Biomedical subjects

F K Lam

Publications and source records attributed to F K Lam.

At least 19 recordsLinked to original sources

PubMed2000

A novel system for simultaneous monitoring of locomotor and sound activities in animals.

This paper describes a PC-based system for simultaneous monitoring of locomotor and sound activities on small rodents. The displacement and location signals of the animal were first determined across consecutive video-frames, followed by marked data reduction to cater for long-term studies. At the same time, sounds generated by the animal were detected and the sound level was recorded as root-mean-square values at 1 s intervals. Preliminary data showed that such a multi-parametric monitor system could provide comprehensive information on the animal's activity.

Animals↗

PubMed2000

Multiscale characterization of chronobiological signals based on the discrete wavelet transform.

To compensate for the deficiency of conventional frequency-domain or time-domain analysis, this paper presents a multiscale approach to characterize the chronobiological time series (CTS) based on a discrete wavelet transform (DWT). We have shown that the local modulus maxima and zero-crossings of the wavelet coefficients at different scales give a complete characterization of rhythmic activities. We further constructed a tree scheme to represent those interacting activities across scales. Using the bandpass filter property of the DWT in the frequency domain, we also characterized the band-related activities by calculating energy in respective rhythmic bands. Moreover, since there is a fast and easily implemented algorithm for the DWT, this new approach may simplify the signal processing and provide a more efficient and complete study of the temporal-frequency dynamics of the CTS. Preliminary results are presented using the proposed method on the locomotion of mice under altered lighting conditions, verifying its competency for CTS analysis.

Animals↗

PubMed2000

Fuzzy EMG classification for prosthesis control.

This paper proposes a fuzzy approach to classify single-site electromyograph (EMG) signals for multifunctional prosthesis control. While the classification problem is the focus of this paper, the ultimate goal is to improve myoelectric system control performance, and classification is an essential step in the control. Time segmented features are fed to a fuzzy system for training and classification. In order to obtain acceptable training speed and realistic fuzzy system structure, these features are clustered without supervision using the Basic Isodata algorithm at the beginning of the training phase, and the clustering results are used in initializing the fuzzy system parameters. Afterwards, fuzzy rules in the system are trained with the back-propagation algorithm. The fuzzy approach was compared with an artificial neural network (ANN) method on four subjects, and very similar classification results were obtained. It is superior to the latter in at least three points: slightly higher recognition rate; insensitivity to overtraining; and consistent outputs demonstrating higher reliability. Some potential advantages of the fuzzy approach over the ANN approach are also discussed.

Algorithms↗

PubMed1999

A tracing evoked potential estimator.

The paper presents an adaptive Gaussian radial basis function neural network (RBFNN) for rapid estimation of evoked potential (EP). Usually, a recorded EP is severely contaminated by background ongoing activities of the brain. Many approaches have been reported to enhance the signal-to-noise ratio (SNR) of the recorded signal. However, non-linear methods are seldom explored due to their complexity and the fact that the non-linear characteristics of the signal are generally hard to determine. An RBFNN possesses built-in non-linear activation functions that enable the neural network to learn any function mapping. An RBFNN was carefully designed to model the EP signal. It has the advantage of being linear-in-parameter, thus a conventional adaptive method can efficiently estimate its parameters. The proposed algorithm is simple so that its convergence behaviour and performance in signal-to-noise ratio (SNR) improvement can be mathematically derived. A series of experiments carried out on simulated and human test responses confirmed the superior performance of the method. In a simulation experiment, an RBFNN having 15 hidden nodes was trained to approximate human visual EP (VEP). For detecting human brain stem auditory EP (BAEP), the approach (40 hidden nodes and convergence rate = 0.005) speeded up the estimation remarkably by using only 80 ensembles to achieve a result comparable to that obtained by averaging 1000 ensembles.

Electroencephalography↗

PubMed1998

Evoked potential estimation using modified time-sequenced adaptive filter.

A method called modified time-sequenced adaptive filtering (MTSAF) is applied to estimate evoked potential (EP) signals and track the temporal variations of EPs. The MTSAF consists of a set of adaptive filters (AFs), with each processing a time segment of EP data. After convergence, each AF reaches the best estimation of EP signals over its own time segment in terms of minimum mean squared error (MMSE). Numerical results of simulated and human EP data show that the MTSAF reaches better estimation of EPs than a conventional adaptive signal enhancer (ASE). With the MTSAF, the temporal variations of EPS across trials can be estimated to reveal more subtle variations of EPs, which may be of clinical value.

Algorithms↗

PubMed1998

Wavelet analysis of embolic heart sound detected by precordial Doppler ultrasound during continuous venous air embolism in dogs.

UNLABELLED: The spectrum of the embolic heart sounds (EHS) detected by precordial Doppler ultrasound has been previously characterized, but only on small volumes of venous air embolism (VAE). We sought to determine whether real-time wavelet analysis is useful in analyzing the signals of EHS and whether the embolic power of the EHS for larger volumes of air is proportionate to the volume of VAE that has been reported for small volumes of VAE. A series of small air boli (0.01, 0.02, 0.05, 0.07, 0.1, 0.15, 0.2, 0.3, 0.4, and 0.8 mL), followed by continuous infusion of larger volumes of air (0.8, 1.6, 2.4, 4.8, and 9.6 mL), was injected into the external jugular vein through a central catheter in seven pentobarbital-anesthetized dogs. We measured the spectrum of the Doppler heart sound (DHS) in a real-time manner by using wavelet analysis at different scales. Wavelet analysis at scale = 1 yielded satisfactory results in distinguishing abnormal EHS from normal DHS with high sensitivity (100%) and good positive predictive value (100%) compared with the conventional method, which requires an anesthesiologist to listen to the audio DHS signals in a real-time manner. There was a linear relationship (y = 1.08x + 7.89, r = 0.75, P < 0.001) between the cumulative embolic power of the EHS and the air volume introduced in the form of either bolus or continuous infusion. The 95% confidence intervals for slope and intercept were 0.89-1.27 and 7.65-8.13, respectively. Our results suggest that wavelet analysis is effective as a real-time monitor and that it is possible to distinguish larger volumes of air emboli based on previous injections of small volumes of air. IMPLICATIONS: The real-time wavelet analysis of the heart sound detected by precordial Doppler ultrasound may be useful in estimating larger volumes of air emboli based on previous injections of small volumes of air in anesthetized dogs.

Animals↗

PubMed1997

Computerised infrared imaging system for studying thermal activation on the skull following somatic stimulation in small animals.

A computerised infrared imaging system has been developed to measure infrared radiation as a means of functionally mapping the cerebral cortex. In two species of small mammal, rat and gerbil, the authors localised the thermal changes at the skull overlying the somatic sensory cortex following somatic stimulation of the mystacial vibrissae. Though typically small in magnitude, a thermal response could be detected through the skull. To enhance detection sensitivity, a number of measures were taken to improve various aspects of data acquisition, stimulus delivery and control of experimental conditions. Regarding data analysis, a coordinate system based on skull landmarks was adopted to localise thermally-active regions for comparison across animals of the same species. To extract the region of weak temperature changes, a coarse-to-fine detection strategy was developed, which searched automatically for clusters of temporally- and spatially-correlated pixels above a data-driven threshold. Thus, the dynamic aspect of the thermal changes at any region of interest on the skull could be studied efficiently. The detection algorithm was tested against simulated responses in addition to empirical data obtained from animals. All of the above software was integrated in a user-friendly package.

Animals↗

PubMed1997

Effect of cage size on ultradian locomotor rhythms of laboratory mice.

The effect of cage size on spontaneous locomotor rhythms of laboratory mice was studied under simulated light-dark (12:12) cycles. On-line image analysis of bodily displacement yielded a locomotor signal over a period of 3 days. Continuous wavelet transform was applied to the signal, and ensemble averaging of eight mice revealed in the time-frequency plot bouts of increased motor activities. Notably, there were two bouts in the dark corresponding to ultradians of periods below 5 h: a first bout at the dark onset (at 0.6-1.0 cycle/h), and a second bout during the second half of the dark period (at 0.4-0.7 cycle/h). These increases of activity were more intense and distinct when the animals were kept inside the larger cage. Furthermore, the first bout disappeared when the animals were kept in the small cage for 3 days.

Activity Cycles↗

PubMed1997

Fast detection of venous air embolism in Doppler heart sound using the wavelet transform.

The introduction of air bubbles into the systemic circulation can result in significant morbidity. Real-time monitoring of continuous heart sound in patients detected by precordial Doppler ultrasound is, thus, vital for early detection of venous air embolism (VAE) during surgery. In this study, the multiscale feature of wavelet transforms (WT's) is exploited to examine the embolic Doppler heart sound (DHS) during intravenous air injections in dogs. As both humans and dogs share similar physiological conditions, our methods and results for dogs are expected to be applicable to humans. The WT of DHS at scale 2j (j = 1, 2) selectively magnified the power of embolic, but not the normal, heart sound. Statistically, the enhanced embolic power was found to be sensitive (P < 0.01 at 0.01 ml of injected air) and correlated significantly (P < 0.0005, r = 0.83) with the volume of injected air from 0.01 to 0.10 ml. A fast detection algorithm of O(N) complexity with unit complexity constant for VAE was developed (processing speed = 8 ms per heartbeat), which confirmed the feasibility of real-time processing for both humans and dogs.

Algorithms↗

PubMed1997

A time domain binaural model based on spatial feature extraction for the head-related transfer function.

A complex-valued head-related transfer function (HRTF) can be represented as a real-valued head-related impulse response (HRIR). The interaural time and level cues of HRIRs are extracted to derive the binaural model and also to normalize each measured HRIR. Using the Karhunen-Loeve expansion, normalized HRIRs are modeled as a weighted combination of a set of basis functions in a low-dimensional subspace. The basis functions and the space samples of the weights are obtained from the measured HRIR. A simple linear interpolation algorithm is employed to obtain the modeled binaural HRIRs. The modeled HRIRs are nearly identical to the measured HRIRs from an anesthetized live cat. Typical mean-square errors and cross-correlation coefficients between the 1816 measured and modeled HRIRs are 1% and 0.99, respectively. The real-valued operations and linear interpolating in the model are very effective for speeding up the model computation in real-time implementation. This approach has made it possible to simulate real free-field signals at the two eardrums of a cat via earphones and to study the neuronal responses to such a virtual acoustic space (VAR).

Acoustic Stimulation↗

PubMed1996

EMG spike trains of succinylcholine-induced fasciculations in myalgic patients.

Single spike activity from the surface electromyogram (EMG) of fasciculations induced by succinylcholine (Sch) were studied from limb muscles (biceps, triceps, anterior tibialis and gastrocnemius) in 100 female patients. About 2/3 of them (n = 72) also received nondepolarizing neuromuscular pretreatment (atracurium or vecuronium). We observed from 20% of EMG records in the myalgic (but not in the nonmyalgic) patients, sustained spike trains (mean duration 1.47 s) that resembled motor units firing at physiologically high rates (mean 21.7 spikes/s). The finding reflects Sch's distal actions at the muscle spindle. The implications for myalgia and the possible involvement of micro damage at the extrafusal muscles are discussed.

Action Potentials↗

PubMed1996

Visual evoked potential enhancement by an artificial neural network filter.

The application of an artificial neural network filter (ANNF) to estimate the visual evoked potential (VEP) is presented. VEP is the gross electrical response of the brain to visual stimuli. Due to the low SNR, it is difficult to extract response from individual stimulus trials. The ANNF we used estimates the deterministic component of the signal and removes the noise uncorrelated with the stimulus, even when the noise is colored. The ANNF is trained through back-error propagation with a data set consisting of a training signal and a target signal. The training signal is the raw VEP from a single trial having a SNR of about -5 dB, while the target signal has a higher SNR which is achieved by ensemble averaging 100 stimulus trials. Simulated signals were generated to test the performance of the ANNF. Results show that the ANNF could greatly enhance the SNR of the VEP to single visual stimulus. Thus the total number of ensembles is reduced. In clinical applications, the traditional ensemble averaging method requires a hundred ensembles to determine the VEP. When ANNF is used, about 20 ensembles are sufficient for the same purpose.

Adolescent↗

PubMed1996

Generation of three-dimensional medical thermograms.

To visualise non-invasively human organs in their true form and shape has intrigued mankind for centuries. Three-dimensional (3D) imaging is one recent development that has brought us closer to fulfilling the age-old quest of non-invasive visualisation so that diagnoses by doctors can be efficiently enhanced. Nowadays, 3D CT and MRI images have been very popular. Thermography is an important medical imaging technique that displays the temperature distribution on the surface of a human organ and it has been proved to be significant in offering a unique physiological reflection of pathology that may confirm or enhance the anatomic findings of other diagnostic imaging modalities. It is the only imaging modality that can evaluate pain whereas plain radiographs, CT and MRI, etc. can only depict structural anatomic abnormalities that may not always coincide with patients' clinical complaints. It is against this background that 3D thermograms have been developed. A set of comprehensive calibration procedures for the 3-camera system have been designed based on different models for the optical and infrared cameras. The accuracy of the results is high enough to produce 3D thermograms that can be used to correlate with the 3D images from other medical imaging modalities. One important achievement of the system is that the resultant 3D images are absolutely dimensioned and hence, it is particularly favourable for fully autonomous applications with robots. The system can also provide an overall picture of both the structural abnormalities and nervous responses of patients.

Algorithms↗

PubMed1995

Thermal images of somatic sensory cortex obtained through the skull of rat and gerbil.

Infrared images of the skull surface were obtained in urethane-anesthetized rats and gerbils before, during and after mechanical stimulation of the face and mystacial vibrissae on one side. Areas of increased temperature on the skull, localized mainly over the face area of the primary somatosensory cortex contralateral to the side of stimulation, appeared within 4-5 s after the onset of stimulation. Rarely, such temperature change was recorded bilaterally. Temperatures did not remain high on the intact skull in rats, but fell to baseline within minutes after stimulus onset regardless of stimulus duration. In rats in which the skull had been thinned and in gerbils with intact skull, temperatures remained elevated during the course of stimulation. We were unable to resolve the activation of individual vibrissae.

Animals↗

PubMed1995

Detection of brainstem auditory evoked potential by adaptive filtering.

A method of detecting brainstem auditory evoked potential (BAEP) using adaptive signal enhancement (ASE) is proposed and tested in humans and cats. The ASE in this system estimates the signal component of the primary input, which is correlated with the reference input to the adaptive filter. The reference input is carefully designed to make an optimal and rapid estimation of the signal corrupted with noise, such as ongoing EEG. With a good choice of reference input, it is possible to track the variability of BAEP efficiently and rapidly. Moreover, the number of repetitions required could be markedly reduced and the result of the system is superior to that of ensemble averaging (EA). To detect BAEP in cats, only 30 ensemble averages are needed to obtain a reasonable reference input to the adaptive filter, and, for humans, 350-750 ensemble averages are sufficient for a satisfactory result. Using the LMS adaptive algorithm, individual BAEP can be obtained in real-time.

Algorithms↗

PubMed1995

Thyroid diagnosis by thermogram sequence analysis.

A computerised thermal imaging system for thyroid diagnosis was developed by the authors and it was discovered that the rate of changes of temperature, rather than the absolute values, associated with a sequence of thermograms could help the medical doctors to identify clinical disorders. In order to further enhance the diagnostic capabilities and speed, a new method for medical thermogram analysis has been developed that compresses a sequence of thermograms into one thermogram while retaining the important information such as the geometrical patterns of the objects and the rate of temperature changes of each pixel within the images. As motion artifacts are unavoidable when a patient undergoes minutes of thermogram recording, direct comparison between images is deemed impossible. A high speed image matching algorithm has been developed to provide an absolute geometrical foundation for pixel-to-pixel comparison. The rate of change of temperature of a particular pixel along the sequence is represented by one single parameter after a process of temperature integration which can then be converted into a corresponding gray level for display. The resultant compressed thermogram can give a clear distinction between problem areas and normal ones. Although our emphasis is on thyroid diagnosis, it is anticipated that this new technique can be applicable to other areas of a human body.

Algorithms↗

PubMed1994

Visual evoked potential measurement by adaptive filtering.

The method of ensemble averaging (EA), commonly used to improve signal-to-noise ratio (SNR) in evoked potential measurements, loses potentially useful information regarding response variability across trials. Due to the usually low SNR, it is difficult to extract the response from individual trials. The present paper describes an adaptive signal enhancer (ASE) that is capable of tracking the variation of visual evoked potential (VEP) from trial to trial as well as improving SNR. This ASE requires two inputs: a primary input, which is the raw noise-corrupted response, and a reference input, which is designed for an optional performance of ASE. We used moving ensemble averaging (MEA) to form the dynamic reference input. Experimental results in humans show a satisfactory performance of the ASE in determining VEP to single stimulus and in tracking the temporal changes of the signal.

Algorithms↗

PubMed1994

An enhanced approach to adaptive processing of the brain stem auditory evoked potential.

The present paper describes an adaptive signal enhancer (ASE) method for improving signal-to-noise ratio (SNR) and also for tracking the variation of brain-stem auditory evoked potential (BAEP). The enhancer has two inputs: a primary input which is the original data to be processed, consisting of signal badly corrupted by noise, and a reference input. A method called dynamic averaging (DA) is introduced to obtain the reference input. The improved reference signal allows closer tracking of evoked potential in each subsequent trial. For BAEP measurement in human, the SNR is typically very low. It requires about 200 ensembles to generate the reference input acceptable for ASE, and tracking of the variation of BAEP can be obtained satisfactorily. Our results show that while ensemble averaging is still needed, the total number of ensembles is greatly reduced. The adaptive method thus reduces the time of measurement for BAEP compared with the conventional method of ensemble averaging.

Electricity↗