Detection and analysis of gastrointestinal sounds in normal and small bowel obstructed rats

This study is aimed at detecting gastrointestinal sounds (GIS) and correlating their characteristics with gastrointestinal (GI) conditions. The central hypotheses are that GIS generation depends on the motility patterns and the mechanical properties of the gut, and that changes in those result in measurable differences in GIS. An animal model which included both healthy rats and those with small bowel obstruction (SBO) was developed. The acoustic bursts, of GIS were detected by amplitude thresholding the signal envelope. Three methods of envelope estimation were proposed and evaluated. Envelope estimation using a Hilbert transform was found to produce the best results in the current application. The duration and dominant frequency of each detected GIS event was estimated and clear differences between healthy and diseased rats were discovered. In the control state, GIS events were found to consistently be of relatively short duration (3–65ms). Although the majority of events in the SBO state had similar short duration, infrequent longer events were also detected and appeared to be pathognomonic. Long duration events (>100 ms) occurred in each of seven obstructed, but in none of 14 non-obstructed, cases (p<0.001). It is concluded that GIS analysis may prove useful in the non-invasive, rapid, and accurate diagnosis of SBO.     

Development and preliminary clinical tests of an impedance sensing VDD recording pacemaker for diagnosis and research

Episodes of serious but infrequently occurring cardiac arrhythmias can be difficult to detect and analyse, even with modern Holter monitoring. A previous diagnostic pacemaker developed by this group provided VVI pacing therapy and recorded intracardiac ECG signals but had no atrial sensing or impedance measuring capability. A new external diagnostic pacemaker system is described that has been developed to assist in diagnosing intermittent arrhythmias by selectively recording intracardiac signals. Unlike other ambulatory monitors, in addition to recording ECG, the device combines VDD pacing therapy with the capability of monitoring and recording intracardiac impedance and pressure waveforms through a temporary intracardiac lead. A PCMCIA memory card allows storage of 48 arrhythmic events of 21 seconds each. Twelve seconds of waveform are retained before the event occurs and nine seconds after. Data retrieval and processing is performed with a PC which reconstructs each waveform for display. The ECG provides data on cardiac rhythm while cardiac function is inferred from the haemodynamic signals. During simulated trials, 14 event types were presented to the system. All events were successfully detected and recorded. During in vivo clinical tests 83 waveform recordings were made. Impedance fluctuations with typical peak-to-peak values of 64 ohms were successfully recorded.     

Development and preliminary clinical tests of an impedance sensing VDD recording pacemaker for diagnosis and research

Episodes of serious but infrequently occurring cardiac arrhythmias can be difficult to detect and analyse, even with modern Holter monitoring. A previous diagnostic pacemaker developed by this group provided VVI pacing therapy and recorded intracardiac ECG signals but had no atrial sensing or impedance measuring capability. A new external diagnostic pacemaker system is described that has been developed to assist in diagnosing intermittent arrhythmias by selectively recording intracardiac signals. Unlike other ambulatory monitors, in addition to recording ECG, the device combines VDD pacing therapy with the capability of monitoring and recording intracardiac impedance and pressure waveforms through a temporary intracardiac lead. A PCMCIA memory card allows storage of 48 arrhythmic events of 21 seconds each. Twelve seconds of waveform are retained before the event occurs and nine seconds after. Data retrieval and processing is performed with a PC which reconstructs each waveform for display. The ECG provides data on cardiac rhythm while cardiac function is inferred from the haemodynamic signals. During simulated trials, 14 event types were presented to the system. All events were successfully detected and recorded. During in vivo clinical tests 83 waveform recordings were made. Impedance fluctuations with typical peak-to-peak values of 64 ohms were successfully recorded.     

基于希尔伯特-黄变换的白细胞信号分

白细胞信号(WBS)具有脉冲形状多样和时频特性各异的特点,目前临床上用细胞信号脉冲计数的方法来分析WBS通常难以反映其所携带的丰富的生理和病理信息,并直接影响到细胞分类问题。针对这一问题,探索能自适应地分解非线性非平稳信号的希尔伯特 黄变换算法在WBC时频分析和分类中的应用效果。通过对血细胞中的WBC进行HHT变换,获取WBC的本征模态函数（IMF）分量、分量的Hilbert边际谱以及信号Hilbert谱;利用瞬时频率、瞬时幅值等进行计算提取健康人与患者的WBS平均强度、谱质心以及能量贡献率等特征作对比分析,根据其时频特征分布规律构建用于分类实验的特征向量;采用支持向量机（SVM）分类器,对58名健康人和60名患者的白细胞实验样本进行分类实验。结果表明,该方法提取的健康人和患者的WBS分量谱质心分布、平均强度值以及能量贡献率具有较好的区分度,分类正确率到达了94.83%。HHT方法能有效提取WBS特征,可辅助临床WBS的处理和分析。     

Automatic on-line analyser of microbial growth using simultaneous measurements of impedance and turbidity

An apparatus for the measurement of bacterial growth is described. The instrument applies alternate adequate sequential currents of two different frequencies through a pair of electrodes immersed in a cultured medium. It monitors, detects and quantifies the growth of micro-organisms based on the measurement of the impedance across the two electrodes and, simultaneously, it measures the variation in the medium turbidity. The medium conductivity and the interface electrode impedance changes can be extracted from the measured impedance. The variations in turbidity can be calibrated in absorbance or optical density units. Moreover, all these parameters are also proportional to bacterial proliferation. The computer-controlled apparatus processes and displays the parameters on a monitor showing bulk resistance, electrode impedance and turbidity changes as time course events. The equipment can detect aerobic or anaerobic micro-organisms and permits the operator simultaneously to assess impedance and turbidity, or it can produce each parameter as a separate event. Time growth curves of different micro-organisms are presented in the results.     

Automatic on-line analyser of microbial growth using simultaneous measurements of impedance and turbidity

An apparatus for the measurement of bacterial growth is described. The instrument applies alternate adequate sequential currents of two different frequencies through a pair of electrodes immersed in a cultured medium. It monitors, detects and quantifies the growth of micro-organisms based on the measurement of the impedance across the two electrodes and, simultaneously, it measures the variation in the medium turbidity. The medium conductivity and the interface electrode impedance changes can be extracted from the measured impedance. The variations in turbidity can be calibrated in absorbance or optical density units. Moreover, all these parameters are also proportional to bacterial proliferation. The computer-controlled apparatus processes and displays the parameters on a monitor showing bulk resistance, electrode impedance and turbidity changes as time course events. The equipment can detect aerobic or anaerobic micro-organisms and permits the operator simultaneously to assess impedance and turbidity, or it can produce each parameter as a separate event. Time growth curves of different micro-organisms are presented in the results.     

Estimation of Delay Times in Biological Systems

The problem of delay time estimation in biological systems is addressed with the focus on practical applicability of methods. Four delay time estimators are described: a cross correlation method and three increasingly sophisticated interpretations of the phase spectrum, ranging from a pointwise interpretation of the phase spectrum in terms of a delay to a Hilbert transform method. The four methods are compared through simulation studies showing that, in general, the Hilbert transform method performs best. The methods are then used to estimate delay times in three physiological systems: vestibular stimulation, cerebral autoregulation, and human orthostatic tremor. In all three cases, the Hilbert transform method yields the best results, leading in some cases to physiologically more sensible interpretations of experiments than the other methods. © 2003 Biomedical Engineering Society. PAC2003: 8710+e, 8780Tq     

Effects of window types on classification of carotid artery Doppler signals in the early phase of atherosclerosis using complex-valued artificial neural network

In this study, carotid artery Doppler ultrasound signals were acquired from left carotid arteries of 38 patients and 40 healthy volunteers. The patient group had an established diagnosis of the early phase of atherosclerosis through coronary or aortofemoropopliteal angiographies. Doppler signals were processed using fast Fourier transform (FFT) with different window types, Hilbert transform and Welch methods. After these processes, Doppler signals were classified using complex-valued artificial neural network (CVANN). Effects of window types in classification were interpreted. Results for three methods and five window types (Bartlett, Blackman, Boxcar, Hamming, Hanning) were presented as comparatively. CVANN is a new technique for solving classification problems in Doppler signals. Furthermore, examining the effects of window types in addition to CVANN in this classification problem is also the first study in literature related with this subject. Results showed that CVANN, whose input data were processed by Welch method for each window types stated above, had classified all training and test patterns, which consist of 36 healthy, 34 unhealthy and four healthy, four unhealthy subjects, respectively, with 100% classification accuracy for both training and test phases.     

A two-step Hilbert transform method for 2D image reconstruction

The paper describes a new accurate two-dimensional (2D) image reconstruction method consisting of two steps. In the first step, the backprojected image is formed after taking the derivative of the parallel projection data. In the second step, a Hilbert filtering is applied along certain lines in the differentiated backprojection (DBP) image. Formulae for performing the DBP step in fanbeam geometry are also presented. The advantage of this two-step Hilbert transform approach is that in certain situations, regions of interest (ROIs) can be reconstructed from truncated projection data. Simulation results are presented that illustrate very similar reconstructed image quality using the new method compared to standard filtered backprojection, and that show the capability to correctly handle truncated projections. In particular, a simulation is presented of a wide patient whose projections are truncated laterally yet for which highly accurate ROI reconstruction is obtained.     

基于自适应局部余弦变换的正交多普勒超声信号降噪方法的研究

多普勒超声信号的谱图已经被广泛用于医疗诊断。来自系统内部的噪声及外部的干扰会产生附加的频谱成分，从而影响谱图的主观分析及进一步的定量分析。为抑制噪声的影响，本文提出利用一种新的基于自适应局部余弦变换和非负Garrote取阈值的方法对正交多普勒超声信号进行降噪。首先，由正交信号提取正向和逆向血流信息；然后对其分别进行降噪；最后利用Hilbert变换进行重构得到真实信号的估计。在仿真研究中，采用平均频率波形和谱宽波形的估计精度作为性能改善的指标。结果表明这种方法优于基于小波变换的降噪方法，特别是在低信噪比情况下。     

Study on gastric interdigestive pressure activity based on phase space reconstruction and FastICA algorithm

To investigate the features of the gastric interdigestive pressure activity under normal physiological conditions, we have developed the wireless radiotelemetry capsule based on a telemetry technique. Twelve healthy volunteers participated in this study. Pressure activity data which are an important index of gastric motility can be obtained from the wireless radiotelemetry capsule. But the capsule only records single-dimensional pressure time series which may contain a few interdependent components simultaneously. Automated embedding phase space reconstruction algorithm is employed to reconstruct multi-dimensional phase space. Then the dominant and separated component of the gastric contractions is identified using FastICA algorithm. Finally the use of Hilbert Huang transform method for analyzing the characters of gastric motility is investigated. The results show that the proposed method is an effective approach for the analysis of the gastric pressure series.     

Methods for evaluating adverse drug event preventability in emergency department patients

Background

There is a high degree of variability in assessing the preventability of adverse drug events, limiting the ability to compare rates of preventable adverse drug events across different studies. We compared three methods for determining preventability of adverse drug events in emergency department patients and explored their strengths and weaknesses.

Methods

This mixed-methods study enrolled emergency department patients diagnosed with at least one adverse drug event from three prior prospective studies. A clinical pharmacist and physician reviewed the medical and research records of all patients, and independently rated each event’s preventability using a “best practice-based” approach, an “error-based” approach, and an “algorithm-based” approach. Raters discussed discordant ratings until reaching consensus. We assessed the inter-rater agreement between clinicians using the same assessment method, and between different assessment methods using Cohen’s kappa with 95% confidence intervals (95% CI). Qualitative researchers observed discussions, took field notes, and reviewed free text comments made by clinicians in a “comment” box in the data collection form. We developed a coding structure and iteratively analyzed qualitative data for emerging themes regarding the application of each preventability assessment method using NVivo.

Results

Among 1356 adverse drug events, a best practice-based approach rated 64.1% (95% CI: 61.5–66.6%) of events as preventable, an error-based approach rated 64.3% (95% CI: 61.8–66.9%) of events as preventable, and an algorithm-based approach rated 68.8% (95% CI: 66.1–71.1%) of events as preventable. When applying the same method, the inter-rater agreement between clinicians was 0.53 (95% CI: 0.48–0.59), 0.55 (95%CI: 0.50–0.60) and 0.55 (95% CI: 0.49–0.55) for the best practice-, error-, and algorithm-based approaches, respectively. The inter-rater agreement between different assessment methods using consensus ratings for each ranged between 0.88 (95% CI 0.85–0.91) and 0.99 (95% CI 0.98–1.00). Compared to a best practice-based assessment, clinicians believed the algorithm-based assessment was too rigid. It did not account for the complexities of and variations in clinical practice, and frequently was too definitive when assigning preventability ratings.

Conclusion

There was good agreement between all three methods of determining the preventability of adverse drug events. However, clinicians found the algorithmic approach constraining, and preferred a best practice-based assessment method.

     

基于HHT的生物电阻抗胃动力信号分析方法

目的 采用HHT时间序列分析方法处理从人体采集到的胃动力信号.方法 通过经验模态分解(EMD)技术将一非线性、非稳态过程的原始胃动力序列分解为一组内在模态函数(IMFs),对每一个IMF进行Hilbert 变换,得到信号的瞬时频率,然后选择与胃动力相关的频率成分,即0.03-0.06 Hz之间的IMF进行重构提取胃动力...     

Sympathetic overactivity and plasma leptin levels in Rett syndrome

The authors examined electroencephalographic (EEG) oscillatory responses to two violent events, the player character wounding and killing an opponent character with a gun, in the digital game James Bond 007: NightFire. EEG was recorded from 25 (16 male) right-handed healthy young adults. EEG data were segmented into one 1-s baseline epoch before each event and two 1-s epochs after event onset. Power estimates (microV(2)) were derived with the fast Fourier transform (FFT) for each artefact free event. Both of the studied events evoked increased occipital theta (4-6Hz) responses as compared to the pre-event baseline. The wounding event evoked also increased occipital high theta (6-8Hz) response and the killing event evoked low alpha (8-10Hz) asymmetry over the central electrodes, both relative to the pre-event baseline. The results are discussed in light of facial electromyographic and electrodermal activity responses evoked by these same events, and it is suggested that the reported EEG responses may be attributable to affective processes related to these violent game events.     

On the Thermodynamics of Cell Injury: Some Insights into the Molecular Mechanisms

A method is presented for determining the thermodynamic parameters of the rate-limiting chemical reaction in cell injury. From these parameters one can deduce certain molecular details of this reaction, such as the number of molecular events required for a specific observable injury, the approximate number of the chemical bonds broken and the degree of molecular configurational change involved. Inactivation of cell division in vitro by heat and by an alkylating agent have been studied by this method. In each case cell injury involved only one to three catastrophic molecular events, which were irreparable within a 3-day period. This suggests that in each case there had been an alteration of a genome essential for cell division. In the case of thermal injury this critical molecular event had the thermodynamic characteristics of a massive configurational change, compatible with the uncoiling of a DNA segment. In the case of alkylation injury the thermodynamic parameters were those of a small localized event with little configurational change and energetically compatible with an alkylation-depurination of DNA.     

Image reconstruction via the finite Hilbert transform of the derivative of the backprojection

An exact analytical image reconstruction method is presented for two-dimensional imaging. The method performs backprojection, the derivative and finite Hilbert transforms. This method can be applied to many imaging geometries. The backprojection procedure is imaging-geometry dependent, while the differentiation and the finite Hilbert transform procedures are identical for all imaging geometries. This algorithm is applicable to list-mode data in nuclear medicine, while other filtered backprojection algorithms cannot be applied directly to the list-mode data.     

Noninvasive Localization of Epileptic Sites from Stable Phase Synchronization Patterns on Different Days Derived from Short Duration Interictal Scalp dEEG

The stochastic behavior of the phase synchronization index (SI) on different days during a hospital stay of epileptic patients was studied for noninvasive localization of the epileptogenic areas from high density (256 channel) scalp EEG recordings. The study was performed on three subjects with interictal EEG data on different days. The seizure areas were localized with subdural recordings with an 8 × 8 grid electrode array. The study was performed in low gamma (30–50 Hz) band with short duration (0–180 s), seizure-free and spike-free scalp EEG data. A detrended fluctuation analysis was used to find the averaged stochastic fluctuations in the SI. The phase synchronization was computed after taking Hilbert transform of the EEG data. Contour plots were constructed with 20 s time–frames using a montage of the layout of 256 electrode positions. It was found that the stochastic behavior of the SI was higher in epileptogenic areas on different days for each subject. Also, a stable higher pattern of SI emerged after 60–100 s in the epileptogenic areas. These findings suggest that it is possible to localize the epileptogenic areas from the short duration (60–100 s), seizure-free and spike-free high density scalp EEG recordings.     

An improved algorithm for respiration signal extraction from electrocardiogram measured by conductive textile electrodes using instantaneous frequency estimation

In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problems of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we are proposing a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 male subjects, and we obtained satisfactory respiration signals that showed high correlation (r ² > 0.8) with the signal acquired from the chest-belt respiration sensor.