Vibration plethysmography: A method for studying the visco-elastic properties of finger arteries

Vibration plethysmography records changes in vascular volume produced by fast vibrations of cuff pressure. From these, waveforms of dynamic vascular compliance (DVC) are obtained. A total of 46 recordings of DVC, photo-electric plethysmogram (PG), cuff pressure (CP), and indirect blood pressure (BP) are performed on two adjacent fingers (third and fourth) in 23 healthy subjects. The shape and polarity of the DVC waveform markedly depends upon CP or transmural pressure (TP) (TP=BP-CP). The correlation coefficient between DVC and PG waveforms is nearly −1 at negative mean TP, near zero at zero TP, and approaches +1 at positive TP. For CP moving between systolic and diastolic BP, the DVC waveform shows a diastolic peak, with its maximum close to the zero value of instantaneous TP. xy-diagrams of PG against TP and of DVC against TP plotted for the diastolic phase of single pulses reveal a close coincidence of the DVC peak with the maximum slope of the PG/TP curve. A similar relationship appears when slow changes in PG and the amplitude of PG pulse waves are plotted against mean TP.     

An exploratory study to design a novel hand movement identification system

Electromyogram signal (EMG) is an electrical manifestation of contractions of muscles. Surface EMG (sEMG) signal collected from the surface of skin has been used in diverse applications. One of its usages is in pattern recognition of hand prosthesis movements. The ability of current prosthesis devices has been generally limited to simple opening and closing tasks, minimizing their efficacy compared to natural hand capabilities. In order to extend the abilities and accuracy of prosthesis arm movements and performance, a novel sEMG pattern recognizing system is proposed. To extract more pertinent information we extracted sEMGs for selected hand movements. These features constitute our main knowledge of the signal for different hand movements. In this study, we investigated time domain, time-frequency domain and combination of these as a compound representation of sEMG signal's features to access required signal information. In order to implement pattern recognition of sEMG signals for various hand movements, two intelligent classifiers, namely artificial neural network (ANN) and fuzzy inference system (FIS), were utilized. The results indicate that our approach of using compound features with principle component analysis (PCA) as dimensionality reduction technique, and FIS as the classifier, provides the best performance for sEMG pattern recognition system.     

Pre-operative ordering of minimally invasive surgical tools: a fuzzy inference system approach

OBJECTIVE: With a limited number of access ports, minimally invasive surgery (MIS) often requires the complete removal of one tool and reinsertion of another in order to provide surgeons with the full functionality necessary to complete a procedure. MATERIALS AND METHODS: Endoscope video from 14 MIS procedures performed at the University of Nebraska Medical Center was used to collect usage statistics for various surgical instruments. This usage data was normalized and input to a fuzzy inference system (FIS) with four membership functions (MFs) to provide a crisp rating value for each instrument. Input membership functions included: number of uses ("Use"), total time used ("Time"), number of changes ("Change") and time per use ("Ave-Time"). Tools were arranged in a simulated cartridge system based on a "Usefulness" output membership function in such a way as to allow easy selection of the next instrument necessary to complete the procedure. Performance was measured by comparing the amount of cartridge indexing needed to complete a procedure using the FIS-generated arrangement against a set of random tool arrangements. RESULTS: The 14 FIS-generated tool arrangements considered in this investigation performed better than 64.11% of randomly generated tool arrangements and as well or better than 80.48% of tool arrangements. Using the FIS in conjunction with a multifunction laparoscopic tool, it is projected that an average cycle savings of 17.75% and 17.39% can be achieved over the mean and median of the random tool arrangements, respectively. CONCLUSIONS: For a given set of tools, the FIS used in this investigation provides an efficient method of arranging tools for MIS that performs at least as well or better than simply placing the tool tips into the chambers in a random configuration. This leads to a decrease in operating room time and corresponding decreases in both patient trauma from insertion and removal of tools and monetary cost, which is directly related to the amount of time spent changing instruments.     

Rational approaches to the design of NMR selective pulses

The need for NMR selective pulses in magnetic resonance imaging and spectroscopy is reviewed. The shortcomings of the current generation of pulses are discussed and the need for new categories of pulse identified. Strategies for selective pulse design are outlined and two numerical optimization methods, simulated annealing and SPINCALC (a method recently introduced by us: J. T. Ngo and P. G. Morris, Magn. Reson. Med. 5, 217 (1987], are discussed in detail. Their use is illustrated and compared for the design of pi/2 phase-compensated pulses. Both methods require substantial amounts of CPU time, with simulated annealing the more demanding. Unconstrained, simulated annealing also tends to produce pulses with discontinuous waveforms. A crude two-dimensional pulse derived from a low flip angle approximation is illustrated.     

深部脑刺激中单相脉冲与双相脉冲的作用比较

深部脑刺激在帕金森和癫痫等脑部疾病治疗中的应用不断发展,它使用的电刺激波形通常为窄脉冲。但是,对于单相脉冲与双相脉冲的刺激作用之间的差别还缺乏全面的认识。为了研究不同波形脉冲对于深部脑组织的刺激作用,在麻醉大鼠海马CA1区的输入和输出轴突纤维上,分别施加不同极性的或者不同方式的（单个或连续）单相和双相脉冲,考察CA1区神经元单细胞和神经元群体在刺激作用下的响应,以定量分析不同刺激波形的作用效果。共计18次动物实验结果如下：1）CA1区输入通道的小强度单个刺激顺向诱发单元锋电位时,以兴奋性相位为前相的双相脉冲和兴奋性单相脉冲的诱发率（分别为69.2%±10.4% 和650%±10%）显著高于以非兴奋性相位为前相的双相脉冲和非兴奋性单相脉冲的诱发率（分别为28.8%±9.5%和34.2%±12.5%）（n=6）;而且,双相脉冲的作用效果取决于前相,与无后相的单相脉冲的作用效果没有显著差别。2）CA1区输出通道的大强度单个刺激逆向诱发群峰电位时,双相脉冲的作用仍然与单相脉冲接近（n=6）,由其前相主导,后相的作用较小。3）在CA1区输出通道逆向的100 Hz持续高频串刺激期间,起始0.5 s时间内单相脉冲引起群峰电位的幅值下降（54.2%±21.3%）显著高于前相与其一致的双相脉冲所引起的幅值下降（39.0%±10.2%）（n=6）,说明高频串刺激时单相脉冲的作用比双相脉冲要强,但是单相脉冲可能造成神经组织的损伤。因此,长时间的高频刺激治疗应采用双相脉冲。这些研究结果对于深入了解深部脑刺激的作用机制以及安全有效地推广其临床应用都具有重要意义。     

Unconstrained detection of respiration rhythm and pulse rate with one under-pillow sensor during sleep

A completely non-invasive and unconstrained method is proposed to detect respiration rhythm and pulse rate during sleep. By employing wavelet transformation (WT), waveforms corresponding to the respiration rhythm and pulse rate can be extracted from a pulsatile pressure signal acquired by a pressure sensor under a pillow. The respiration rhythm was obtained by an upward zero-crossing point detection algorithm from the respiration-related waveform reconstructed from the WT 2⁶ scale approximation, and the pulse rate was estimated by a peak point detection algorithm from the pulse-related waveform reconstructed from the WT 2⁴ and 2⁵ scale details. The finger photo-electric plethysmogram (FPP) and nasal thermistor signals were recorded simultaneously as reference signals. The reference pulse rate and respiration rhythm were detected with the peak and upward zero-crossing point detection algorithm. This method was verified using about 24 h of data collected from 13 healthy subjects. The results showed that, compared with the reference data, the average error rates were 3.03% false negative and 1.47% false positive for pulse rate detection in the extracted pulse waveform. Similarly, 4.58% false negative and 3.07% false positive were obtained for respiration rhythm detection in the extracted respiration waveform. This study suggests that the proposed method is suitable, in sleep monitoring, for the diagnosis of sleep apnoea or sudden death syndrome.     

Bayesian tracking of intracranial pressure signal morphology

Background

The waveform morphology of intracranial pressure (ICP) pulses holds essential informations about intracranial and cerebrovascular pathophysiological variations. Most of current ICP pulse analysis frameworks process each pulse independently and therefore do not exploit the temporal dependency existing between successive pulses. We propose a probabilistic framework that exploits this temporal dependency to track ICP waveform morphology in terms of its three peaks.

Material

ICP and electrocardiogram (ECG) signals were recorded from a total of 128 patients treated for various intracranial pressure related conditions.

Methods

The tracking is posed as inference in a graphical model that associates a random variable to the position of each peak. A key contribution is to exploit a nonparametric Bayesian inference algorithm that offers robustness and real time performance. A simple, yet effective learning procedure estimates the statistical, nonlinear, dependencies between the peaks in a nonparametric way using evidence collected from manually annotated pulses.

Results

Experiments demonstrate the effectiveness of the tracking framework on real ICP pulses and its robustness to occlusion and missing peaks. On artificialy distorted ICP sequences, the average error in latency in comparision with MOCAIP detector was reduced as follows: 11.88-8.09 ms, 11.80-6.90 ms, and 11.76-7.46 ms for the first, second, and third peak, respectively.

Conclusion

The proposed tracking algorithm sucessfuly increases the temporal resolution of detecting ICP pulse morphological changes from the minute-level to the beat-level.     

Classification of acute myocardial ischemia by artificial neural network using echocardiographic strain waveforms

Echocardiographic strain waveforms are highly variable, so their interpretation is experience-dependent and subjective. We tested whether an artificial neural network (ANN) can distinguish between strain waveforms obtained at baseline and during experimentally induced acute ischemia. An open-chest model of coronary occlusion and acute ischemia was used in 14 adult pigs. Strain waveforms were obtained using a GE Vivid 7 ultrasound system. An ANN design was implemented in MATLAB, and backpropagation and "leave-one-out" processes were used to train and test it. Specificity of 86% and sensitivity of 87% suggest that ANNs could aid in diagnostic prescreening of echocardiographic strain waveforms.     

Two-point vibrotactile discrimination related to parameters of pulse burst stimulus

Tactile spatial resolution is an important factor in the design of vibrotactile arrays. The two-point discrimination distance is used as a measure of tactile spatial resolution. An experimental study is presented showing the effect of pulse burst stimulus parameters, pulse repetition period and duty cycle on two-point vibrotactile spatial discrimination. An array of piezoceramic vibrators is used to measure two-point spatial discrimination on the index finger. In a group of 14 subjects, the average two-point discrimination distance for a pulse repetition period of 1/25 s is 2.1 mm (SD=1.0), whereas for 1/500 s it is 5.1 mm (SD=0.9). Differences in discrimination distances are statistically significant according to the ANOVA analysis (p<0.001). Results show that the two-point discrimination distance is better for longer pulse repetition periods. Therefore the pulse repetition period in an excitatory waveform composed of bursts of pulses is important for tactile resolution. No statistically significant differences in discrimination distances are found between bursts of pulses of 50% duty cycle and those of lower duty cycle. The latter result indicates that, by choosing low-duty cycle waveforms for vibrotactile stimulation, the power can be reduced with no loss in two-point discrimination capacity.     

Power requirements for vibrotactile piezo-electric and electromechanical transducers

Human-machine information transfer through tactile excitation has addressed new applications in virtual reality, robotics, telesurgery, sensory substitution and rehabilitation for the handicapped in the past few years. Power consumption is an important factor in the design of vibrotactile displays, because it affects energy needs and the size, weight, heat dissipation and cost of the associated electronics. An experimental study is presented on the power required to reach tactile thresholds in electromechanical and piezo-electric transducers. Three different waveforms are considered, with an excitatory period formed by a burst of rectangular 50% duty cycle pulses (R50), rectangular low duty cycle pulses (RLO) and sinusoidal pulses (SIN). Ten different pulse repetition periods (RPs) were considered in the range 1/550-1/25s. The voltage and current waveforms applied to the transducers at sensation thresholds in a group of 12 healthy subjects were sampled and stored in a digital oscilloscope. The average power was determined for each subject, and differences of two orders of magnitude were measured between the electromechanical and the piezo-electric transducer power consumption. Results show that, for the electromechanical transducer, a smaller power consumption of 25μW was determined for RP=1/25s and the RLO waveform. In the case of the piezo-electric transducer, power of 0.21 μW was determined for SIN excitation and RP=1/250s. These results show the advantages of reducing power requirements for vibrotactile displays, which can be optimised by the choice of appropriate types of transducer, excitatory waveforms and pulse repetition periods.     

Fuzzy detection of EEG alpha without amplitude thresholding

Intelligent automated systems are needed to assist the tedious visual analysis of polygraphic recordings. Most systems need detection of different electroencephalogram (EEG) waveforms. The problem in automated detection of alpha activity is the large inter-individual variability of its amplitude and duration. In this work, a fuzzy reasoning based method for the detection of alpha activity was designed and tested using a total of 32 recordings from seven different subjects. Intelligence of the method was distributed to features extracted and the way they were combined. The ranges of the fuzzy rules were determined based on feature statistics. The advantage of the detector is that no alpha amplitude threshold needs to be selected. The performance of the alpha detector was assessed with receiver operating characteristic (ROC) curves. When the true positive rate was 94.2%, the false positive rate was 9.2%, which indicates good performance in sleep EEG analysis.     

VERSE‐guided parallel RF excitations using dynamic field correction

In parallel RF pulse design, peak RF magnitudes and specific absorption rate levels are critical concerns in the hardware and safety limits. The variable rate selective excitation (VERSE) method is an efficient technique to limit the peak RF power by applying a local‐only RF and gradient waveform reshaping while retaining the on‐resonance profile. The accuracy of the excitation performed by the VERSEd RF and gradient waveforms strictly depends on the performance of the employed hardware. Any deviation from the nominal gradient fields as a result of frequency dependent system imperfections violates the VERSE condition similarly to off‐resonance effects, leading to significant excitation errors and the RF pulse not converging to the targeted peak RF power. Moreover, for iterative VERSE‐guided RF pulse design (i.e. reVERSE), the k‐space trajectory actually changes at every iteration, which is assumed to be constant. In this work, we show both theoretically and experimentally the effect of gradient system imperfections on iteratively VERSEd parallel RF excitations. In order to improve the excitation accuracy besides limiting the RF power below certain thresholds, we propose to integrate gradient field monitoring or gradient impulse response function (GIRF) estimations of the actual gradient fields into the RF pulse design problem. A third‐order dynamic field camera comprising a set of NMR field sensors and GIRFs was used to measure or estimate the actual gradient waveforms that are involved in the VERSE algorithm respectively. The deviating and variable k‐space is counteracted at each iteration of the VERSE‐guided iterative RF pulse design. The proposed approaches are demonstrated for accelerated multiple‐channel spatially selective RF pulses, and highly improved experimental performance was achieved at both 3 T and 7 T.     

Integrated monitoring can detect critical events and improve alarm accuracy

A computer-based, integrated monitor system was designed and utilized to collect and interactively manage physiologic data (13 variables and 3 waveforms) from six routinely used operating room monitors. Various approaches were developed to reduce false alarms, classify waveforms, and recognize events. False alarms: false alarms in ECG heart rate detection were reduced from 37.3% to 2.6% (p=0.005) of total alarms using multi-variable analysis and rate-of-change limits. Waveform classification: using artificial neural networks (AN), CO2 waveforms were classified into (a) spontaneous, (b) mechanical, and (c) mechanical/with spontaneous breathing attempts. The system properly classified 47 of 71 spontaneous, 65 of 67 mechanical, and 37 of 44 mechanical breaths/with spontaneous breathing attempts. Another ANN was used for detection of elevated and depressed ST segments in the ECG signal. All ST segment elevations and depressions of 0.1 mV were correctly identified. Event recognition: an algorithm developed to identify endotracheal intubation correctly recognized 13 of 17 intubations. This resulted in a 42% reduction in low end-tidal-CO2 false alarms.     

A low-pass differentiation filter based on the 2nd-order B-spline wavelet for calculating augmentation index

The key point to calculate augmentation index (AIx) related to cardiovascular diseases is the precise identification of the shoulder point. The commonly used method for extracting the shoulder point is to calculate the fourth derivative of the pulse waveform by numerical differentiation. However, this method has a poor anti-noise capability and is computationally intensive. The aims of this study were to develop a new method based on the 2nd-order B-spline wavelet for calculating AIx, and to compare it with numerical differentiation and Savitzky–Golay digital differentiator (SGDD). All the three methods were applied to pulse waveforms derived from 60 healthy subjects. There was a significantly high correlation between the proposed method and numerical differentiation (r = 0.998 for carotid pulses, and r = 0.997 for radial pulses), as well as between the proposed method and the SGDD (r = 0.995 for carotid pulses, and r = 0.993 for radial pulses). In addition, the anti-noise capability of the proposed method was evaluated by adding simulated noise (>10 Hz) on pulse waveforms. The results showed that the proposed method was advantageous in noise tolerance than the other two methods. These findings indicate that the proposed method can quickly and accurately calculate AIx with a good anti-noise capability.     

Some methodological questions concerning receiver operating characteristic (ROC) analysis as a method for assessing image quality in radiology

This paper raises five methodological questions concerning Receiver operating characteristic (ROC) analysis: (1) can the ROC “confidence criterion” be applied in a valid, reliable way?; (2) can ROC deal with ambiguous findings?; (3) can ROC deal effectively with false-negative findings?; (4) are ROC curves susceptible to valid statistical testing?; and (5) are ROC results useful in choosing among alternative imaging modalities? A review of the evidence leads to six conclusions. First, using ROC, all radiological findings must be unambiguously scored as true-positive, true-negative, false-positive, or false-negative, often forcing arbitrary, procrustean choices on readers and evaluators. Second, ROC requires radiologists to report findings by confidence level on a consistent, reliable basis throughout a ROC experiment; something that seems unrealistic, given what is known about human performance in almost all perceptual tasks of comparable complexity. Third, as gathered during the typical experiment, ROC data are probably nominal, but treated as if ordinal (or even interval) data, leading to distorted results. Fourth, ROC does not deal effectively with false-negatives, despite their importance. Fifth, there is no satisfactory method for statistically testing the significance of observed differences between two ROC curves if they are based on nominal data. Finally, the artificial tasks required of radiologists in a ROC evaluation limit the usefulness of ROC results in choosing among the imaging modalities.     

A new method based on fuzzy logic to evaluate the contract service provider performance

This paper puts forward a fuzzy inference system for evaluating the service quality performance of service contract providers. An application service provider (ASP) model for computerized maintenance management was used in establishing common performance indicators of the quality of service. This model was implemented in 10 separate hospitals. As a result, inference produced a service cost/acquisition cost (SC/AC) ratio reduction from 16.14% to 6.09%, an increase of 20.9% in availability, with a maintained repair quality (NRR) in the period of December 2001 to January 2003.     

Effect of pulse duration on two-photon excited fluorescence and second harmonic generation in nonlinear optical microscopy

We have developed a multiphoton microscopy (MPM) system using a 12-fs Ti:sapphire laser with adjustable dispersion precompensation in order to examine the impact of pulse duration on nonlinear optical signals. The efficiencies of two-photon-excited fluorescence (TPEF) and second harmonic generation (SHG) were studied for various pulse durations, measured at the sample, ranging from approximately 400 fs to sub-20 fs. Both TPEF and SHG increased proportionally to the inverse of the pulse duration for the entire tested range. Because of improved signal-to-noise ratio, sub-20-fs pulses were used to enhance MPM imaging depth by approximately 160%, compared to 120-fs pulses, in human skin.     

Electrogastrography in the dog: waveform analysis by a coherent averaging technique

Electrogastrograms (e.g.g.s) recorded cutaneously in the dog were subjected to waveform analysis by coherent (or ‘triggered’) averaging techniques, to study the relation between e.g.g. waveforms and gastric contractile activity on the one hand, and the position of the cutaneous electrodes used to pick up the e.g.g. on the other. The trigger pulses used were picked up by electrodes applied to the serosal surface of the stomach. To make allowance for the influence of gastric contractions and the related electrical signals on the e.g.g. waveforms a computer program was developed to create a multicategory averager. Instead of adding all signal segments together, each segment was assigned to one of four categories, depending on the magnitude of the corresponding gastric contraction (as recorded by a force transducer applied to the stomach wall). The signal segments in each category were then averaged. The results of the analysis showed that both abdominal electrode position and magnitude of gastric contraction had a clear influence on e.g.g. waveforms. It was also concluded that, depending on the position of the abdominal electrodes, e.g.g. waveforms are related to either corporal or antral regions, or to both regions simultaneously.     

多参数中央监护系统的研制

本文介绍了一个多参数中央监护系统，可同时监护１－８个床位。系统可显示病人的心电、呼吸、脉搏波形，及心率、呼吸率、血氧饱和度、无创血压、体温等多项生理参数。