Geometrical features for premature ventricular contraction recognition with analytic hierarchy process based machine learning algorithms selection.

BACKGROUND AND OBJECTIVE: Premature ventricular contraction is associated to the risk of coronary heart disease, and its diagnosis depends on a long time heart monitoring. For this purpose, monitoring through Holter devices is often used and computational tools can provide essential assistance to specialists. This paper presents a new premature ventricular contraction recognition method based on a simplified set of features, extracted from geometric figures constructed over QRS complexes (Q, R and S waves). METHODS: Initially, a preprocessing stage based on wavelet denoising electrocardiogram signal scaling is applied. Then, the signal is segmented taking into account the ventricular depolarization timing and a new set of geometrical features are extracted. In order to validate this approach, simulations encompassing eight different classifiers are presented. To select the best classifiers, a new methodology is proposed based on the Analytic Hierarchy Process. RESULTS: The best results, achieved with an Artificial Immune System, were 98.4%, 91.1% and 98.7% for accuracy, sensitivity and specificity, respectively. When artificial examples were generated to balance the dataset, the recognition performance increased to 99.0%, 98.5% and 99.5%, employing the Support Vector Machine classifier. CONCLUSIONS: The proposed approach is compared with some of latest references and results indicate its effectiveness as a method for recognizing premature ventricular contraction. Besides, the overall system presents low computation load.

Perception of a nursing team in the implantation of a reception with risk classification sector for pregnant women / Percepção da equipe de enfermagem sobre a implantação do setor de acolhimento com classificação de risco às gestantes

Abstract Objectives: to analyze the perception of a nursing team in the implantation of a Reception with Risk Classification (RRC) sector for pregnant women. Methods: a descriptive cross-sectional study with a qualitative approach performed in a private hospital and linked to the Public Health System in Feira de Santana city in Bahia State in 2016. 10 nursing team professionals participated in the study that provided direct care for the pregnant women who were in labor and in puerperium. A semi-structured questionnaire was applied with questions identifying and characterizing their sociodemographic profile and an interview addressing questions about RRC sector, the advantages of implanting RRC sector to care for the pregnant women in labor and the possible changes in the implantation in the professionals' routine. Results: the interviewees recognize that the RSRC is a way to administrate in the health services, reorganizing the work process, ensuring the quality of care, so its implementation is useful to differentiate care for pregnant women, with humanization and sensitivity, and create a bond among the professionals and the health users. Conclusions: the implementation of the RRC sector establishes improvement that ensures a relationship of trust among the health users and the professionals and the effectiveness of care for pregnancy emergencies and urgencies.

Resumo Objetivos: analisar a percepção da equipe de enfermagem sobre a implantação do setor de Acolhimento com Classificação de Risco (ACCR) às gestantes. Métodos: estudo transversal descritivo com abordagem qualitativa, realizado num hospital privado e conveniado ao Sistema Único de Saúde, na cidade de Feira de Santana- BA, em 2016. Participaram do estudo 10 profissionais da equipe de enfermagem que prestam assistência direta às gestantes em trabalho de parto e no puerpério. Foi aplicado um questionário semiestruturado contendo questões de identificação e caracterização do perfil sociodemográfico e uma entrevista abordando indagações sobre ACCR, as vantagens da implantação do setor de ACCR para a assistência às gestantes em trabalho de parto e as possíveis mudanças decorrentes desta implantação na rotina destes profissionais. Resultados: as entrevistadas reconhecem que o ACCR é um modo de operar nos serviços de saúde, reorganizando o processo de trabalho, garantindo a qualidade do atendimento, portanto sua implantação é necessária para uma assistência diferenciada às gestantes, com humanização e sensibilidade, e a formação de vínculo entre profissionais e usuários. Conclusões: a implantação do ACCR estabelece melhorias que garantem uma relação de confiança entre usuárias e profissionais e eficácia no atendimento às urgências e emergências gravídicas.

A wavelet-based method for power-line interference removal in ECG signals

Abstract Introduction The analysis of electrocardiogram (ECG) signals allows the experts to diagnosis several cardiac disorders. However, the accuracy of such diagnostic depends on the signals quality. In this paper it is proposed a simple method for power-line interference (PLI) removal based on the wavelet decomposition, without the use of thresholding techniques. Methods This method consists in identifying the ECG and noise frequency range for further zeroing wavelet detail coefficients in the subbands with no ECG coefficients in the frequency content. Afterward, the enhanced ECG signal is obtained by the inverse discrete wavelet transform (IDWT). In order to choose the wavelet function, several experiments were performed with synthetic signals with worse Signal-to-Noise Ratio (SNR). Results Considering the relative error metrics and runtime, the best wavelet function for denoising was Symlet 8. Twenty synthetic ECG signals with different features and eight real ECG signals, obtained in the Physionet Challenge 2011, were used in the experiments. Results show the advantage of the proposed method against thresholding and notch filter techniques, considering classical metrics of assessment. The proposed method performed better for 75% of the synthetic signals and for 100% of the real signals considering most of the evaluation measures, when compared with a thresholding technique. In comparison with the notch filter, the proposed method is better for all signals. Conclusion The proposed method can be used for PLI removal in ECG signals with superior performance than thresholding and notch filter techniques. Also, it can be applied for high frequencies denoising even without a priori frequencies knowledge.