Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2017. / Submitted by Raquel Almeida (raquel.df13@gmail.com) on 2018-03-09T21:40:22Z
No. of bitstreams: 1
2017_LuisaSantiagoContreirasBritodaSilva.pdf: 4732963 bytes, checksum: ed2a7969fde70fe3b2349be5930d780e (MD5) / Approved for entry into archive by Raquel Viana (raquelviana@bce.unb.br) on 2018-03-13T19:47:49Z (GMT) No. of bitstreams: 1
2017_LuisaSantiagoContreirasBritodaSilva.pdf: 4732963 bytes, checksum: ed2a7969fde70fe3b2349be5930d780e (MD5) / Made available in DSpace on 2018-03-13T19:47:49Z (GMT). No. of bitstreams: 1
2017_LuisaSantiagoContreirasBritodaSilva.pdf: 4732963 bytes, checksum: ed2a7969fde70fe3b2349be5930d780e (MD5)
Previous issue date: 2018-03-13 / Fundação de Apoio à Pesquisa do Distrito Federal (FAP-DF). / A dinâmica entre a PA e a FC é de malha fechada, na qual a PA influencia a FC através do baroreflexo e a FC influencia a PA através da dinâmica circulatória. A respiração exerce uma influência direta sobre a FC que é mediada pelo SNA, chamada de acoplamento cardiorrespiratório (ACR), e também um efeito mecânico indireto mediado pelo baroreflexo. Enquanto análises espectrais univariáveis e bivariáveis podem ser usadas para avaliar esses mecanismos, são técnicas de malha aberta que são incapazes de diferenciar efeitos de retroalimentação dos efeitos de alimentação direta e também de separar o ACR das influências indiretas da respiração na FC. Para lidar com essas limitações, uma abordagem de identificação de sistemas foi aplicada. O CRSIDLab implementa três modelos: o modelo AR com entradas exógenas (ARX), o modelo de funções de base de Laguerre (FBL) e o modelo de funções de base de Meixner (FBM). As respostas ao impulso, que caracterizam a dinâmica entre cada par de variáveis, são calculadas a partir do modelo estimado. Esses modelos são capazes de isolar o ACR ao considerar ambos VPI e PAS como entradas e conseguem abrir a malha do baroreflexo computacionalmente pela imposição de atrasos entre a PAS e o IRR, caracterizando a resposta ao impulso do baroreflexo arterial (BRA). A partir dessas análises, não só o ganho em cada banda de frequência é fornecido através da transformada de Fourier da resposta ao impulso, mas também informações temporais como o atraso entre duas variáveis. Os resultados mostram que ficar de pé é acompanhado por uma supressão vagal e tom vascular simpático aumentado. Análises de correlação mostraram que as estimativas de ASR e SBR baseadas em análises espectrais não apresentam a mesma informação que as estimativas baseadas no modelo de ACR e BRA. As diferenças encontradas sugerem que as análises baseadas em modelo são efetivas em representar o ACR como uma medida dos efeitos diretos da respiração na FC e o BRA como expressão do baroreflexo independente da dinâmica circulatória. Assim, o CRSIDLab é uma ferramenta poderosa para a determinação não-invasiva de diferentes indicadores quantitativos do SNA. Os resultados mostram que os indicadores estimados refletem a fisiologia subjacente, pois ficar de pé é um estímulo simpático que deveria levar a supressão vagal, conforme observado. Os resultados obtidos também mostram que a abordagem de modelagem de sistemas multivariáveis pode fornecer importantes informações adicionais àquelas encontradas pelas abordagens espectrais mais tradicionais, podendo levar a indicadores quantitativos mais específicos do SNA. / The autonomic nervous system (ANS) controls the involuntary functions of the body and its imbalance has been linked to increased risk of cardiac mortality. Heart rate variability (HRV) analysis is usually employed as a non-invasive method for assessing ANS modulation. Traditional measures of HRV are based on the analysis of the beat-to-beat oscillations in heart rate (or its reciprocal, the interval between consecutive R waves on the electrocardiogram - RRI), since heart rate (HR) rhythm is a consequence of sympathetic and parasympathetic activity on the sinoatrial node of the heart. However, these oscillations in beat-to-beat HR are also influenced by mechanisms, such as baroreflex and respiratory sinus arrhythmia (RSA), that affect HRV. Therefore, in this work, a multivariate analysis of the cardiorespiratory system is used. This study consists of two parts: the development of the cardiorespiratory system identification lab (CRSIDLab), a Matlab graphical user interface that provides quantitative indicators of ANS activity from a multivariate system model analysis of cardiorespiratory data, followed by its application on data obtained from subjects in supine and standing postures, illustrating its capabilities. Electrocardiogram (ECG), continuous blood pressure (BP) and airflow were recorded from 23 subjects in supine and standing postures for 10 min and preprocessed on CRSIDLab. In this work the classical HRV and BP variability (BPV) analyses were performed though power spectral density (PSD) analysis of the RRI and the systolic BP (SBP), respectively. CRSIDLab implements three methods for spectral analysis: the Fourier transform, Welch method and AR model. All methods were used to calculate the power of the low frequency (LF: 0.04-0.15 Hz) and high frequency (HF: 0.15-0.4 Hz) bands, as the areas under the PSD curve. For the HRV, the LF/HF ratio was also calculated. Traditional baroreflex sensitivity (BRS) estimates were calculated from the relation between HRV and BPV in the LF and HF regions. Spectral transfer functions were estimated between SBP and RRI, characterizing baroreflex, and between instantaneous lung volume (ILV, derived from the airflow record) and RRI, characterizing RSA, or the effects of respiration on HR, for the determination of the LF and HF gains. BRS was estimated from the gains of the transfer function between SBP and RRI.The dynamics between BP and HR are closed-loop, where BP influences HR through baroreflex and HR influences BP through circulatory dynamics. Respiration has a direct influence on HR that is mediated through the ANS, called the respiratory-cardiac coupling (RCC), and also a mechanical indirect effect mediated through baroreflex. While univariate and bivariate spectral analyses can be used to assess these effects, they are open-loop techniques that are unable to differentiate feedforward from feedback effects and also to separate RCC from the indirect effects of respiration on HR. To address these limitations a system model identification approach was applied. CRSIDLab implements three types of models: the autoregressive with exogenous inputs (ARX) model, the Laguerre basis function (LBF) model, and the Meixner basis function (MBF) model. The impulse responses, which characterize the dynamics between each pair of variables, are calculated from the estimated model. These multivariate models are able to isolate RCC by considering both SBP and ILV as system inputs and are able to computationally open the baroreflex loop through the imposition of time delays between SBP and RRI, characterizing the arterial baroreflex (ABR) impulse response. From this analysis not only the gain for each frequency band is provided from the Fourier transform of the impulse response, but also temporal information such as delays between variables. The results show that standing is accompanied by significant vagal withdrawal and increased sympathetic vascular tone. Correlation analyses showed that the spectral-based RSA and BRS estimates do not present the same information as the model-based RCC and ABR estimates. The differences found suggest the model-based analyses are effective in representing RCC as a measure of the direct effects of respiration on HR and ABR as an expression of baroreflex that is independent from circulatory dynamics. Thus, CRSIDLab is a powerful tool for the non-invasive determination of different quantitative indicators of the ANS. The results show that all estimated indicators reflect the underlying physiology, in the sense that standing is a sympathetic stimulus that should lead to vagal withdrawal, as observed. The results obtained also show that the multivariate system modeling approach can provide important additional information to those found by the more traditional spectral analyses approaches, which could potentially lead to more specific quantitative indicators of the ANS.
Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.unb.br:10482/31424 |
Date | 27 November 2017 |
Creators | Silva, Luisa Santiago Contreiras Brito da |
Contributors | Oliveira, Flavia Maria Guerra de Sousa Aranha |
Source Sets | IBICT Brazilian ETDs |
Language | Inglês |
Detected Language | English |
Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
Source | reponame:Repositório Institucional da UnB, instname:Universidade de Brasília, instacron:UNB |
Rights | A concessão da licença deste item refere-se ao termo de autorização impresso assinado pelo autor com as seguintes condições: Na qualidade de titular dos direitos de autor da publicação, autorizo a Universidade de Brasília e o IBICT a disponibilizar por meio dos sites www.bce.unb.br, www.ibict.br, http://hercules.vtls.com/cgi-bin/ndltd/chameleon?lng=pt&skin=ndltd sem ressarcimento dos direitos autorais, de acordo com a Lei nº 9610/98, o texto integral da obra disponibilizada, conforme permissões assinaladas, para fins de leitura, impressão e/ou download, a título de divulgação da produção científica brasileira, a partir desta data., info:eu-repo/semantics/openAccess |
Page generated in 0.002 seconds