Louis Shue

Heart sound as a biometric

In this paper, we propose a novel biometric method based on heart sound signals. The biometric system comprises an electronic stethoscope, a computer equipped with a sound card and the software application. Our approach consists of a robust feature extraction scheme which is based on cepstral analysis with a specified configuration, combined with Gaussian mixture modeling. Experiments have been conducted to determine the relationship between various parameters in our proposed scheme. It has been demonstrated that heart sounds should be processed within segments of 0.5s and using the full resolution in frequency domain. Also, higher order cepstral coefficients that carry information on the excitation proved to be useful. A preliminary test of 128 heart sounds from 128 participants was collected to evaluate the uniqueness of the heart sounds. The HTK toolkit produces a 99% recognition rate with only one mismatch. Next, a more comprehensive test consisting almost 1000 heart sounds collected from 10 individuals over a period of 2 months yields a promising matching accuracy of 96% using the proposed feature and classification algorithm. A real-time heart sound authentication system is then built and can be used in two modes: to identify a particular individual or to verify an individuals claimed identity.

On state-estimation of a two-state hidden Markov model with quantization

We consider quantization from the perspective of minimizing filtering error when quantized instead of continuous measurements are used as inputs to a nonlinear filter, specializing to discrete-time two-state hidden Markov models (HMMs) with continuous-range output. An explicit expression for the filtering error when continuous measurements are used is presented. We also propose a quantization scheme based on maximizing the mutual information between quantized observations and the hidden states of the HMM.

Adaptive mean and variance filter for detection of dim point-like targets

The problem of detecting small target in IR imagery has attracted much research effort over the past few decades. As opposed to early detection algorithms which detect targets spatially in each image and then apply tracking algorithm, more recent approaches have used multiple frames to incorporate temporal as well as spatial information. They often referred to as track before detect algorithms. This approach has shown promising results particularly for detection of dim point-like targets. However, the computationally complexity has prohibited practical usage for such algorithms. This paper presents an adaptive, recursive and computation efficient detection method. This detection algorithm updates parameters and detects occurrence of targets as new frame arrived without storing previous frames, thus achieved recursiveness. Besides, the target temporal intensity change is modeled by two Gaussian distribution with different mean and variance. The derivation of this generalized model has taken account of the wide variation of target speed, therefore detects wider range of targets.

Performance evaluation of adaptive dual microphone systems

In this paper, the performance of the adaptive noise cancellation method is evaluated on several possible dual microphone system (DMS) configurations. Two groups of DMS are taken into consideration with one consisting of two omnidirectional microphones and another involving directional microphones. The properties of these methods are theoretically analyzed under incoherent, coherent and diffuse noise respectively. To further investigate their achievable noise reduction performance in real situations, a series of experiments in simulated and real office environments are carried out. Some recommendations are given at the end for designing and choosing the suitable methods in real applications.

Asymptotic smoothing errors for hidden Markov models

In this paper, the asymptotic smoothing error for hidden Markov models (HMMs) is investigated using hypothesis testing ideas. A family of HMMs is studied parametrised by a positive constant /spl epsiv/, which is a measure of the frequency of change. Thus, when /spl epsiv//spl rarr/0, the HMM becomes increasingly slower moving. We show that the smoothing error is O(/spl epsiv/). These theoretical predictions are confirmed by a series of simulations.

Fetal Heart Signal Monitoring with Confidence Factor

In this paper we present a PDA-based fetal heart monitor that is able to provide instantaneous fetal heart rate (FHR) for the pregnant women. A modified spectral subtraction algorithm is first used to remove the unwanted stationary background noise from the noisy fetal heart sound. The AM/FM modulation technique is then employed to make the fetal heart sound more audible so that both pregnant women and gynaecologists can identify the rhythmic fetal heart beat sounds easily. A real-time algorithm is proposed to extract the fetal heart rate information from the weak and noisy signals. Furthermore, based on the signal spectrum distribution, a confidence factor (CF) is designed to indicate the reliability of the estimated fetal heart rate in real time. The device has been tested in a local hospital on a sample group of 41 pregnant women. Our finding shows that an approximate 75% of the pregnant mothers are able to hear their babys heart sound clearly using our device. Tests are also carried out to compare the fetal heart rate calculated using our device and the existing ultrasound cardiotocography (CTG) machine. In most time our device functions properly and provides results close to the CTG records

Development of a compact two-sensor directional audio-capturing device

A directional audio-capturing device is highly desirable for normal communication in a noisy environment, and to enhance the quality of speech signal for the hearing impaired. In this paper, we propose a compact directional audio-capturing device which reduces the background noise in relation to speech signal which originates from a desired direction. This device contains three functional units: (1) a differential microphone formed by two omni-directional microphones connected in an endfire orientation, (2) adaptive beamforming and (3) echo shaping of the residual output signals to further improve the signal-to-noise ratio. The adaptation is based on a control scheme using the differences in the spatial responses between the omni-directional and the differential microphone signals. A post-processing scheme using echo-shaping filter is used to further suppress any residual interferences. A real-time implementation of our proposed scheme has been constructed and its performance measured. The experiments indicate a polar pattern with good interference cancellation, with an average interference suppression of as much as 22 dB. Our experiments also indicate lower speech distortion using our proposed system. In term of speech quality, the improvement is indicated by the mean-opinion-score (MOS) scale. The MOS has been obtained from both subjective tests conducted using ten listeners, as well as using the perceptual evaluation of speech quality tool indicated in ITU-T standards document.

A new approach for speaker tracking in reverberant environment

A scheme for detecting and locating speech signals in the presence of reverberations using a linear array is proposed. The equispaced linear array with a plurality of onmi-directional microphones is decomposed into two groups. Pairs of virtual and steerable directional microphones are then generated by using the frequency invariant beamforming technique for time delay estimations. This enables the microphone array to behave like ears in a human-like fashion to enhance the likelihood of valid speaker direction estimation. Additional decision rules are incorporated to enhance the robustness of the scheme.

An adaptive microphone array with local acoustic sensitivity

In this paper, a microphone array with 3-D focal zone is proposed. The microphone array consists of one omni-directional and two uni-directional microphones. The microphone array is so constructed that a cross zone is formed such that only the sound within this zone is captured and any interferences outside the zone are effectively cancelled. The proposed framework is flexible in defining the location/size of the closed volume where the sound source of interest is located. Simulations have been carried out to demonstrate the 3-D spatial selectivity as well as the noise cancellation performance. The most important feature which differs from the previous works is that the super volumetric selectivity is realized by strategically use only three microphones, by which the overall apparatus acts as a virtual wireless close-talking microphone with confined position constrained in both distance and directions.

Complexity reduction in fixed-lag smoothing for hidden Markov models

We investigate approximate smoothing schemes for a class of hidden Markov models (HMMs), namely, HMMs with underlying Markov chains that are nearly completely decomposable. The objective is to obtain substantial computational savings. Our algorithm can not only be used to obtain aggregate smoothed estimates but can be used also to obtain systematically approximate full-order smoothed estimates with computational savings and rigorous performance guarantees, unlike many of the aggregation methods proposed earlier.