
id = {96ed4058-5ff2-395d-8a83-89f8032345f6},
created = {2020-04-13T12:29:15.225Z},
accessed = {2020-04-13},
file_attached = {false},
profile_id = {8f53583f-94e1-3d98-83ad-e84ae5eab9e4},
last_modified = {2020-04-13T13:09:54.806Z},
read = {false},
starred = {false},
authored = {true},
confirmed = {false},
hidden = {false},
folder_uuids = {82814afd-f83c-46c7-a954-4e1461dc16f7},
private_publication = {false},
abstract = {The objective of this work is study, implementation and evaluation of compression techniques used in bioelectrical signals, applied to electroencephalography. For that, the fundamental concepts of Fast Walsh Hadamard Transform (FWHT), the Discrete Cosine Transform (DCT) and the Discrete Wavelet Transform (DWT), in essence, the mathematical models were studied. In these systems, the applicability and principles of operation were considered the Peak Signal to Noise Ratio (PSNR), Signal to Noise Ratio (SNR), Mean Absolute Error (MAE) and mean squared error. Later, it is proposed the implementation of the compression algorithms. For the implementation of the techniques, computational tools of tests were developed, and for the purposes of validation and comparison of the results were used, with the appropriate adaptations, and described in the work, being these among the most recognised in terms of evaluation of signal quality. Finally, we present the results and the conclusions, where we sought a compromise of the implementations between the estimated percentage of DCT and the level of degradation of the signal provided by the compression application. In this sense, it was verified that they presented satisfactory results.},
bibtype = {article},
author = {Saraiva, Aratã Andrade and Castro, Felipe Miranda de Jesus and Nascimento, Renato Conceição and de Melo, Rodrigo Teixeira and Moura Sousa, José Vigno and Valente, Antonio and Fonseca Ferreira, Nuno Miguel},
doi = {10.1080/21681163.2019.1673212},
journal = {Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization}
}
Downloads: 0
{"_id":"hscjgpvNNxN5ZNyxQ","bibbaseid":"saraiva-castro-nascimento-demelo-mourasousa-valente-fonsecaferreira-electroencephalographyappliedcompressionalgorithmsqualitativeanalysis-2019","author_short":["Saraiva, A., A.","Castro, F., M., d., J.","Nascimento, R., C.","de Melo, R., T.","Moura Sousa, J., V.","Valente, A.","Fonseca Ferreira, N., M."],"bibdata":{"title":"Electroencephalography applied compression algorithms qualitative analysis","type":"article","year":"2019","keywords":"Compression,algorithms,electroencephalography,signal","publisher":"Taylor and Francis Ltd.","id":"96ed4058-5ff2-395d-8a83-89f8032345f6","created":"2020-04-13T12:29:15.225Z","accessed":"2020-04-13","file_attached":false,"profile_id":"8f53583f-94e1-3d98-83ad-e84ae5eab9e4","last_modified":"2020-04-13T13:09:54.806Z","read":false,"starred":false,"authored":"true","confirmed":false,"hidden":false,"folder_uuids":"82814afd-f83c-46c7-a954-4e1461dc16f7","private_publication":false,"abstract":"The objective of this work is study, implementation and evaluation of compression techniques used in bioelectrical signals, applied to electroencephalography. For that, the fundamental concepts of Fast Walsh Hadamard Transform (FWHT), the Discrete Cosine Transform (DCT) and the Discrete Wavelet Transform (DWT), in essence, the mathematical models were studied. In these systems, the applicability and principles of operation were considered the Peak Signal to Noise Ratio (PSNR), Signal to Noise Ratio (SNR), Mean Absolute Error (MAE) and mean squared error. Later, it is proposed the implementation of the compression algorithms. For the implementation of the techniques, computational tools of tests were developed, and for the purposes of validation and comparison of the results were used, with the appropriate adaptations, and described in the work, being these among the most recognised in terms of evaluation of signal quality. Finally, we present the results and the conclusions, where we sought a compromise of the implementations between the estimated percentage of DCT and the level of degradation of the signal provided by the compression application. In this sense, it was verified that they presented satisfactory results.","bibtype":"article","author":"Saraiva, Aratã Andrade and Castro, Felipe Miranda de Jesus and Nascimento, Renato Conceição and de Melo, Rodrigo Teixeira and Moura Sousa, José Vigno and Valente, Antonio and Fonseca Ferreira, Nuno Miguel","doi":"10.1080/21681163.2019.1673212","journal":"Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization","bibtex":"@article{\n title = {Electroencephalography applied compression algorithms qualitative analysis},\n type = {article},\n year = {2019},\n keywords = {Compression,algorithms,electroencephalography,signal},\n publisher = {Taylor and Francis Ltd.},\n id = {96ed4058-5ff2-395d-8a83-89f8032345f6},\n created = {2020-04-13T12:29:15.225Z},\n accessed = {2020-04-13},\n file_attached = {false},\n profile_id = {8f53583f-94e1-3d98-83ad-e84ae5eab9e4},\n last_modified = {2020-04-13T13:09:54.806Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n folder_uuids = {82814afd-f83c-46c7-a954-4e1461dc16f7},\n private_publication = {false},\n abstract = {The objective of this work is study, implementation and evaluation of compression techniques used in bioelectrical signals, applied to electroencephalography. For that, the fundamental concepts of Fast Walsh Hadamard Transform (FWHT), the Discrete Cosine Transform (DCT) and the Discrete Wavelet Transform (DWT), in essence, the mathematical models were studied. In these systems, the applicability and principles of operation were considered the Peak Signal to Noise Ratio (PSNR), Signal to Noise Ratio (SNR), Mean Absolute Error (MAE) and mean squared error. Later, it is proposed the implementation of the compression algorithms. For the implementation of the techniques, computational tools of tests were developed, and for the purposes of validation and comparison of the results were used, with the appropriate adaptations, and described in the work, being these among the most recognised in terms of evaluation of signal quality. Finally, we present the results and the conclusions, where we sought a compromise of the implementations between the estimated percentage of DCT and the level of degradation of the signal provided by the compression application. In this sense, it was verified that they presented satisfactory results.},\n bibtype = {article},\n author = {Saraiva, Aratã Andrade and Castro, Felipe Miranda de Jesus and Nascimento, Renato Conceição and de Melo, Rodrigo Teixeira and Moura Sousa, José Vigno and Valente, Antonio and Fonseca Ferreira, Nuno Miguel},\n doi = {10.1080/21681163.2019.1673212},\n journal = {Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization}\n}","author_short":["Saraiva, A., A.","Castro, F., M., d., J.","Nascimento, R., C.","de Melo, R., T.","Moura Sousa, J., V.","Valente, A.","Fonseca Ferreira, N., M."],"biburl":"https://bibbase.org/service/mendeley/8f53583f-94e1-3d98-83ad-e84ae5eab9e4","bibbaseid":"saraiva-castro-nascimento-demelo-mourasousa-valente-fonsecaferreira-electroencephalographyappliedcompressionalgorithmsqualitativeanalysis-2019","role":"author","urls":{},"keyword":["Compression","algorithms","electroencephalography","signal"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"article","biburl":"https://bibbase.org/service/mendeley/8f53583f-94e1-3d98-83ad-e84ae5eab9e4","dataSources":["2252seNhipfTmjEBQ"],"keywords":["compression","algorithms","electroencephalography","signal"],"search_terms":["electroencephalography","applied","compression","algorithms","qualitative","analysis","saraiva","castro","nascimento","de melo","moura sousa","valente","fonseca ferreira"],"title":"Electroencephalography applied compression algorithms qualitative analysis","year":2019}