Spectrum shaping with a hardware digital filter

Digital filters have certain characteristics which make possible some things that are either difficult or essentially impossible using analog equipment. Among the most useful characteristics are steep transition band slopes and the capability to shape the passband transfer function in great detail. Unlike most digital filters implemented in software, hardware digital filters can be used to filter signals in real-time. Also, they can be designed to provide a linear phase response. They have some disadvantages as well, however, including moderately high cost, the need for supporting equipment, and at the present time, the need for a moderate degree of computer programming and interfacing skill. We have used hardware digital filters in a number of applications. These applications and the relevant filter performance characteristics are described.     

Adaptive clutter filtering for ultrasound color flow imaging

In this article, we present an adaptive clutter rejection method for selecting different clutter filters in ultrasound color flow imaging. A single clutter filter is typically used to reject the clutter. Because the clutter characteristics vary in both space and time, the single clutter filter approach has difficulty in providing optimum clutter rejection in ultrasound images. To achieve more accurate velocity estimation, we have developed a method to select a clutter filter adaptively at each location in an image from a set of predefined filters. Selection criteria have been developed based on the underlying clutter characteristics and the properties of various filters (e.g., minimum-phase finite impulse response, projection-initialized infinite impulse response and polynomial regression). We have incorporated our adaptive clutter rejection method in an ultrasound system. We have found that our adaptive method can reduce the mean absolute error between the estimated and true flow velocities significantly compared with the conventional methods, in which a single clutter filter is used throughout the entire image. With in vivo abdominal data, we obtained an average gain of 5.0 dB in signal-to-clutter ratio (SCR), compared with the conventional method. These preliminary results indicate that the proposed adaptive method could improve the accuracy of flow velocity estimation in ultrasound color flow imaging through the improvement in SCR and the reduction in bias.     

Application of Beat-to-Beat Techniques

FLOWERS, N.C., ET AL.: Application of Beat-to-Beat Techniques. The focus of this report is to describe a system for recording surface His-Purkinje and ventricular late potentials on a beat-by-beat basis outside of a shielded environment. An AC magnetic field monitoring device was designed for improved site selection, orientation, and quality control of the acquisition. His-Purkinje signals are detected utilizing spatial averaging and specific channel selection algorithms applied to discriminate random noise from signal. Beat-by-beat vectormagnitude complexes were generated from pairs of X, Y, and Z leads. Both infinite impulse response (IIR) filters, modified for beat-by-beat approaches, and finite impulse response (FIR) filters were utilized. Using the IIR filter, beat-by-beat recordings from test subjects were compared to the signal averaged electrocardiogram (SAECG). Measurement parameters from normal test subjects fell within the previously specified normal range for the SAECG. The IIR filter applied to beat-by-beat recordings exhibited sharp frequency response and a precisely defined cutoff frequency allowing maximal attenuation of the low frequency components in the ST segment. While filter ringing was eliminated, discontinuity and distortion of the filtered waveform resulted. The FIR filter with linear phase response retained the integrity and morphology of the complex but because of its flat frequency response, the ST segment was not as well attenuated and it was more difficult to isolate late potentials. A high order FIR filter should be used if the desire is to match the frequency response of the four-pole IIR filter, since the frequency response of the FIR filter is primarily determined by the order of the filter. With the FIR filter the waveform will be widened on both sides in time and therefore a trade-off results between the order of the filter and the cutoff frequency. A low order and a high cutoff frequency were necessary to attenuate the low frequency components of the ST segment without significantly widening the QRS. To record high resolution ECGs without noticeable 60-Hz noise, the magnetic field of 60 Hz should be smaller than 6.6 × 10^-8 Tesla. This study indicates that real-time analysis of both His-Purkinje potentials and late potentials in an unshielded environment is possible. (PACE, Vol. 13, December, Part II 1990)     

Frequency filtering improves ultrasonic embolic signal detection.

Problems in detection of Doppler cerebral embolic signals primarily occur for embolic signals of low relative intensity. A characteristic feature of embolic signals is that the intensity increase is maximal over a narrow frequency band. Therefore, frequency filtering of the data might improve embolic signal relative intensity and detectability. We implemented an off-line finite impulse response filter in software running on a commercially available transcranial Doppler system, using the time-domain audio data as input. The range of the filter was chosen by placing a box around the embolic signal on the spectral display. One hundred consecutive embolic signals from patients with carotid stenosis were analyzed; all had been recorded by a bigate system and the signal was analyzed in both proximal and distal channels. There was a highly significant increase in embolic signal relative intensity following frequency filtering; mean (SD) proximal channel prefiltering 12.75 (4.83) dB, postfiltering 16.36 (4.93) dB; distal channel prefiltering 13.42 (4.98) dB, postfiltering 16.60 (5.11) dB, for both p < 0.001. Despite all embolic signals being audible and visible in at least one channel on the frequency spectral display, in 17 cases, the amplitude increase associated with the embolic signal could not be clearly seen in time-domain data of one or both channels prior to filtering. Following frequency filtering, this was reduced to 5. Incorporation of such a frequency-filtering approach to an online system is likely to improve the sensitivity of online detection for embolic signals of low relative intensity.     

Toward a practical mobile robotic aid system for people with severe physical disabilities.

A simple, relatively inexpensive robotic system that can aid severely disabled persons by providing pick-and-place manipulative abilities to augment the functions of human or trained animal assistants is under development at Rice University and the Baylor College of Medicine. A stand-alone software application program runs on a Macintosh personal computer and provides the user with a selection of interactive windows for commanding the mobile robot via cursor action. A HERO 2000 robot has been modified such that its workspace extends from the floor to tabletop heights, and the robot is interfaced to a Macintosh SE via a wireless communications link for untethered operation. Integrated into the system are hardware and software which allow the user to control household appliances in addition to the robot. A separate Machine Control Interface device converts breath action and head or other three-dimensional motion inputs into cursor signals. Preliminary in-home and laboratory testing has demonstrated the utility of the system to perform useful navigational and manipulative tasks.     

采集表面肌电信号应用于动作识别的可行性

背景：文献表明上肢前臂运动时所产生的表面肌电信号具有非线性特征,而肢体运动时肌电信号又呈现出非平稳特性。目的：设计一种简单的拾取电路采集表面肌电信号,拟应用于动作肌电信号的特征识别。方法：根据表面肌电信号的特点,设计高共模抑制比的前端放大电路,抑制共模干扰;采用低通滤波电路,有源双T带阻滤波器对信号进行去噪处理;对采集得到的信号进行小波包变换,得到信号的特征量。结果与结论：所设计的表面肌电信号检测电路具有较高共模抑制比,并能有效地滤除50Hz工频信号,可以满足肌电信号采集电路的基本要求。肌电信号的处理结果表明采用子频段能量值的方法可以区分手部4种不同动作。     

Blood flow estimation error with intravascular ultrasound due to in-plane component of flow

Previously, we presented a real-time method to measure blood flow perpendicular to the image plane of an intravascular ultrasound (IVUS) imaging system using a slow-time FIR (finite impulse response) filter bank. Any in-plane flow introduces error in the flow measurement using the filter bank algorithm. Simulations show that for a flow angle of +/- 10 degrees and velocities between 200 mm/s and 300 mm/s, the energy within the lowest frequency band filter is 6.92 to 7.80 times higher than for perpendicular flow in the worst case. We present a variation of the FIR filter bank algorithm, applying filter coefficients in a tilted fashion to slow-time signals (i.e., combining slow-time and fast-time). An appropriate tilt, which depends on the flow angle and velocity, corrects for the increased energy under the frequency bands. In this case, the energy under the lowest frequency band filter for an angle of +/- 10 degrees and velocities ranging from 200 mm/s to 300 mm/s is 2.09 to 2.94 times higher than for perpendicular flow, yielding greater than a factor of three improvement in the worst case over the original slow-time method. Moreover, the average energy over the vessel determined with the appropriate tilt is within 2-3% of the true value.     

The removal of EMG in EEG by neural networks

In this paper, it is presented that electromyography (EMG) is a shot noise based on the generation of EMG. A novel filter is proposed by applying a neural network (NN) ensemble where the noisy input signal and the desired one are the same in a learning process. Both incremental and batch mode are applied in the learning process of NNs that is better than generalized NN filters. This NN ensemble filter not only reduces additive and multiplicative white noise inside signals, but also preserves the signals' characteristics. In clinical EEG and EMG signals processing, the filter is capable of reducing EMG in the clinical EEG, and it is proved that there is randomness in EMG.     

Bias and variance in the estimate of the Doppler frequency induced by a wall motion filter

In pulsed Doppler flowmeters, processing of the Doppler signals is often done digitally. The first step in the analysis of the echoes is the filtering which is needed to remove stationary components and low frequency shifts induced by wall motion. This preliminary step is of utmost importance. The influence of uncorrelated noise on the measurement of Doppler signals at the input of this filter is analysed. The frequencies of the Doppler signals are extracted by an algorithm based on correlation techniques. We observed that the filter induces a correlated noise term, which results in an overestimation of the frequency. An effect similar to frequency aliasing may appear. The level of the bias is dependent on filter characteristics and noise level. Our study was carried out on simulated Doppler signals using first and second order filters. An especially desirable solution in flow mapping is proposed in order to decrease this error.     

Design, development, and implementation of a data processing system for multiple controlled trials and epidemiologic studies

We were given the opportunity to design and implement a general data processing system to accommodate several different epidemiologic studies to be conducted by a new research group. A survey of 15 operating data centers was conducted in preparation for undertaking the design and development of our system. The results of the survey indicated that data processing activities can be classified, both conceptually and operationally, into three modules: data recording and data entry, data management, and data analysis, and that the data management functions were those amenable to generalization. Based on our survey and the varying needs of our studies, we selected a "mixed" hardware environment, using both a computer center mainframe and microcomputers. We created the systems using commercially available software, including a mainframe database manager and mainframe statistics packages, microcomputer data entry software, and a communications package to link the two environments. Our strategy was to buy software, when possible, rather than to build custom programs, and to let software tools govern hardware needs. Hardware independence, price, and functional capability directed our software choices, while hardware selection was constrained most importantly by available software, then by budget, by available computing resources, and finally by the marketplace. The system has been used successfully in three studies differing in design, size, data collection locale, and rate of data accrual.     

基于PCI总线的磁共振成像数据采集卡设计

目的为小型磁共振成像装置设计专用的高速数据采集卡.方法采用高速模数转换器ADS 804对MRI复数模拟信号进行数字化采样,用静态存储器(SRAM)暂存这数字化信号数据.扫描完一幅图像数据后再把数据从SRAM读入计算机.对模数转换器ADC和静态存储器SRAM的所有逻辑控制信号包括写入ADC的地址均由现场可编程器件FPGA产生.对FPGA读、写和对AD的读出均使用并行总线,由PCI 9052总线控制器进行控制.结果用甚高速硬件描述语言Foundation 3.1软件对FPGA进行设计,并对其产生的控制逻辑电路进行了功能仿真模拟,得到了可行的结果.结论用硬件描述语言VHDL对FPGA进行数字逻辑电路设计是很方便的,修改纠错也很容易.     

基于PCI总线的MRI数字频率源设计

目的为小型磁共振成像(MRI)装置设计频率能够高速切换、相位和幅度可调的数字化频率源,同时产生成像需要的3路梯度波形.方法采用直接数字频率合成器件AD 9854,产生相位和幅度可调的高频信号;D/A转换器MAX527产生三路梯度信号;PCI 9052作为PCI总线到local控制端的桥;复杂可编程逻辑器件(CPLD)XC 95108对数据线、地址线和控制线进行译码后控制AD 9854和MAX 527.结果对由CPLD产生的数据和控制逻辑信号用专用的Modelsim软件进行了功能仿真和时序仿真,得到了可行的结果.结论VHDL具有强大的语言描述功能,非常适合单个模块的设计,而原理图输入方式则适合于各个模块的连接和有关时序调整的设计,采用VHDL和原理图结合的方法可以很方便地对CPLD的内部控制逻辑电路进行设计.     

Comparison of signal-to-noise ratio of myoelectric filters for prosthesis control.

A comparison of signal-to-noise ratios and rise times was performed on several myoelectric filters used for muscle-force estimation and prosthesis control. Linear, averaging, and adaptive filters were compared using single as well as multiple electrode pairs (spatial filtering). The filters were matched for having the same rise time (0-95%) and the signal-to-noise ratios were measured off-line using the same myoelectric signal recording. The linear filter was a low-pass filter with a time constant of 80 ms. The averaging filter had an averaging time of 250 ms. The adaptive filter was the same as is used in the Utah Artificial Arm. The adaptive filter varied its time constant according to the rate of change of the signal mean. If the rate was high, the time constant was set low. If the rate was low, the time constant was set high. Spatial filtering is where the myoelectric signals from four cutaneous sites over the same muscle were summed, that is, spatially filtered, and the resultant signal was smoothed by the linear, averaging, or adaptive filter. Significant improvement in the signal-to-noise ratio has been shown over conventional linear or averaging filters when using spatial and adaptive filtering, both when used separately and when used together.     

Comparison of physiological motion filters for in vivo cardiac ARFI

Acoustic radiation force impulse (ARFI) imaging is being utilized to investigate mechanical properties ofcardiac tissue. The underlying physiological motion, however, presents a major challenge. This paper aims to investigate the effectiveness of various physiological motion filters using in vivo canine data with a simulated ARFI push pulse. Ideally, the motion filter will exactly model the physiological motion and, when subtracted from the total displacement, leave only the simulated ARFI displacement profile. We investigated three temporal quadratic motion filters: (1)interpolation, (2) extrapolation and (3) a weighted technique. Additionally, the various motion filters were compared when using 1-D versus 2-D autocorrelation methods to estimate motion. It was found that 2D-autocorrelation always produced better physiological motion estimates regardless of the type of filter used. The extrapolation filter gives the most accurate estimate of the physiological motion at times immediately after the ARFI push (0.1 ms) while a close-time interpolation filter using displacement estimates at times before full tissue recovery gives the most accurate estimates at later times after the ARFI push (0.7 ms). While improvements to the motion filter during atrial systole and the onset of ventricular systole are needed, the weighted, close-time interpolation and extrapolation motion filters all offer promising results for estimating cardiac physiological motion more accurately, while allowing faster ARFI frame rates than previous motion filters. This study demonstrates the ability to eliminate physiological motion in a clinically-feasible manner, opening the door for more extensive clinical experimentation.     

Adaptive Kalman filtering for real-time mapping of the visual field

This paper demonstrates the feasibility of real-time mapping of the visual field for clinical applications. Specifically, three aspects of this problem were considered: (1) experimental design, (2) statistical analysis, and (3) display of results.Proper experimental design is essential to achieving a successful outcome, particularly for real-time applications. A random-block experimental design was shown to have less sensitivity to measurement noise, as well as greater robustness to error in modeling of the hemodynamic impulse response function (IRF) and greater flexibility than common alternatives. In addition, random encoding of the visual field allows for the detection of voxels that are responsive to multiple, not necessarily contiguous, regions of the visual field.Due to its recursive nature, the Kalman filter is ideally suited for real-time statistical analysis of visual field mapping data. An important feature of the Kalman filter is that it can be used for nonstationary time series analysis. The capability of the Kalman filter to adapt, in real time, to abrupt changes in the baseline arising from subject motion inside the scanner and other external system disturbances is important for the success of clinical applications.The clinician needs real-time information to evaluate the success or failure of the imaging run and to decide whether to extend, modify, or terminate the run. Accordingly, the analytical software provides real-time displays of (1) brain activation maps for each stimulus segment, (2) voxel-wise spatial tuning profiles, (3) time plots of the variability of response parameters, and (4) time plots of activated volume.     

数字化多深度脉冲波超声多普勒系统的设计与实验研究

目的设计一套数字化脉冲波超声多普勒系统,以实现多深度血流频谱分析和显示.方法首先开发了一块PCI接口的数据采集卡,用于采集正交模拟解调后的超声回波信号,然后在PC平台上对数据进行了累加、壁滤波、谱分析等分析处理.结果导管水流测量和人体血流测量两组实验结果验证了算法的正确性,表明在正交模拟解调后对数据进行模数转换,利用数字信号处理的手段对数据分析处理,完全可以替代传统系统中模拟电路构成的距离选通、积分、采样保持和壁滤波等环节.结论相对于传统的模拟血流测量装置,本系统在稳定性和可移植性方面更具有优势,不仅可方便实现多深度的谱分析和显示,还可扩充更多功能.     

Doppler Ultrasound Simulation Model for Pulsatile Flow with Nonaxial Components

A numerical model that can produce pulsed Doppler signals for nonaxial, pulsatile flow is presented. The model takes into account both hemodynamic and acoustic factors that affect the Doppler signal, such that a wide range of flow patterns and arbitrary transducer types can be simulated. The physics of blood flow is modeled by solving the Navier-Stokes equations utilizing a finite element technique, and the acoustic field is modeled using the acoustic impulse response method. The model was validated by comparison to the Womersley theory. The median deviation was 3.45%. Doppler signals from flow through a 50% stenosis were also simulated. The calculated spectra demonstrated the changing flow patterns from jets and vortices. This new computer model can be used to test spectral analysis tools on simulated Doppler signals, whose underlying flow patterns are of clinical importance.     

Adaptive clutter filtering via blind source separation for two-dimensional ultrasonic blood velocity measurement

A method for adaptive clutter rejection via blind source separation (BSS) using principal and independent component analyses is presented in application to blood velocity measurement in the carotid artery. In particular, the filtering method's efficacy for eliminating clutter and preserving lateral blood flow signal components is presented. The performance of IIR filters is compromised by shorth data ensembles (10 to 20 temporal samples) as implemented for color-flow and high frame-rate imaging due to initialization requirements. Further, the ultrasonic imaging system's transfer function maps axial wall and lateral blood motion to overlapping spectra. As such, frequency domain-based approaches to wall filtering are ineffective for distinguishing wall from blood motion signals. Rather than operating in the frequency domain. BSS performs clutter rejection by decomposing the input data ensemble into N constitutive source signals in time, where N is the ensemble length. Source signal energy coupled with respective signal depth and time course profiles reveal which source signals correspond to blood, noise and clutter components. Clutter components may then be removed without disruption of lateral blood flow information needed for two-dimensional blood velocity measurement. A simplistic data simulation is employed to offer an intuitive understanding of BSS methods for signal separation. The adaptive BSS filter is further demonstrated using a Field II simulation of blood flow through the carotid artery including tissue motion. BSS clutter filter performance is compared to the performance of FIR, IIR and polynomial regression clutter filters. Finally, the filter is employed for clinical application using a Siemens Elegra scanner, carotid artery data with lateral blood flow collected from healthy volunteers, and Speckle Tracking; velocity magnitude and angle profiles are shown. Once again, the BSS clutter filter is contrasted to FIR, IIR and polynomial regression clutter filters using clinical examples. Velocities computed with Speckle Tracking after BSS wall filtering are highest in the center of the artery and diminish to low velocities near the vessel walls, with velocity magnitudes consistent with physiological expectations. These results demonstrate that the BSS adaptive filter sufficiently suppresses wall motion signal for clinical lateral blood velocity measurement using data ensembles suitable for color-flow and high frame-rate imaging.     

采集表面肌电信号应用于动作识别的可行性

背景:文献表明上肢前臂运动时所产生的表面肌电信号具有非线性特征,而肢体运动时肌电信号又呈现出非平稳特性.目的:设计一种简单的拾取电路采集表面肌电信号,拟应用于动作肌电信号的特征识别.方法:根据表面肌电信号的特点,设计高共模抑制比的前端放大电路,抑制共模干扰;采用低通滤波电路,有源双T带阻滤波器对信号进行去噪处理;对采集得到的信号进行小波包变换,得到信号的特征量.结果与结论:所设计的表面肌电信号检测电路具有较高共模抑制比,并能有效地滤除50 Hz工频信号,可以满足肌电信号采集电路的基本要求.肌电信号的处理结果表明采用子频段能量值的方法可以区分手部4种不同动作.     

A Comparative Analysis of Signal Processing Methods for Motion-Based Rate Responsive Pacing

Pacemakers that augment heart rate (HR) by sensing body motion have been the most frequently prescribed rate responsive pacemakers. Many comparisons between motion-based rate responsive pacemaker models have been published. However, conclusions regarding specific signal processing methods used for rate response (e.g., filters and algorithms) can be affected by device-specific features. To objectively compare commonly used motion sensing filters and algorithms, acceleration and ECG signals were recorded from 16 normal subjects performing exercise and daily living activities. Acceleration signals were filtered (1–4 or 15-Hz band-pass), then processed using threshold crossing (TC) or integration (IN) algorithms creating four filter/algorithm combinations. Data were converted to an acceleration indicated rate and compared to intrinsic HR using root mean square difference (RMSd) and signed RMSd. Overall, the filters and algorithms performed similarly for most activities. The only differences between filters were for walking at an increasing grade (1–4 Hz superior to 15-Hz) and for rocking in a chair (15-Hz superior to 1–4 Hz). The only differences between algorithms were for bicycling (TC superior to IN), walking at an increasing grade (IN superior to TC), and holding a drill (IN superior to TC). Performance of the four filter/algorithm combinations was also similar over most activities. The 1–4/IN (filter [Hz]/algorithm) combination performed best for walking at a grade, while the 15/TC combination was best for bicycling. However, the 15/TC combination tended to be most sensitive to higher frequency artifact, such as automobile driving, downstairs walking, and hand drilling. Chair rocking artifact was highest for 1–4/IN. The RMSd for bicycling and upstairs walking were large for all combinations, reflecting the nonphysiological nature of the sensor. The 1–4/TC combination demonstrated the least intersubject variability, was the only filter/algorithm combination insensitive to changes in footwear, and gave similar RMSd over a large range of amplitude thresholds for most activities. In conclusion, based on overall error performance, the preferred filter/algorithm combination depended upon the type of activity.