Hsiao-Lung Chan

A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising

In this paper, a simple moving average-based computing method for real-time QRS detection is proposed. In addition, for signal preprocessing our detection algorithm also incorporates a wavelet-based denoising procedure to effectively reduce the noise level for electrocardiogram (ECG) data. The overall computational structure of the proposed algorithm allows the QRS detection to be performed and implemented in real-time with high time- and memory-efficiency. Algorithm performance was evaluated against the MIT-BIH Arrhythmia Database. The numerical results indicated that the novel algorithm finally achieved about 99.5% of the detection rate for the standard database, and also, it could function reliably even under the condition of poor signal quality in the measured ECG data.

Tight Mechanism Correlation Between Heart Rate Turbulence and Baroreflex Sensitivity: Sequential Autonomic Blockade Analysis

Heart Rate Turbulence and Baroreflex Sensitivity. Introduction: Heart rate turbulence is a powerful de novo risk predictor for patients surviving acute myocardial infarction. However, little is known about its underlying physiologic mechanism.

Human identification by quantifying similarity and dissimilarity in electrocardiogram phase space

Specific patterns of electrocardiogram (ECG), along with other biometrics, have recently been used to recognize a person. Most ECG-based human identification methods rely on the reduced features derived from ECG characteristic points and supervised classification. However, detecting characteristic points is an arduous procedure, particularly at low signal-to-noise ratios. The supervised classifier requires retraining when a new person is included in the group. In the present study, we propose a novel unsupervised ECG-based identification method based on phase space reconstruction of one-lead or three-lead ECG, saving from picking up characteristic points. Identification is performed by inspecting similarity or dissimilarity measure between ECG phase space portraits. Our results in a 100-subject group showed that one-lead ECG reached identification rate at 93% accuracy and three-lead ECG acquired 99% accuracy.

Complexity of subthalamic 13-35 Hz oscillatory activity directly correlates with clinical impairment in patients with Parkinson's disease.

Excessive synchronization of the basal ganglia neuronal activity in the 13- to 35-Hz frequency band, so-called beta activity, has been associated with the motor deficits of Parkinsons disease (PD). Studies have demonstrated that beta activity may be suppressed by treatment with dopaminergic medication and high-frequency stimulation of the subthalamic nucleus (STN), with the degree of suppression correlating with clinical improvement. However, these studies failed to demonstrate any correlation between beta activity of parkinsonism in the resting, untreated state. This argues against a significant relationship between beta activity and motor impairment. Here we use an advanced nonlinear dynamical analysis method based on the Lempel-Ziv estimator to show frequency band and symptom-subset specific correlations between STN local field potential (LFP) complexity and motor impairment in PD patients. Oscillatory activity has a reduced complexity, and we found a strong negative correlation between the complexity of the STN LFP over the 13- to 35-Hz frequency range and akinesia-rigidity. There was no such correlation with tremor. Furthermore, there was no correlation between LFP Lempel-Ziv complexity (LZC) over the 0- to 12-Hz frequency band and any parkinsonian motor impairment. The results strengthen the association between the dynamic structure of synchonised (LFP) activity in the beta frequency band in the STN and akinesia-rigidity.

Long-term β-blocker therapy improves autonomic nervous regulation in advanced congestive heart failure: A longitudinal heart rate variability study ☆ ☆☆

BACKGROUND beta-Blocker therapy is believed to modulate the detrimental effect of overcompensating neurohormonal activation in chronic heart failure. However, clinical doubts remain, particularly the physiologic sympathovagal balance. METHODS To respond to clinical concern about worsening autonomic nervous perturbation in beta-blocker therapy of advanced congestive heart failure, 15 consecutive patients were longitudinally studied to elucidate the evolution of cardiac function versus 24-hour heart rate variability (HRV) before and after 1, 3, and 6 to 9 months of atenolol-combined therapy. RESULTS Two patients died prematurely within 1 month. All 13 surviving patients showed improvement in New York Heart Association functional class, with decrease in left ventricular end-systolic and end-diastolic dimensions and increase in fraction shortening and ejection fraction by echocardiography after at least 3 months of atenolol use. The retarded therapeutic effect was accompanied by a general rise of total, very low, low-, and high-frequency components (9.0 +/- 0.5, 8.8 +/- 0.5, 6.2 +/- 0.6, and 6.1 +/- 0.5 vs 10.9 +/- 0.3, 10.7 +/- 0.4, 8.6 +/- 0.3, and 7.8 +/- 0.3; all P <.02) of daily HRV. This implied recovery of parasympathetic and baroreceptor function. Return of sympathovagal interaction was further supported by the suppression of Cheyne-Stokes type HRV as detected by Wigner-Ville distribution. CONCLUSIONS Long-term beta-blocker therapy for advanced congestive heart failure upwardly regulates the autonomic nervous interaction in synchrony with the evolution of cardiac function performance.

Stimulation of the subthalamic region at 20Hz slows the development of grip force in Parkinson's disease

Excessive synchronization of basal ganglia neuronal activity at ~20 Hz is characteristic of patients with untreated Parkinsons disease (PD). Correlative evidence suggests that this activity may contribute to bradykinesia. Attempts to demonstrate causality through stimulation imposed synchronization at 20 Hz in the region of the subthalamic nucleus (STN) have had limited success. Finger-tapping is slowed by about 8% and only in those PD patients that have a relatively normal baseline performance in this task. Here we investigate whether greater performance decrements might be seen in a reaction time grip task. We studied 32 sides in 16 patients with PD after overnight withdrawal of medication. Patients were asked to grip as hard and as fast as possible without STN stimulation and during bilateral stimulation at 5 Hz, 10 Hz, 20 Hz, 50 Hz and 130 Hz. Stimulation at 20 Hz slowed the development of force by 14.7±8.3% (P=0.044) across all patients. Slowing increased by 22±7% (P=0.005) in those patients with the best performance in the task without stimulation. The effect was frequency specific. These data provide direct interventional evidence of a mechanistic link between excessive neuronal synchronization in the beta range and motor impairment in PD.

Time-frequency analysis of heart rate variability during transient segments

AbstractThe spectral characteristics of heart rate variability (HRV) are related to the modulation of the autonomic nervous system. As the physiological condition is changed by such external stimuli such as drugs, postural changes, and anesthesia, or by internal deregulation such as in syncope, adjective autonomic responses could alter HRV characteristics. Time-frequency analysis is commonly used to investigate the time-related HRV characteristics. An alteration of the autonomic regulation resulting in a change in mean heart rate induces a transient component in heart rate, which, with any analysis method based on signals from multiple beats, results in the apparent spread of the spectrum of frequencies. This obscures the spectral components related to the autonomic function. In this paper we investigated the influence of the transient component in several time-frequency methods including the short-time Fourier transform, the Choi-Williams distribution, the smoothed pseudo Wigner–Ville distribution (SPWVD), the filtering SPWVD compensation, and the discrete wavelet transform. One simulated signal and two heart rate signals during general anesthesia and postural change were used for this assessment. The result demonstrates that the filtering SPWVD compensation and the discrete wavelet transform have small spectrum interference from the transient component.

A comparison of automatic fall detection by the cross-product and magnitude of tri-axial acceleration

Falling is an important problem in the health maintenance of people above middle age. Portable accelerometer systems have been designed to detect falls. However, false alarms induced by some dynamic motions, such as walking and jumping, are difficult to avoid. Acceleration cross-product (AC)-related methods are proposed and examined by this study to seek solutions for detecting falls with less motion-evoked false alarms. A set of tri-axial acceleration data is collected during simulated falls, posture transfers and dynamic activities by wireless sensors for making methodological comparisons. The performance of fall detection is evaluated in aspects of parameter comparison, threshold selection, sensor placement and post-fall posture (PP) recruitment. By parameter comparison, AC leads to a larger area under the receiver operating characteristic (ROC) curve than acceleration magnitude (AM). Three strategies of threshold selection, for 100% sensitivity (Sen100), for 100% specificity (Spe100) and for the best sum (BS) of sensitivity and specificity, are evaluated. Selecting a threshold based on Sen100 and BS leads to more practicable results. Simultaneous data recording from sensors in the chest and waist is performed. Fall detection based on the data from the chest shows better global accuracy. PP recruitment leads to lower false alarm ratios (FR) for both AC- and AM-based methods.

Correlates of the shift in heart rate variability with postures and walking by time-frequency analysis

Heart rate (HR) variability derived from electrocardiogram (ECG) can be used to assess the function of the autonomic nervous system. HR exhibits various characteristics during different physical activities attributed to the altered autonomic mediation, where it is also beneficial to reveal the autonomic shift in response to physical-activity change. In this paper, the physical-activity-related HR behaviors were delineated using a portable ECG and body acceleration recorder based on a personal digital assistant and the smoothed pseudo Wigner-Ville distribution. The results based upon eighteen subjects performing four sequential 5-min physical activities (supine, sitting, standing and spontaneous walking) showed that the high-frequency heartbeat fluctuations during supine and sitting were significantly larger than during standing, and that the ratio of low- to high-frequency fluctuation during standing was significantly higher than during supine and sitting. This could be linked with the parasympathetic predominance during supine and sitting, and a shift to sympathetic dominance while standing. During spontaneous walking, the high-frequency fluctuation was significant lower than during supine. The low- to high-frequency ratio decreased significantly from standing to spontaneous walking, which may imply an increased vagal predominance (autonomic effect) or an increased respiratory activity (mechanical effect).

Detection of neuronal spikes using an adaptive threshold based on the max–min spread sorting method

Neuronal spike information can be used to correlate neuronal activity to various stimuli, to find target neural areas for deep brain stimulation, and to decode intended motor command for brain-machine interface. Typically, spike detection is performed based on the adaptive thresholds determined by running root-mean-square (RMS) value of the signal. Yet conventional detection methods are susceptible to threshold fluctuations caused by neuronal spike intensity. In the present study we propose a novel adaptive threshold based on the max-min spread sorting method. On the basis of microelectrode recording signals and simulated signals with Gaussian noises and colored noises, the novel method had the smallest threshold variations, and similar or better spike detection performance than either the RMS-based method or other improved methods. Moreover, the detection method described in this paper uses the reduced features of raw signal to determine the threshold, thereby giving a simple data manipulation that is beneficial for reducing the computational load when dealing with very large amounts of data (as multi-electrode recordings).