ABSTRACT
An ECG signal, generally filled with noise, when de-noised, enables a physician to effectively determine and predict the condition and health of the heart. This paper aims to address the issue of denoising a noisy ECG signal using the Fast Fourier Transform based bandpass filter. Multi-stage adaptive peak detection is then applied to identify the R-peak in the QRS complex of the ECG signal. The result of test simulations using the MIT/BIH Arrhythmia database shows high sensitivity and positive predictivity (PP) of 99.98 and 99.96% respectively, confirming the accuracy and reliability of proposed algorithm for detecting R-peaks in the ECG signal.
Subject(s)
Arrhythmias, Cardiac , Electrocardiography , Fourier Analysis , Heart , NoiseABSTRACT
The study of atrial fibrillation (AF) has been known as a hot topic of clinical concern. Body surface potential mapping (BSPM), a noninvasive electrical mapping technology, has been widely used in the study of AF. This study adopted 10 AF patients' preoperative and postoperative BSPM data (each patient's data contained 128 channels), and applied the autocorrelation function method to obtain the activation interval of the BSPM signals. The activation interval results were compared with that of manual counting method and the applicability of the autocorrelation function method was verified. Furthermore, we compared the autocorrelation function method with the commonly used fast Fourier transform (FFT) method. It was found that the autocorrelation function method was more accurate. Finally, to find a simple rule to predict the recurrence of atrial fibrillation, the autocorrelation function method was used to analyze the preoperative BSPM signals of 10 patients with persistent AF. Consequently, we found that if the patient's proportion of channels with dominant frequency larger than 2.5 Hz in the anterior left region is greater than the other three regions (the anterior right region, the posterior left region, and the posterior right region), he or she might have a higher possibility of AF recurrence. This study verified the rationality of the autocorrelation function method for rhythm analysis and concluded a simple rule of AF recurrence prediction based on this method.
ABSTRACT
Resumen Este trabajo presenta el desarrollo de un sistema de adquisición y procesamiento de señales mioeléctricas superficiales o SEMG. El sistema propuesto adquiere las señales SEMG de la superficie de la piel utilizando electrodos superficiales de AgCl. El sistema tiene una etapa de amplificación y de filtrado por hardware para eficientar el tiempo de proceso. Se desarrolló un software para procesar por transformada de Fourier la señal SEMG amplificada y filtrada. A diferencia de otros sistemas de adquisición de señales biológicas que son desarrollados para terapia o rehabilitación, este sistema está pensado para ser usado para el control de brazos robóticos, por ello el software desarrollado mide la fatiga utilizando parámetros como el corrimiento de la frecuencia media instantánea y la densidad espectral de potencia de la señal SEMG.
Abstract This paper presents the development of a system for acquiring and processing of surface myoelectric signals or SEMG. The proposed system acquires signals SEMG skin surface using AgCl surface electrodes. The system has an amplification step and hardware filtering to streamline the processing time. Developed software for processing the Fourier transform SEMG amplified and filtered signal. Unlike other systems for acquisition of biological signals, which are developed for therapy or rehabilitation, this system is intended to be used for the control of robotic arms, so the software performs the measurement of fatigue using parameters like bleed average frequency and instantaneous power spectral density of the signal SEMG.
ABSTRACT
PURPOSE: This pilot study was to find the influence of complete denture on the brain activity and cognitive function of edentulous patients measured through Electroencephalogram (EEG) signals. MATERIALS AND METHODS: The study recruited 20 patients aged from 50 to 60 years requiring complete dentures with inclusion and exclusion criteria. The brain function and cognitive function were analyzed with a mental state questionnaire and a 15-minute analysis of power spectral density of EEG alpha waves. The analysis included edentulous phase and post denture insertion adaptive phase, each done before and after chewing. The results obtained were statistically evaluated. RESULTS: Power Spectral Density (PSD) values increased from edentulous phase to post denture insertion adaption phase. The data were grouped as edentulous phase before chewing (EEG p1-0.0064), edentulous phase after chewing (EEG p2-0.0073), post denture insertion adaptive phase before chewing (EEG p3-0.0077), and post denture insertion adaptive phase after chewing (EEG p4-0.0096). The acquired values were statistically analyzed using paired t-test, which showed statistically significant results (P<.05). CONCLUSION: This pilot study showed functional improvement in brain function of edentulous patients with complete dentures rehabilitation.
Subject(s)
Humans , Brain , Denture, Complete , Dentures , Electroencephalography , Mastication , Pilot Projects , RehabilitationABSTRACT
The autonomic nervous system plays an important role in physiological and pathological conditions, and has been extensively evaluated by parametric and non-parametric spectral analysis. To compare the results obtained with fast Fourier transform (FFT) and the autoregressive (AR) method, we performed a comprehensive comparative study using data from humans and rats during pharmacological blockade (in rats), a postural test (in humans), and in the hypertensive state (in both humans and rats). Although postural hypotension in humans induced an increase in normalized low-frequency (LFnu) of systolic blood pressure, the increase in the ratio was detected only by AR. In rats, AR and FFT analysis did not agree for LFnu and high frequency (HFnu) under basal conditions and after vagal blockade. The increase in the LF/HF ratio of the pulse interval, induced by methylatropine, was detected only by FFT. In hypertensive patients, changes in LF and HF for systolic blood pressure were observed only by AR; FFT was able to detect the reduction in both blood pressure variance and total power. In hypertensive rats, AR presented different values of variance and total power for systolic blood pressure. Moreover, AR and FFT presented discordant results for LF, LFnu, HF, LF/HF ratio, and total power for pulse interval. We provide evidence for disagreement in 23 percent of the indices of blood pressure and heart rate variability in humans and 67 percent discordance in rats when these variables are evaluated by AR and FFT under physiological and pathological conditions. The overall disagreement between AR and FFT in this study was 43 percent.