{"id":{"repo_id":"brazil-uerj","oai_identifier":"oai:pantheon.ufrj.br:11422/8330"},"canonical_url":"https://search.dev.ndltd.org/etd/brazil-uerj/oai:pantheon.ufrj.br:11422/8330","repository":{"repo_id":"brazil-uerj","name":"Brazil UERJ","base_url":"https://pantheon.ufrj.br/oai/request"},"display":{"title":"Redução do Eletroencefalograma durante monitorização contínua de paciente crítico","abstract":"\"[ENG] This work aimed to apply the Hilbert Transform to the Electroencephalogram (EEG) data reduction. The scope of this work was to analyze differences between two EEG reduction methods, amplitude-integrated EEG (aEEG) and Hilbert aEEG (HaEEG). The main difference is in the signal envelope obtention: the aEEG uses a 5th - order Butterworth lowpass filter, and the HaEEG uses the analytical signal module of Discrete Hilbert Transform (DHT). One aimed at investigating the use of DHT to obtain the envelope in EEG reduction; to compare different parameters to obtaining the envelope using the Butterworth filter; to analyze and to compare the Butterworth and Hilbert envelopes; and to compare the filtering of HaEEG signal within the band 2- 15 Hz and within 1 and 70 Hz. The methodology consisted of evaluating the Butterworth filter order and the scaling parameter for the aEEG by means of a known signal, to visually compare aEEG and HaEEG in the same frequency range (2 to 15 Hz) and to compare HaEEG in frequency ranges 2 to 15 Hz and 1 to 70 Hz. One fulfilled the comparison between segments of 15 s of raw signal, 2-15 Hz and 1-70 Hz filtered signal, and between the respective envelopes, of the aEEG and HaEEG. In conclusion the Hilbert Transform is an effective method to reduce EEG signals. The aEEG envelope is better obtained by means of 2nd order Butterworth using Square Law and No Gain. Hilbert envelope resembles the original signal and highlights better the seizure segments in relation to background activity compared to Butterworth. The frequency range within 2-15 Hz can omit epileptic characteristics.\"","abstract_html":""[ENG] This work aimed to apply the Hilbert Transform to the Electroencephalogram (EEG) data reduction. The scope of this work was to analyze differences between two EEG reduction methods, amplitude-integrated EEG (aEEG) and Hilbert aEEG (HaEEG). The main difference is in the signal envelope obtention: the aEEG uses a 5th - order Butterworth lowpass filter, and the HaEEG uses the analytical signal module of Discrete Hilbert Transform (DHT). One aimed at investigating the use of DHT to obtain the envelope in EEG reduction; to compare different parameters to obtaining the envelope using the Butterworth filter; to analyze and to compare the Butterworth and Hilbert envelopes; and to compare the filtering of HaEEG signal within the band 2- 15 Hz and within 1 and 70 Hz. The methodology consisted of evaluating the Butterworth filter order and the scaling parameter for the aEEG by means of a known signal, to visually compare aEEG and HaEEG in the same frequency range (2 to 15 Hz) and to compare HaEEG in frequency ranges 2 to 15 Hz and 1 to 70 Hz. One fulfilled the comparison between segments of 15 s of raw signal, 2-15 Hz and 1-70 Hz filtered signal, and between the respective envelopes, of the aEEG and HaEEG. In conclusion the Hilbert Transform is an effective method to reduce EEG signals. The aEEG envelope is better obtained by means of 2nd order Butterworth using Square Law and No Gain. Hilbert envelope resembles the original signal and highlights better the seizure segments in relation to background activity compared to Butterworth. The frequency range within 2-15 Hz can omit epileptic characteristics."","abstract_has_math":false,"creators":["Santos, Talita Endriely Batista dos"],"institution":"Universidade Federal do Rio de Janeiro","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Cagy, Maurício"],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-03","date_published":"2017-03","updated_at":"2026-07-24T01:16:26Z","subjects":["Engenharia biomédica","HaEEG","aEEG","Monitorização contínua","Transformada de Hilbert","Redução de dados"],"languages":["por"],"rights":["Acesso Aberto"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11422/8330","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Cagy, Maurício"]},{"key":"dc:creator","label":"Author","values":["Santos, Talita Endriely Batista dos"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2019-06-06T17:53:36Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-05-16T03:05:44Z"]},{"key":"dc:date.issued","label":"Date","values":["2017-03"]},{"key":"dc:publisher","label":"Institution","values":["Universidade Federal do Rio de Janeiro"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia"]},{"key":"dc:type","label":"Dc Type","values":["Dissertação"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engenharia biomédica","HaEEG","aEEG","Monitorização contínua","Transformada de Hilbert","Redução de dados"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["por"]},{"key":"dc:rights","label":"Dc Rights","values":["Acesso Aberto"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11422/8330"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["\"[ENG] This work aimed to apply the Hilbert Transform to the Electroencephalogram (EEG) data reduction. The scope of this work was to analyze differences between two EEG reduction methods, amplitude-integrated EEG (aEEG) and Hilbert aEEG (HaEEG). The main difference is in the signal envelope obtention: the aEEG uses a 5th - order Butterworth lowpass filter, and the HaEEG uses the analytical signal module of Discrete Hilbert Transform (DHT). One aimed at investigating the use of DHT to obtain the envelope in EEG reduction; to compare different parameters to obtaining the envelope using the Butterworth filter; to analyze and to compare the Butterworth and Hilbert envelopes; and to compare the filtering of HaEEG signal within the band 2- 15 Hz and within 1 and 70 Hz. The methodology consisted of evaluating the Butterworth filter order and the scaling parameter for the aEEG by means of a known signal, to visually compare aEEG and HaEEG in the same frequency range (2 to 15 Hz) and to compare HaEEG in frequency ranges 2 to 15 Hz and 1 to 70 Hz. One fulfilled the comparison between segments of 15 s of raw signal, 2-15 Hz and 1-70 Hz filtered signal, and between the respective envelopes, of the aEEG and HaEEG. In conclusion the Hilbert Transform is an effective method to reduce EEG signals. The aEEG envelope is better obtained by means of 2nd order Butterworth using Square Law and No Gain. Hilbert envelope resembles the original signal and highlights better the seizure segments in relation to background activity compared to Butterworth. The frequency range within 2-15 Hz can omit epileptic characteristics.\""]},{"key":"dc:title","label":"Title","values":["Redução do Eletroencefalograma durante monitorização contínua de paciente crítico"]}]}],"canonical_facts":{"dc:contributor.advisor":["Cagy, Maurício"],"dc:creator":["Santos, Talita Endriely Batista dos"],"dc:date.accessioned":["2019-06-06T17:53:36Z"],"dc:date.available":["2026-05-16T03:05:44Z"],"dc:date.issued":["2017-03"],"dc:description.abstract":["\"[ENG] This work aimed to apply the Hilbert Transform to the Electroencephalogram (EEG) data reduction. The scope of this work was to analyze differences between two EEG reduction methods, amplitude-integrated EEG (aEEG) and Hilbert aEEG (HaEEG). The main difference is in the signal envelope obtention: the aEEG uses a 5th - order Butterworth lowpass filter, and the HaEEG uses the analytical signal module of Discrete Hilbert Transform (DHT). One aimed at investigating the use of DHT to obtain the envelope in EEG reduction; to compare different parameters to obtaining the envelope using the Butterworth filter; to analyze and to compare the Butterworth and Hilbert envelopes; and to compare the filtering of HaEEG signal within the band 2- 15 Hz and within 1 and 70 Hz. The methodology consisted of evaluating the Butterworth filter order and the scaling parameter for the aEEG by means of a known signal, to visually compare aEEG and HaEEG in the same frequency range (2 to 15 Hz) and to compare HaEEG in frequency ranges 2 to 15 Hz and 1 to 70 Hz. One fulfilled the comparison between segments of 15 s of raw signal, 2-15 Hz and 1-70 Hz filtered signal, and between the respective envelopes, of the aEEG and HaEEG. In conclusion the Hilbert Transform is an effective method to reduce EEG signals. The aEEG envelope is better obtained by means of 2nd order Butterworth using Square Law and No Gain. Hilbert envelope resembles the original signal and highlights better the seizure segments in relation to background activity compared to Butterworth. The frequency range within 2-15 Hz can omit epileptic characteristics.\""],"dc:identifier.uri":["http://hdl.handle.net/11422/8330"],"dc:language":["por"],"dc:publisher":["Universidade Federal do Rio de Janeiro"],"dc:publisher.department":["Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia"],"dc:rights":["Acesso Aberto"],"dc:subject":["Engenharia biomédica","HaEEG","aEEG","Monitorização contínua","Transformada de Hilbert","Redução de dados"],"dc:title":["Redução do Eletroencefalograma durante monitorização contínua de paciente crítico"],"dc:type":["Dissertação"]},"updated_at":"2026-07-24T01:16:26Z"}