雷达式生命探测仪中人体与动物识别技术的研究

雷达式生命探测仪通过检测生命体的呼吸信号来确定废墟、建筑物内等一些用肉眼无法观测到的生命体时,不仅关心生命体是否存在,而且需要知道生命体为人体还是动物。本文利用短时傅利叶变换对生命体的呼吸信号进行变换,并通过奇异值分解有效地提取特征矢量进行模式识别,能够成功地识别人体和动物。实验结果表明,基于短时傅利叶变换的奇异值分解法能够稳定、有效地提取特征矢量,从而便雷达式生命探测仪对生命体进行较准确地识别。     

Discrimination between artefacts and contractions in pressure signals from the gastrointestinal tract by pattern recognition method

A pattern recognition algorithm has been developed to discriminate between artefacts and contractions in interdigestive motility recorded by a pressure catheter with four channels from the human duodenum. A learning and a test set, both containing natural and induced artefacts, such as respiration and body movement, are obtained from five volunteers. The event classes were phase I, II and III contractions of the interdigestive motility complex and artefacts from respiration, cough, calibration signals and movements. Length, area, amplitude, inter-event interval, up- and downstroke, and correlation to other pressure channels and to respiration, are applied to classify the events. The sensitivity of the computer scoring increases with the number of applied features. When all the features are applied, the sensitivity of the Bayes' classifier against the visually scored contractions and artefacts is 0·96 with a specificity of 0·69.     

Using a multi-agent system approach for microaneurysm detection in fundus images

ObjectiveMicroaneurysms represent the first sign of diabetic retinopathy, and their detection is fundamental for the prevention of vision impairment. Despite several research attempts to develop an automated system to detect microaneurysms in fundus images, none has shown the level of performance required for clinical practice. We propose a new approach, based on a multi-agent system model, for microaneurysm segmentation.Methods and materialsA multi-agent based approach, preceded by a preprocessing phase to allow construction of the environment in which agents are situated and interact, is presented. The proposed method is applied to two available online datasets and results are compared to other previously described approaches.ResultsMicroaneurysm segmentation emerges from agent interaction. The final score of the proposed approach was 0.240 in the Retinopathy Online Challenge.ConclusionsWe achieved competitive results, primarily in detecting microaneurysms close to vessels, compared to more conventional algorithms. Despite these results not being optimum, they are encouraging and reveal that some improvements may be made.     

Receiver operating characteristic and location analysis of simulated near-infrared tomography images

Receiver operating characteristic (ROC) analysis was performed on simulated near-infrared tomography images, using both human observer and contrast-to-noise ratio (CNR) computational assessment, for application in breast cancer imaging. In the analysis, a nonparametric approach was applied for estimating the ROC curves. Human observer detection of objects had superior capability to localize the presence of heterogeneities when the objects were small with high contrast, with a minimum detectable threshold of CNR near 3.0 to 3.3 in the images. Human observers were able to detect heterogeneities in the images below a size limit of 4 mm, yet could not accurately find the location of these objects when they were below 10 mm diameter. For large objects, the lower limit of a detectable contrast limit was near 10% increase relative to the background. The results also indicate that iterations of the nonlinear reconstruction algorithm beyond 4 did not significantly improve the human detection ability, and degraded the overall localization ability for the objects in the image, predominantly by increasing the noise in the background. Interobserver variance performance in detecting objects in these images was low, suggesting that because of the low spatial resolution, detection tasks with NIR tomography is likely consistent between human observers.     

Detection of alpha electro-encephalogram onset following eye closure using four location-based techniques

Detection of alpha activity in the electro-encephalogram (EEG) has been used extensively in neurophysiological studies. Previously applied alpha parameterisation techniques, which utilise the amplitude information from a pair of differential electrodes, are often susceptible to interference from artifact signals. This is an issue if the purpose of detecting the change in alpha wave synchronisation is the basis of an environmental control system (ECS). An alternative approach to alpha activity detection is proposed that utilises the information from an array of electrodes on the scalp to estimate the apparent location of alpha activity in the brain. Four methods are described that successfully detect the onset of alpha EEG increase following eye closure by monitoring the apparent location of alpha activity in the head. The methods use Bartlett beamforming, a four-sphere anatomical head model, the MUSIC algorithm and a new ‘power vector’ technique. Of the methods described, the power vector technique is found to be the most successful. The power vector technique detects the alpha increase associated with eye closure in times that are, on average, 33% lower than previously applied alpha detection methods.     

Automated detection of perinatal hypoxia using time–frequency-based heart rate variability features

Perinatal hypoxia is a cause of cerebral injury in foetuses and neonates. Detection of foetal hypoxia during labour based on the pattern recognition of heart rate signals suffers from high observer variability and low specificity. We describe a new automated hypoxia detection method using time–frequency analysis of heart rate variability (HRV) signals. This approach uses features extracted from the instantaneous frequency and instantaneous amplitude of HRV signal components as well as features based on matrix decomposition of the signals’ time–frequency distributions using singular value decomposition and non-negative matrix factorization. The classification between hypoxia and non-hypoxia data is performed using a support vector machine classifier. The proposed method is tested on a dataset obtained from a newborn piglet model with a controlled hypoxic insult. The chosen HRV features show strong performance compared to conventional spectral features and other existing methods of hypoxia detection with a sensitivity 93.3 %, specificity 98.3 % and accuracy 95.8 %. The high predictive value of this approach to detecting hypoxia is a substantial step towards developing a more accurate and reliable hypoxia detection method for use in human foetal monitoring.     

Functional adaptation of reactive saccades in humans: a PET study

It is known that the saccadic system shows adaptive changes when the command sent to the extraocular muscles is inappropriate. Despite an abundance of supportive psychophysical investigations, the neurophysiological substrate of this process is still debated. The present study addresses this issue using H2(15)O positron emission tomography (PET). We contrasted three conditions in which healthy human subjects were required to perform saccadic eye movements toward peripheral visual targets. Two conditions involved a modification of the target location during the course of the initial saccade, when there is suppression of visual perception. In the RAND condition, intra-saccadic target displacement was random from trial-to-trial, precluding any systematic modification of the primary saccade amplitude. In the ADAPT condition, intra-saccadic target displacement was uniform, causing adaptive modification of the primary saccade amplitude. In the third condition (stationary, STAT), the target remained at the same location during the entire trial. Difference images reflecting regional cerebral-blood-flow changes attributable to the process of saccadic adaptation (ADAPT minus RAND; ADAPT minus STAT) showed a selective activation in the oculomotor cerebellar vermis (OCV; lobules VI and VII). This finding is consistent with neurophysiological studies in monkeys. Additional analyses indicated that the cerebellar activation was not related to kinematic factors, and that the absence of significant activation within the frontal eye fields (FEF) or the superior colliculus (SC) did not represent a false negative inference. Besides the contribution of the OCV to saccadic adaptation, we also observed, in the RAND condition, that the saccade amplitude was significantly larger when the previous trial involved a forward jump than when the previous trial involved a backward jump. This observation indicates that saccade accuracy is constantly monitored on a trial-to-trial basis. Behavioral measurements and PET observations (RAND minus STAT) suggest that this single-trial control of saccade amplitude may be functionally distinct from the process of saccadic adaptation.     

Enhancement of Non-Invasive Recording of Electroenterogram by Means of a Flexible Array of Concentric Ring Electrodes

Monitoring intestinal myoelectrical activity by electroenterogram (EEnG) would be of great clinical interest for diagnosing gastrointestinal pathologies and disorders. However, surface EEnG recordings are of very low amplitude and can be severely affected by baseline drifts and respiratory and electrocardiographic (ECG) interference. In this work, a flexible array of concentric ring electrodes was developed and tested to determine whether it can provide surface EEnG signals of better quality than bipolar recordings from conventional disc electrodes. With this aim, sixteen healthy subjects in a fasting state (>8 h) underwent recording. The capability of detecting intestinal pacemaker activity (slow wave) and the influence of physiological interferences were studied. The signals obtained from the concentric ring electrodes proved to be more robust to ECG and respiratory interference than those from conventional disc electrodes. The results also show that intestinal EEnG components such as the slow wave can be more easily identified by the proposed system based on a flexible array of concentric ring electrodes. The developed active electrode array could be a very valuable tool for non-invasive diagnosis of disease states such as ischemia and motility disorders of the small bowel which are known to alter the normal enteric slow wave activity.     

Impaired postural compensation for respiration in people with recurrent low back pain

This study evaluated the degree to which the disturbance to posture from respiration is compensated for in healthy normals and whether this is different in people with recurrent low back pain (LBP), and to compare the changes when respiratory demand is increased. Angular displacement of the lumbar spine and hips, and motion of the centre of pressure (COP), were recorded with high resolution and respiratory phase was recorded from ribcage motion. With subjects standing in a relaxed posture, recordings were made during quiet breathing, while breathing with increased dead-space to induce hypercapnoea, and while subjects voluntarily increased their respiration to match ribcage expansion that was induced in the hypercapnoea condition. The relationship between respiration and the movement parameters was measured from the coherence between breathing and COP and angular motion at the frequency of respiration, and from averages triggered from the respiratory data. Small angular changes in the lumbopelvic and hip angles were evident at the frequency of respiration in both groups. However, in quiet standing, the LBP subjects had a greater displacement of their COP that was associated with respiration than the control subjects. The LBP group had a trend for less hip motion. There were no changes in the movement parameters when respiratory demand increased involuntarily via hypercapnoea, but when respiration increased voluntarily, the amplitude of motion and the displacement of the COP increased in both groups. The present data suggest that the postural compensation to respiration counteracts at least part of the disturbance to posture caused by respiration and that this compensation may be less effective in people with LBP.     

一种生物雷达呼吸和心跳信号实时分离技术

目的 本研究旨在从雷达式生命参数检测平台的回波信号中分离出呼吸和心跳信号,提取呼吸、心跳特征参数.方法 分析回波信号的特征,改进算法,将呼吸信号的谐波组合作为自适应滤波器的参考输入信号进行回波信号滤波处理实验.结果 提出了一种基于自适应谐波抵消的呼吸和心跳信号分离算法.结论 该算法在生物雷达模拟人体平躺实验中能够有效地分离出呼吸和心跳信号.     

Three-dimensional sonoelastography: principles and practices

Sonoelastography is an ultrasound imaging technique where low amplitude, low-frequency shear waves (less than 0.1 mm displacement and less than 1 kHz frequency) are propagated through internal organs, while real-time Doppler techniques are used to image the resulting vibration pattern. When a discrete hard inhomogeneity, such as a tumour, is present within a region of soft tissue, a decrease in the vibration amplitude will occur at its location. This forms the basis for tumour detection using sonoelastography. For three-dimensional (3D) imaging the acquisition of sequential tomographic slices using this technique, combined with image segmentation, enables the reconstruction, quantification and visualization of tumour volumes. Sonoelastography and magnetic resonance images (MRI) of a tissue phantom containing a hard isoechoic inclusion are compared to evaluate the accuracy of this method. The tumour delineation from sonoelastography was found to have good agreement with the tumour from MRI except for a bleeding at one of its ends. Although sonoelastography is still in an experimental phase, the principles behind this imaging modality are explained and some practical aspects of acquiring sonoelastography images are described. Results from a 3D sonoelastography reconstruction of a tissue mimicking phantom and an ex vivo whole prostate specimen are presented.     

Detection of copy number variations in epilepsy using exome data

Epilepsies are common neurological disorders and genetic factors contribute to their pathogenesis. Copy number variations (CNVs) are increasingly recognized as an important etiology of many human diseases including epilepsy. Whole‐exome sequencing (WES) is becoming a standard tool for detecting pathogenic mutations and has recently been applied to detecting CNVs. Here, we analyzed 294 families with epilepsy using WES, and focused on 168 families with no causative single nucleotide variants in known epilepsy‐associated genes to further validate CNVs using 2 different CNV detection tools using WES data. We confirmed 18 pathogenic CNVs, and 2 deletions and 2 duplications at chr15q11.2 of clinically unknown significance. Of note, we were able to identify small CNVs less than 10 kb in size, which might be difficult to detect by conventional microarray. We revealed 2 cases with pathogenic CNVs that one of the 2 CNV detection tools failed to find, suggesting that using different CNV tools is recommended to increase diagnostic yield. Considering a relatively high discovery rate of CNVs (18 out of 168 families, 10.7%) and successful detection of CNV with <10 kb in size, CNV detection by WES may be able to surrogate, or at least complement, conventional microarray analysis.     

Computer-supported analysis of continuous ambulatory manometric recordings in the human small bowel

An algorithm has been developed for the offline analysis of prolonged manometric recordings in the upper small intestine of humans. Sample data are acquired in the human duodenum and jejunum using six solid-state strain-gauge transducers mounted on a silicon catheter that is connected to a portable digital recording device. The data are sampled at 4 Hz and filtered. For accurate calculations, the filtered signals are converted to cubic B-spline functions of order four. Based on an exponential weighted moving average, a base-line is calculated from the signal. Contractions are recognised on the basis of thresholds for minimum amplitude and duration. The developed algorithm calculates properties of these contractions, such as amplitude, duration, area and a motility index. In addition, the program automatically recognises normal motor patterns of the fasted human small intestine, such as the migrating motor complex, and aids in the identification of the postprandial motor pattern. Motor patterns are defined in terms of properties such as contraction frequency and propagation. In a validation procedure using conventional manual analysis, the program correctly identifies the number of individual contractions with a 98% confidence interval and also correctly recognises 96% of phase 3 motor activity.     

Recording and processing of fetal movements and sounds obtained with the Inpho inductive transducer

A recently developed transducer based on an inductive principle allows recording of fetal displacement signals on the maternal abdominal wall. The transducer is a relatively passive device, in contrast to commonly applied ultrasound transducers. This permits long-term observation of fetal movements and sounds. The bandwidth of the system is DC −200 Hz (±3dB), and signal-to-noise ratios of more than 96 dB have been measured in a laboratory setup, whereas in the practical situation a signal-to-noise ratio of 78 dB has been established. The transducer has been applied to study fetal respiratory sinus arrhythmia, which means that fetal breathing movements have to be extracted from the transducer's output. This proved possible by digital filtering of the displacement signal as detected by the transducer. The transducer has also been applied in a study where the signal-to-noise ratio of fetal heart sounds as a function of location of the fetus and position of the transducer on the maternal abdominal wall has been studied. It proved possible to adequately record fetal heart sounds for measurement of fetal heart rate. Also uterine activity could be recorded using the sensor's DC output.     

Epilepsy detection from EEG signals: a review

Abstract

Over many decades, research is being attempted for the detection of epileptic seizure to support for automatic diagnosis system to help clinicians from burdensome work. In this respect, an enormous number of research papers is published for identification of epileptic seizure. It is difficult to present a detailed review of all these literature. Therefore, in this paper, an attempt has been made to review the detection of an epileptic seizure. More than 100 research papers have been discussed to discern the techniques for detecting the epileptic seizure. Further, the literature survey shows that the pattern recognition required to detect epileptic seizure varies with different conditions of EEG datasets. This is mainly due to the fact that EEG detected under different conditions has different characteristics. This is, in turn, necessitates the identification of pattern recognition technique to effectively distinguish EEG epileptic data from a various condition of EEG data.     

Functional anatomy of saccadic adaptation in humans

Positron emission tomography (PET) was used to investigate the neurophysiological substrate of human saccadic adaptation. Subjects made saccadic eye movements toward a visual target that was displaced during the course of the initial saccade, a time when visual perception is suppressed. In one condition, displacement was random from trial to trial, precluding any systematic modification of the initial saccade amplitude. In the second condition, the direction and magnitude of displacement were consistent, causing adaptative modification of the initial saccade amplitude. PET difference images reflecting metabolic changes attributable to the process of saccadic adaptation showed selective activation of the medioposterior cerebellar cortex. This localization is consistent with neurophysiological findings in monkeys and brain-lesioned humans.     

Detection of artifacts from high energy bursts in neonatal EEG

Detection of non-cerebral activities or artifacts, intermixed within the background EEG, is essential to discard them from subsequent pattern analysis. The problem is much harder in neonatal EEG, where the background EEG contains spikes, waves, and rapid fluctuations in amplitude and frequency. Existing artifact detection methods are mostly limited to detect only a subset of artifacts such as ocular, muscle or power line artifacts. Few methods integrate different modules, each for detection of one specific category of artifact. Furthermore, most of the reference approaches are implemented and tested on adult EEG recordings. Direct application of those methods on neonatal EEG causes performance deterioration, due to greater pattern variation and inherent complexity. A method for detection of a wide range of artifact categories in neonatal EEG is thus required. At the same time, the method should be specific enough to preserve the background EEG information. The current study describes a feature based classification approach to detect both repetitive (generated from ECG, EMG, pulse, respiration, etc.) and transient (generated from eye blinking, eye movement, patient movement, etc.) artifacts. It focuses on artifact detection within high energy burst patterns, instead of detecting artifacts within the complete background EEG with wide pattern variation. The objective is to find true burst patterns, which can later be used to identify the Burst-Suppression (BS) pattern, which is commonly observed during newborn seizure. Such selective artifact detection is proven to be more sensitive to artifacts and specific to bursts, compared to the existing artifact detection approaches applied on the complete background EEG. Several time domain, frequency domain, statistical features, and features generated by wavelet decomposition are analyzed to model the proposed bi-classification between burst and artifact segments. A feature selection method is also applied to select the feature subset producing highest classification accuracy. The suggested feature based classification method is executed using our recorded neonatal EEG dataset, consisting of burst and artifact segments. We obtain 78% sensitivity and 72% specificity as the accuracy measures. The accuracy obtained using the proposed method is found to be about 20% higher than that of the reference approaches. Joint use of the proposed method with our previous work on burst detection outperforms reference methods on simultaneous burst and artifact detection. As the proposed method supports detection of a wide range of artifact patterns, it can be improved to incorporate the detection of artifacts within other seizure patterns and background EEG information as well.     

Design and research of an interface compatible non-contacting respiratory signal detection system

Respiration-induced displacements of organs greatly affect the safety and efficiency of high intensity focused ultrasound (HIFU) tumor therapy system. The key to solve this problem is accurate, real-time detection of respiratory signals. The present study gives a new design of an interface compatible non-contacting respiratory signal detection system using the method of irradiating the laser beam onto certain region of the surface of human body that is intensely influenced by the breathing movements (mostly the breast or the dorsum) at a certain angle, and meanwhile using a camera to acquire information from the location of the laser projection. Then we can draw a curve of the location of laser projection versus time base, that is the respiration curve. This respiratory signal detection method is non-contacting, interface compatible and easy to be integrated into the treatment system.     

Oscillations in stroke volume and cardiac output arising from oscillatory ventilation in humans

Oscillations in the cardiovascular system have been observed in patients with periodic breathing. It is not clear whether these are driven by primary oscillations in the respiratory system or whether an intrinsic cardiovascular instability is required, as previous studies with subjects performing voluntary periodic breathing have failed to produce the cardiovascular oscillations. We investigated whether cardiovascular oscillations occurred in healthy controls performing voluntary periodic breathing. Six healthy subjects performed voluntary periodic breathing with guidance from a real-time computer display. We measured ventilation, end-tidal partial pressures of O2 (PO2) and CO2 (PCO2), heart rate, blood pressure (BP), arterial oxygen saturation and stroke volume and cardiac output by transthoracic impedance cardiography. Fourier analysis was used to quantify the size and phase of the periodic breathing-induced oscillations in these parameters. Periodic breathing (amplitude 30% of mean ventilation) induced oscillations in end-tidal PO2 (amplitude 0.8 kPa), end-tidal PCO2 (amplitude 0.3 kPa), R-R interval (amplitude 32.6 ms), systolic BP (amplitude 3 mmHg), diastolic BP (amplitude 3 mmHg), stroke volume (amplitude 8.0 ml, mean 79.5 ml) and cardiac output (amplitude 0.6 1, mean 5.9 l x min(-1)). The oscillations in stroke volume and cardiac output were nearly in phase with ventilation, with their peaks occurring 5.6 and 6.1 s, respectively, after the peak in ventilation. An oscillatory ventilatory pattern entrains the cardiovascular system in healthy controls into fluctuations, not only in heart rate and BP, but also in stroke volume and cardiac output.     

基于ARM7的多功能离子导入治疗仪的设计

目的：设计一种频率可调的新型多功能离子导入治疗仪,使之能够克服目前国内大部分离子导入仪输出频率单一,或者仅仅局限于某一频段的缺点,可实现不同种类药物离子的导入,最大限度地发挥药物的疗效。方法：采用以ARM7为内核的LPC2138作为主控芯片,使用基于DDS技术的AD9834作为波形信号产生芯片,经过功率放大器LF347放大后,系统可实现独立调节的四通道输出。使用LCD TFT真彩屏作为显示器件,API8108A作为语音芯片,具有动态显示和语音同步告知等功能。结果：系统输出波形表明,该系统实现了多种频率和多种波形输出,且输出幅值和频率可调,并且通过选择治疗模式可以实现电离子导入疗法和干扰电疗法两种治疗功能。结论：整个系统具有电路结构简单、成本低、安全可靠、性能稳定和精度高等优点。且人机交互能力强,操作简单,并且特别设计了电极脱落检测电路,可在系统整个工作的过程中自动检测电极是否与人体可靠接触,如果检测到电极脱落则自动语音提示用户进行检查,能够及时有效的保护患者的安全。