Signal Processing Stage Research Articles

Nonparametric Signal Processing Validation in T-Wave Alternans Detection and Estimation

Although a number of methods have been proposed for T-Wave Alternans (TWA) detection and estimation, their performance strongly depends on their signal processing stages and on their free parameters tuning. The dependence of the system quality with respect to the main signal processing stages in TWA algorithms has not yet been studied. This study seeks to optimize the final performance of the system by successive comparisons of pairs of TWA analysis systems, with one single processing difference between them. For this purpose, a set of decision statistics are proposed to evaluate the performance, and a nonparametric hypothesis test (from Bootstrap resampling) is used to make systematic decisions. Both the temporal method (TM) and the spectral method (SM) are analyzed in this study. The experiments were carried out in two datasets: first, in semisynthetic signals with artificial alternant waves and added noise; second, in two public Holter databases with different documented risk of sudden cardiac death. For semisynthetic signals (SNR = 15dB), after the optimization procedure, a reduction of 34.0% (TM) and 5.2% (SM) of the power of TWA amplitude estimation errors was achieved, and the power of error probability was reduced by 74.7% (SM). For Holter databases, appropriate tuning of several processing blocks, led to a larger intergroup separation between the two populations for TWA amplitude estimation. Our proposal can be used as a systematic procedure for signal processing block optimization in TWA algorithmic implementations.

Assessment of Conductive Dysfunction: Wideband Acoustic Immittance

The conductive mechanism plays an important role in our hearing: the first stage of signal processing in the auditory system. While it consists of the ear canal, the crucial portion is the middle ear system, which transforms airborne sound into mechanical vibration and helps improve sound transmission into the fluid-filled inner ear. Hearing loss due to dysfunction of the middle ear system may be threatening to the quality of life for humans. For example, conductive hearing loss may significantly impact normal speech and language development of children. Assessment of middle ear dysfunction is essential for audiological diagnosis of hearing loss and differential diagnosis of ear diseases. For instance, middle ear dysfunction may cloud outcomes of newborn hearing screening. Acoustic immittance is the current clinical technique for assessment of middle ear dysfunction. The major procedures include tympanometry and acoustic reflex test. In these procedures, a single-frequency probe tone (e.g., 226 Hz and 1000 Hz) is used to estimate the acoustic impudence/admittance of the middle ear. Although they have been a clinical routine in audiology since 1970s, value of these procedures in assessment of conductive dysfunction has been limited.

Efficient FPGA Hardware Reuse in a Multiplierless Decimation Chain

In digital communications, an usual reception chain requires many stages of digital signal processing for filtering and sample rate reduction. For satellite on board applications, this need is hardly constrained by the very limited hardware resources available in space qualified FPGAs. This short paper focuses on the implementation of a dual chain of 14 stages of cascaded half band filters plus 2 : 1 decimators for complex signals (in-phase and quadrature) with minimal hardware resources, using a small portion of an UT6325 Aeroflex FPGA, as a part of a receiver designed for a low data rate command and telemetry channel.

Cerebellar Cortex Granular Layer Interneurons in the Macaque Monkey Are Functionally Driven by Mossy Fiber Pathways through Net Excitation or Inhibition

The granular layer is the input layer of the cerebellar cortex. It receives information through mossy fibers, which contact local granular layer interneurons (GLIs) and granular layer output neurons (granule cells). GLIs provide one of the first signal processing stages in the cerebellar cortex by exciting or inhibiting granule cells. Despite the importance of this early processing stage for later cerebellar computations, the responses of GLIs and the functional connections of mossy fibers with GLIs in awake animals are poorly understood. Here, we recorded GLIs and mossy fibers in the macaque ventral-paraflocculus (VPFL) during oculomotor tasks, providing the first full inventory of GLI responses in the VPFL of awake primates. We found that while mossy fiber responses are characterized by a linear monotonic relationship between firing rate and eye position, GLIs show complex response profiles characterized by “eye position fields” and single or double directional tunings. For the majority of GLIs, prominent features of their responses can be explained by assuming that a single GLI receives inputs from mossy fibers with similar or opposite directional preferences, and that these mossy fiber inputs influence GLI discharge through net excitatory or inhibitory pathways. Importantly, GLIs receiving mossy fiber inputs through these putative excitatory and inhibitory pathways show different firing properties, suggesting that they indeed correspond to two distinct classes of interneurons. We propose a new interpretation of the information flow through the cerebellar cortex granular layer, in which mossy fiber input patterns drive the responses of GLIs not only through excitatory but also through net inhibitory pathways, and that excited and inhibited GLIs can be identified based on their responses and their intrinsic properties.

A dynamic multi-channel speech enhancement system for distributed microphones in a car environment

Supporting multiple active speakers in automotive hands-free or speech dialog applications is an interesting issue not least due to comfort reasons. Therefore, a multi-channel system for enhancement of speech signals captured by distributed distant microphones in a car environment is presented. Each of the potential speakers in the car has a dedicated directional microphone close to his position that captures the corresponding speech signal. The aim of the resulting overall system is twofold: On the one hand, a combination of an arbitrary pre-defined subset of speakers’ signals can be performed, e.g., to create an output signal in a hands-free telephone conference call for a far-end communication partner. On the other hand, annoying cross-talk components from interfering sound sources occurring in multiple different mixed output signals are to be eliminated, motivated by the possibility of other hands-free applications being active in parallel. The system includes several signal processing stages. A dedicated signal processing block for interfering speaker cancellation attenuates the cross-talk components of undesired speech. Further signal enhancement comprises the reduction of residual cross-talk and background noise. Subsequently, a dynamic signal combination stage merges the processed single-microphone signals to obtain appropriate mixed signals at the system output that may be passed to applications such as telephony or a speech dialog system. Based on signal power ratios between the particular microphone signals, an appropriate speaker activity detection and therewith a robust control mechanism of the whole system is presented. The proposed system may be dynamically configured and has been evaluated for a car setup with four speakers sitting in the car cabin disturbed in various noise conditions.

Wavelet‐based automatic cry recognition system for detecting infants with hearing‐loss from normal infants

Infant cry is a multimodal and dynamic behaviour that it contains a lot of information. Goal of this investigation is recognition of two groups of infants by new acoustic feature that has not used in infant cry classification. The cry of deaf infants and normal hearing infants is studied. ‘Mel filter-bank discrete wavelet coefficients (MFDWCs)’ have been extracted as feature vector. Infant cry classification is a pattern recognition problem such as ‘automatic speech recognition’, which in signal processing stage the authors performed some pre-processing included silence elimination, filtering, pre-emphasising and, segmentation. After applying the discrete wavelet transform on the Mel scaled log filter bank energies of a cry signal frames, MFDWCs feature vector was extracted. The feature vector, MFDWCs, of each cry sample has large length, so they used principle components analysis to reduce in feature space dimension, after training of neural network as classifier, they achieved to 93.2% correction rate in cry recognition of test data set. This result shows better efficiency in comparison with previous familiarised approaches.

Electro-optic acquisition system for ECG wearable sensor applications

In the past few years a remarkable progress has been made in the design of sensors for wearable devices. Nevertheless, the existent devices are difficult to integrate, mainly due to the quantity of electrical interconnections and components required at the sensing places. This leads to the need for a new generation of wearable sensors. Photonic sensors have been presented in the medical field as a valuable alternative where power supply, electromagnetic interference and integration constitute a challenge. Therefore, this paper presents an electro-optic (EO) acquisition system designed for wearable Electrocardiogram (ECG) monitoring devices. The system includes a Lithium Niobate Mach-Zehnder Interferometer (MZI) modulator as the sensing element, and an optoelectronic signal conversion and processing stage. Tests were made in order to evaluate system performance in terms of signal amplification and sensitivity, frequency response and linearity. Obtained results have shown a suitable sensor's sensitivity of 20μV and a frequency response of 60dB flat from 0.2 to 40Hz. Clinical sensor's performance was tested considering the requirements for evaluation of ECG. Results were compared with clinical standard electronics. Clear ECGs can be obtained with the EO sensor, showing adequate and reliable clinical performance. This EO sensor can be integrated into wearable materials being a suitable alternative for clinical cardiac monitoring.

Improvement for Speech Signal based on Post Wiener Filter and Adjustable Beam-Former

In this study, a two-stage filter structure is introduced for speech enhancement. The first stage is an adjustable filter and sum beam-former with four-microphone array. The control of beam-forming filter is realized by adjusting only a single control variable. Different from the adaptive beam-forming filter, the proposed filter structure does not bring to any adaptive error noise, thus, it also does not bring the trouble to the second stage of the speech signal processing. The second stage of the proposed filter is a Wiener filter. The estimation of signal’s power spectrum for Wiener filter is realized by cross-correlation between primary outputs of two adjacent directional beams. This estimation is based on the assumption that the noise outputs of the two adjacent directional beams come from two independent noise source but the speech outputs come from the same speech source. The simulation results shown that the proposed algorithm can improve the Signal-Noise-Ratio (SNR) about 6 dB.

From the intrinsic properties to the functional role of a neuron phenotype: an example from electric fish during signal trade-off

This review deals with the question: what is the relationship between the properties of a neuron and the role that the neuron plays within a given neural circuit? Answering this kind of question requires collecting evidence from multiple neuron phenotypes and comparing the role of each type in circuits that perform well-defined computational tasks. The focus here is on the spherical neurons in the electrosensory lobe of the electric fish Gymnotus omarorum. They belong to the one-spike-onset phenotype expressed at the early stages of signal processing in various sensory modalities and diverse taxa. First, we refer to the one-spike neuron intrinsic properties, their foundation on a low-threshold K(+) conductance, and the potential roles of this phenotype in different circuits within a comparative framework. Second, we present a brief description of the active electric sense of weakly electric fish and the particularities of spherical one-spike-onset neurons in the electrosensory lobe of G. omarorum. Third, we introduce one of the specific tasks in which these neurons are involved: the trade-off between self- and allo-generated signals. Fourth, we discuss recent evidence indicating a still-undescribed role for the one-spike phenotype. This role deals with the blockage of the pathway after being activated by the self-generated electric organ discharge and how this blockage favors self-generated electrosensory information in the context of allo-generated interference. Based on comparative analysis we conclude that one-spike-onset neurons may play several functional roles in animal sensory behavior. There are specific adaptations of the neuron's 'response function' to the circuit and task. Conversely, the way in which a task is accomplished depends on the intrinsic properties of the neurons involved. In short, the role of a neuron within a circuit depends on the neuron and its functional context.

A Switched-Capacitor Front-End for Velocity-Selective ENG Recording

Multi-electrode cuffs (MECs) have been proposed as a means for extracting additional information about the velocity and direction of nerve signals from multi-electrode recordings. This paper discusses certain aspects of the implementation of a system for velocity selective recording (VSR) where multiple neural signals are matched and summed to identify excited axon populations in terms of velocity. The approach outlined in the paper involves the replacement of the digital signal processing stages of a standard delay-matched VSR system with analogue switched-capacitor (SC) delay lines which promises significant savings in both size and power consumption. The system specifications are derived and two circuits, each composed of low-noise preamplifiers connecting to a 2nd rank SC gain stage, are evaluated. One of the systems provides a single-ended SC stage whereas the other system is fully differential. Both approaches are shown to provide the low-noise, low-power operation, practically identical channel gains and sample delay range required for VSR. Measured results obtained from chips fabricated in 0.8 μ m CMOS technology are reported.

HEARING DEVICE WITH RF COMMUNICATION

In a hearing device with an audio signal processing stage (3, 7, 5) and an Rf signal processing stage (9, 11) the Rf signal processing stage is realized in one module (13a), whereas the audio signal processing stage is realized in a second module (13b). The two modules are releasably interlinked by means of a releasable positive locking link (15).

Intrasaccadic suppression is dominated by reduced detector gain

Human vision requires fast eye movements (saccades). Each saccade causes a self-induced motion signal, but we are not aware of this potentially jarring visual input. Among the theorized causes of this phenomenon is a decrease in visual sensitivity before (presaccadic suppression) and during (intrasaccadic suppression) saccades. We investigated intrasaccadic suppression using a perceptual template model (PTM) relating visual detection to different signal-processing stages. One stage changes the gain on the detector's input; another increases uncertainty about the stimulus, allowing more noise into the detector; and other stages inject noise into the detector in a stimulus-dependent or -independent manner. By quantifying intrasaccadic suppression of flashed horizontal gratings at varying external noise levels, we obtained threshold-versus-noise (TVN) data, allowing us to fit the PTM. We tested if any of the PTM parameters changed significantly between the fixation and saccade models and could therefore account for intrasaccadic suppression. We found that the dominant contribution to intrasaccadic suppression was a reduction in the gain of the visual detector. We discuss how our study differs from previous ones that have pointed to uncertainty as an underlying cause of intrasaccadic suppression and how the equivalent noise approach provides a framework for comparing the disparate neural correlates of saccadic suppression.

Bladed disc crack diagnostics using blade passage signals

One of the major potential faults in a turbo fan engine is the crack initiation and propagation in bladed discs under cyclic loads that could result in the breakdown of the engines if not detected at an early stage. Reliable fault detection techniques are therefore in demand to reduce maintenance cost and prevent catastrophic failures. Although a number of approaches have been reported in the literature, it remains very challenging to develop a reliable technique to accurately estimate the health condition of a rotating bladed disc. Correspondingly, this paper presents a novel technique for bladed disc crack detection through two sequential signal processing stages: (1) signal preprocessing that aims to eliminate the noises in the blade passage signals; (2) signal postprocessing that intends to identify the crack location. In the first stage, physics-based modeling and interpretation are established to help characterize the noises. The crack initiation can be determined based on the calculated health monitoring index derived from the sinusoidal effects. In the second stage, the crack is located through advanced detrended fluctuation analysis of the preprocessed data. The proposed technique is validated using a set of spin rig test data (i.e. tip clearance and time of arrival) that was acquired during a test conducted on a bladed military engine fan disc. The test results have demonstrated that the developed technique is an effective approach for identifying and locating the incipient crack that occurs at the root of a bladed disc.

Purinergic Modulation of Neuronal Activity in Developing Auditory Brainstem

In the developing nervous system, spontaneous neuronal activity arises independently of experience or any environmental input. This activity may play a major role in axonal pathfinding, refinement of topographic maps, dendritic morphogenesis, and the segregation of axonal terminal arbors. In the auditory system, endogenously released ATP in the cochlea activates inner hair cells to trigger bursts of action potentials (APs), which are transferred to the central auditory system. Here we show the modulatory role of purinergic signaling beyond the cochlea, i.e., the developmentally regulated and cell-type-specific depolarizing effects on auditory brainstem neurons of Mongolian gerbil. We assessed the effects of P2X receptors (P2XRs) on neuronal excitability from prehearing to early stages of auditory signal processing. Our results demonstrate that in neurons expressing P2XRs, extracellular ATP can evoke APs in sync with Ca(2+) signals. In cochlear nucleus (CN) bushy cells, ATP increases spontaneous and also acoustically evoked activity in vivo, but these effects diminish with maturity. Moreover, ATP not only augmented glutamate-driven firing, but it also evoked APs in the absence of glutamatergic transmission. In vivo recordings also revealed that endogenously released ATP in the CN contributes to neuronal firing activity by facilitating AP generation and prolonging AP duration. Given the enhancing effect of ATP on AP firing and confinement of P2XRs to certain auditory brainstem nuclei, and to distinct neurons within these nuclei, it is conceivable that purinergic signaling plays a specific role in the development of neuronal brainstem circuits.

Development and implementation of a system to measure the response of quartz crystal resonator based gas sensors using a field-programmable gate array

The development of gas sensors based on quartz crystal resonators requires the use of a frequency counter to measure the sensor response. However, commercial frequency counters have at most two channels, and in odour sensory systems (electronic noses), arrays of at least eight sensors are used. Furthermore, it is also desirable that the signal processing and data analysis stage can be included in the same system. A field-programmable gate array (FPGA) can provide a solution to these kinds of problems. This work involves the development of a system to measure the response of quartz crystal resonators, which is implemented using a high resolution frequency counter using an FPGA capable of processing and storing the data in 32-bit registers. Data transfer and acquisition were performed using a microcontroller. The virtual instrumentation software LabVIEW was used for the sensor response display and data storage in a computer. A frequency range from 0 Hz to 100 MHz with a resolution and stability of 1 Hz was achieved using a timebase of 1 s. Tests were performed using gas sensors to obtain real data. The system was escalated to four channels, verifying that it behaves in a correct and stable way.

RADAR TARGET DETECTION USING HIDDEN MARKOV MODELS

Standard radar detection process requires that the sensor output is compared to a predetermined threshold. The threshold is selected based on a-priori knowledge available and/or certain assumptions. However, any knowledge and/or assumptions become inadequate due to the presence of multiple targets with varying signal return and usually non stationary background. Thus, any fixed predefined threshold may result in either increased false alarm rate or increased track loss. Even approaches where the threshold is adaptively varied will not perform well in situations when the signal return from the target of interest is too low compared to the average level of the background. Track-before-detect techniques eliminate the need for a detection threshold and provide detecting and tracking targets with lower signal-to-noise ratios than standard methods. However, although track-before-detect techniques eliminate the need for detection threshold at sensor’s signal processing stage, they often use tuning thresholds at the output of the filtering stage. This paper presents a Hidden Markov Model based target detection method that avoids any thresholding at any stage of the detection process. Moreover, since the proposed Hidden Markov Model method is based on the target motion models, the output of the detection process can easily be employed for maneuvering target tracking.

Pulsed laser noise analysis and pump-probe signal detection with a data acquisition card

A photodiode and data acquisition card whose sampling clock is synchronized to the repetition rate of a laser are used to measure the energy of each laser pulse. Simple analysis of the data yields the noise spectrum from very low frequencies up to half the repetition rate and quantifies the pulse energy distribution. When two photodiodes for balanced detection are used in combination with an optical modulator, the technique is capable of detecting very weak pump-probe signals (ΔI/I(0) ~ 10(-5) at 1 kHz), with a sensitivity that is competitive with a lock-in amplifier. Detection with the data acquisition card is versatile and offers many advantages including full quantification of noise during each stage of signal processing, arbitrary digital filtering in silico after data collection is complete, direct readout of percent signal modulation, and easy adaptation for fast scanning of delay between pump and probe.

Design of a modular signal processing board (MSPB) for gamma-ray imaging applications

Abstract In this paper a new modular signal processing board (MSPB) for high-resolution gamma-ray computed tomography (GCT) is presented. The MSPB is optimised for parallel signal processing of eight detector channels operating in pulse counting mode. Signal processing stages comprise of variable gain amplifiers, pulse height discrimination stages, 13-bit counters with corresponding latches as well as logic circuitry for coordinated data transfer with a multitude of MSPBs. The digital signal processing units are realised in commercially available complex programmable logic devices (CPLD). Each MSPB is addressable by an 8-bit DIP-switch, which allows the use of up to 256 modules or 2048 detector pixels within one detector system. The geometry of the MSPB allows a multiple and seamless detector module arrangement, which eases the adaptation of a given gamma-ray detector system to specific industrial and laboratory applications. The choice of the electronic devices and the thermal design was optimised for low power consumption in order to minimise internal heat production, which would affect the characteristics of the detector's intrinsic gain strongly. Thermal measurements have been executed to prove the functionality of the thermal design.

Development of a GPU-Based Two-Way Time Transfer Modem

We have developed a new two-way time transfer modem to improve the time transfer precision of remote clock comparison. As a timing signal, we apply a binary offset carrier, which is similar to those signals used for the next-generation Global Navigation Satellite Systems. We took advantage of versatile A/D and D/A converters, and most of the digital signal processing stages were realized by software, running on an off-the-shelf PC. This enabled us to realize the complete system with cheaper equipment, leading to an affordable low-cost modem. For the real-time digital signal processing stages implemented in software, we relied on a graphics processing unit (GPU) developed for computer game enthusiast. The developed modem can receive four channels at the same time with a single GPU card. We performed two-way satellite time transfer experiments using these modems between Japan and Taiwan. The obtained results are consistent within 200 ps with respect to the results of GPS carrier phase time transfer. As a consequence, we improved the time transfer precision by nearly one order of magnitude as compared to a conventional two-way modem without increasing the connection fees caused by commercial communication satellites.

Electronic-nose for detecting environmental pollutants: signal processing and analog front-end design

Environmental monitoring relies on compact, portable sensor systems capable of detecting pollutants in real-time. An integrated chemical sensor array system is developed for detection and identification of environmental pollutants in diesel and gasoline exhaust fumes. The system consists of a low noise floor analog front-end (AFE) followed by a signal processing stage. In this paper, we present techniques to detect, digitize, denoise and classify a certain set of analytes. The proposed AFE reads out the output of eight conductometric sensors and eight amperometric electrochemical sensors and achieves 91 dB SNR at 23.4 mW quiescent power consumption for all channels. We demonstrate signal denoising using a discrete wavelet transform based technique. Appropriate features are extracted from sensor data, and pattern classification methods are used to identify the analytes. Several existing pattern classification algorithms are used for analyte detection and the comparative results are presented.