Biomedical subjects

L Tarassenko

Publications and source records attributed to L Tarassenko.

At least 19 recordsLinked to original sources

PubMed2006

Integrated monitoring and analysis for early warning of patient deterioration.

Recently there has been an upsurge of interest in strategies for detecting at-risk patients in order to trigger the timely intervention of a Medical Emergency Team (MET), also known as a Rapid Response Team (RRT). We review a real-time automated system, BioSign, which tracks patient status by combining information from vital signs monitored non-invasively on the general ward. BioSign fuses the vital signs in order to produce a single-parameter representation of patient status, the Patient Status Index. The data fusion method adopted in BioSign is a probabilistic model of normality in five dimensions, previously learnt from the vital sign data acquired from a representative sample of patients. BioSign alerts occur either when a single vital sign deviates by close to +/-3 standard deviations from its normal value or when two or more vital signs depart from normality, but by a smaller amount. In a trial with high-risk elective/emergency surgery or medical patients, BioSign alerts were generated, on average, every 8 hours; 95% of these were classified as 'True' by clinical experts. Retrospective analysis has also shown that the data fusion algorithm in BioSign is capable of detecting critical events in advance of single-channel alerts.

Critical Care↗

PubMed2006

Combined transfer function analysis and modelling of cerebral autoregulation.

The clinical importance of cerebral autoregulation has resulted in a significant body of literature that attempts both to model the underlying physiological processes and to estimate the mathematical relationships between clinically measurable variables, the most common of which are Arterial Blood Pressure and Cerebral Blood Flow Velocity. These approaches have, however, rarely been used together to interpret clinical data. A simple model of cerebral autoregulation is thus proposed here, based on a flow dependent feedback mechanism with gain and time constant that adjusts arterial compliance. Analysis of this model shows that it closely approximates a second order system for typical values of physiological parameters. The model parameters can be optimally estimated from available experimental data for the Impulse Response (IR), yielding physiologically reasonable values, although there is one free parameter that must be fixed. The effects of changes in feedback gain and time constant are found to be significant on the predicted IR and can thus be estimated robustly from experimental data. The effects of elevated baseline Intracranial Pressure (ICP) are found to be exactly equivalent to a reduced feedback gain, although the solution is much less sensitive to the former effect. A transfer function approach can be used to estimate autoregulation status clinically using a physiologically-based model, thus providing greater insight into the processes that govern cerebral autoregulation.

Algorithms↗

PubMed2006

A randomised controlled trial of the effect of continuous electronic physiological monitoring on the adverse event rate in high risk medical and surgical patients.

We conducted a randomised controlled trial of mandated five-channel physiological monitoring vs standard care, in acute medical and surgical wards in a single UK teaching hospital. In all, 402 high-risk medical and surgical patients were studied. The primary outcome was the proportion of patients experiencing one or more major adverse events, including urgent staff calls, changes to higher care levels, cardiac arrests or death, in 96 h following randomisation. Secondary outcomes were the proportion of patients requiring acute treatment changes, and the 30-day and hospital mortality. In the 96 h following randomisation, 113 (56%) patients in the monitored arm and 116 (58%) in the control arm (OR 0.94, 95% CI 0.63-1.40, p = 0.76) had a major event. An acute change in treatment was necessary in 107 (53%) monitored patients and 101 (50%) control patients (OR 0.55, 95% CI 0.87-1.29). Thirty-four (17%) monitored patients and 35 (17%) control patients died within 30 days. Thirteen patients in the control group received full five-channel monitoring at the request of the ward staff. We conclude that mandated electronic vital signs monitoring in high risk medical and surgical patients has no effect on adverse events or mortality.

Adult↗

PubMed2005

A systematic review of telemedicine interventions to support blood glucose self-monitoring in diabetes.

AIMS: To evaluate evidence for feasibility, acceptability and cost-effectiveness of diabetes telemedicine applications. METHODS: MEDLINE, EMBASE, PSYCHINFO, CINAHL, Cochrane, and INSPEC were searched using the terms diabetes and telemedicine for clinical studies using electronic transfer of blood glucose results in people with diabetes. The technology used, trial design and clinical outcome measures used were extracted for trials and prospective cohort studies. Randomized controlled trials with HbA(1c) as an outcome were pooled using standard meta-analytical methods. RESULTS: We identified 539 papers among which 32 papers described 10 prospective cohort studies, 12 parallel group randomized controlled trials (RCT), three crossover trials, and one non-parallel group trial. Only two studies described full details of randomization, blinding of outcomes and dropouts and withdrawals. Electronic transfer of glucose results appears feasible in a clinical setting. Only two of the RCTs included more than 100 patients, and only three extended to 1 year. Only one study was designed to show that telemedicine interventions might replace clinic interventions without deterioration in HbA(1c). Results pooled from the nine RCTs with reported data did not provide evidence that the interventions were effective in reducing HbA(1c) (-0.1%, 95% CI -0.4% to 0.04%). CONCLUSIONS: Telemedicine solutions for diabetes care are feasible and acceptable, but evidence for their effectiveness in improving HbA(1c) or reducing costs while maintaining HbA(1c) levels, or improving other aspects of diabetes management is not strong. Further research should seek to understand how telemedicine might enhance educational and self-management interventions and RCTs are required to examine cost-effectiveness.

Blood Glucose Self-Monitoring↗

PubMed2005

Mobile phone technology in the management of asthma.

Peak flow monitoring is widely recommended as part of a self-management plan for asthma. We conducted an observational study using electronic peak flow monitoring and mobile phone technology in a UK general practice population over a nine-month period. Patients between 12 and 55 years of age who required treatment with regular inhaled steroids and (as needed) bronchodilators were recruited from nine general practices. Patients were included if their asthma was considered stable (i.e. no exacerbation in the previous three months). No therapeutic intervention was proposed. The primary outcome measure was compliance. In all, 69% of the 46 participants who filled in the post-study questionnaire were 'satisfied' or 'very satisfied' by the study, citing the ease of use and the increased autonomy and understanding of asthma as the main advantages. In total, 74% indicated that the system had helped to improve their ability to manage their symptoms. The most positive features of the telemedicine system were described as follows: increased awareness and information about asthma, improved ability to monitor/manage the condition with the feedback screens on the mobile phone and ease of use.

Adolescent↗

PubMed2004

Segmenting cardiac-related data using sleep stages increases separation between normal subjects and apnoeic patients.

Inter-patient comparisons of cardiovascular metrics indicative of patient health have been shown to be successful in differentiating patients on a group rather than an individual level. This is in part due to the range of mental (as well as physical) activity-based variations for each patient and the difficulty assessing physical and mental activity during conscious states. In order to provide an objective scale for measuring central nervous system activity during sleep, the heart rate (RR) interval time series is divided into coarse sleep stage segments in which the LF/HF-ratio (the relative balance between low and high frequency power) is estimated for age and sex-matched populations of apnoeic and healthy subjects. Activity-based noise is therefore reduced and a more useful comparison of heart rate variability can be made. Additionally, the spectral estimation performances of the FFT and the Lomb-Scargle periodogram (LSP), a Fourier-based technique for unevenly sampled time series are compared. Separation of patients according to condition is shown to be more pronounced when using the LSP than the FFT. Furthermore, separation is found to be most marked in slow wave sleep.

Adult↗

PubMed2002

Linear and non-linear methods for automatic seizure detection in scalp electro-encephalogram recordings.

The electro-encephalogram is a time-varying signal that measures electrical activity in the brain. A conceptually intuitive non-linear technique, multi-dimensional probability evolution (MDPE), is introduced. It is based on the time evolution of the probability density function within a multi-dimensional state space. A synthetic recording is employed to illustrate why MDPE is capable of detecting changes in the underlying dynamics that are invisible to linear statistics. If a non-linear statistic cannot outperform a simple linear statistic such as variance, then there is no reason to advocate its use. Both variance and MDPE were able to detect the seizure in each of the ten scalp EEG recordings investigated. Although MDPE produced fewer false positives, there is no firm evidence to suggest that MDPE, or any other non-linear statistic considered, outperforms variance-based methods at identifying seizures.

Electroencephalography↗

PubMed2001

Tracking poles with an autoregressive model: a confidence index for the analysis of the intrapartum cardiotocogram.

Clinicians often rely upon the cardiotocogram, a display of the fetal heart rate and maternal uterine activity (UA) over time, as a means of monitoring fetal health during labour. Fetal health can be monitored adequately only when the signal quality of the cardiotocogram is good. We propose an automated assessment of UA signal quality in order to create a confidence index for subsequent analysis of the intrapartum cardiotocogram. We use an autoregressive (AR) model of the UA to estimate the power at the contraction frequency, with high power indicative of "good" UA signal quality. 5th, 10th, and 15th-order AR models are used to assess the signal quality of 12 intrapartum UA traces as "good/medium" or "poor". We compare our results to two experts' visual assessments of signal quality. The 10th-order model exhibits the highest percent agreement rate of 62%. It also exhibits the most balanced false positive and false negative rates, where "good" or "medium" signal quality is considered a positive and "poor" signal quality a negative. The 10th-order model can therefore be used as a confidence index to reduce the errors made in the identification of uterine contractions in the UA trace and in the subsequent analysis of the cardiotocogram as a whole.

Cardiotocography↗

PubMed1999

Second by second patterns in cortical electroencephalograph and systolic blood pressure during Cheyne-Stokes.

Little is known about how arousal develops during the ventilatory phase of Cheyne-Stokes breathing. This study employs neural network analysis of electroencephalograms (EEGs) to describe these changes and relate them to changes in systolic blood pressure, which is probably a subcortical marker of arousal. Six patients with Cheyne-Stokes respiration (apnoea/hypopnoea index 32-69 h(-1)) caused by stable chronic heart failure underwent polysomnography including arterial beat-to-beat systolic blood pressure determination. Periods of 15 sequential apnoeas during nonrapid eye movement sleep were identified for each subject. For each apnoea, the EEG was examined second-by-second using neural net analysis from 28 s before to 28 s after apnoea termination (first return of oronasal airflow), and this was compared with the systolic blood pressure pattern. During the apnoeic phase, sleep deepened progressively. Arousal started to develop at or just before apnoea termination and progresses through the breathing phase. The rise and fall in the systolic blood pressure closely followed the rise and fall in electroencephalographic sleep depth. In conclusion, during Cheyne-Stokes breathing, cortical electroencephalographic arousal begins at or just before the resumption of breathing. Cortical electroencephalographic sleep depth changes are closely mirrored by changes in arterial systolic blood pressure, suggesting that the state changes in the cortical and basal brain structures may be synchronous.

Arousal↗

PubMed1998

Sleep studies of adults with severe or profound mental retardation and epilepsy.

Sleep patterns of people with mental retardation have received little research attention. This is an important gap in knowledge because understanding the relation between sleep and wakefulness may be critical to care provision. Descriptive sleep information on 28 people with severe or profound mental retardation and epilepsy was presented here. Sleep EEG data, studied both conventionally and by means of a neural network-based sleep analysis system suggest atypical sleep stages with significant depletion of REM sleep and a predominance of "indiscriminate" non-REM sleep. Sleep diaries completed by caregivers reveal lengthy sleep period times, especially among those with profound mental retardation. Possible explanations for these results and their implications were discussed.

Adolescent↗

PubMed1997

Analysis of dynamic MR breast images using a model of contrast enhancement.

We describe a model of dynamic contrast enhancement in breast MRI designed to aid the radiologist in cases for which X-ray mammography is ineffective. The breasts are segmented from the image slices by a dynamic programming algorithm after morphological opening. A pharmacokinetic model has been derived to fit the rise in intensities after injection of a contrast agent, in a way that facilitates investigation of the effects of different models of bolus injection. The pharmacokinetic model is used in a modified Horn-Schunck algorithm to correct for motion effects during the seven minute acquisition period. The results show significant localization of tumours and enable discrimination of cancerous tissue. In particular, we illustrate the approach with an image that shows a carcinoma, whose appearance and localization are greatly improved by the registration algorithm.

Algorithms↗

PubMed1996

A review of parametric modelling techniques for EEG analysis.

This review provides an introduction to the use of parametric modelling techniques for time series analysis, and in particular the application of autoregressive modelling to the analysis of physiological signals such as the human electroencephalogram. The concept of signal stationarity is considered and, in the light of this, both adaptive models, and non-adaptive models employing fixed or adaptive segmentation, are discussed. For non-adaptive autoregressive models, the Yule-Walker equations are derived and the popular Levinson-Durbin and Burg algorithms are introduced. The interpretation of an autoregressive model as a recursive digital filter and its use in spectral estimation are considered, and the important issues of model stability and model complexity are discussed.

Biomedical Engineering↗

PubMed1996

A new approach to the analysis of the human sleep/wakefulness continuum.

The conventional approach to the analysis of human sleep uses a set of pre-defined rules to allocate each 20 or 30-s epoch to one of six main sleep stages. The application of these rules is performed either manually, by visual inspection of the electroencephalogram and related signals, or, more recently, by a software implementation of these rules on a computer. This article evaluates the limitations of rule-based sleep staging and then presents a new method of sleep analysis that makes no such use of pre-defined rules and stages, tracking instead the dynamic development of sleep on a continuous scale. The extraction of meaningful features from the electroencephalogram is first considered, and for this purpose a technique called autoregressive modelling was preferred to the more commonly-used methods of band-pass filtering or the fast Fourier transform. This is followed by a qualitative investigation into the dynamics of the electroencephalogram during sleep using a technique for data visualization known as a self-organizing feature map. The insights gained using this map led to the subsequent development of a new, quantitative method of sleep analysis that utilizes the pattern recognition capabilities of an artificial neural network. The outputs from this network provide a second-by-second quantification of the sleep/wakefulness continuum with a resolution that far exceeds that of rule-based sleep staging. This is demonstrated by the neural network's ability to pinpoint micro-arousals and highlight periods of severely disturbed sleep caused by certain sleep disorders. Both these phenomena are of considerable clinical value, but neither are scored satisfactorily using rule-based sleep staging.

Adult↗

PubMed1996

Effect of short term graded withdrawal of nasal continuous positive airway pressure on systemic blood pressure in patients with obstructive sleep apnoea.

It is debated whether obstructive sleep apnoea (OSA) is a significant independent risk factor for sustained hypertension or cardiovascular morbidity and mortality. In an attempt to avoid the problem of confounding variables we have investigated whether withdrawing nasal continuous positive airway pressure (NCPAP) from patients with OSA for different proportions of the night leads to a subsequent rise in their morning blood pressures. Six patients with treated OSA had their NCPAP automatically varied between 3 cms H2O and a therapeutic pressure over 5 successive nights. The proportion of therapeutic NCPAP given was kept constant over the 5 nights and blood pressure measured the morning after the 5th night. Each patient had 5 different levels of sleep disruption, from no therapeutic NCPAP at all, through to 100% NCPAP. The nocturnal consequences of these different proportions of NCPAP were quantified both by oximetry and by a new EEG analysis that provides an objective estimate of the periodicity (fluctuations in the EEG depth) of the time course seen in patients with OSA. Increasing degrees of nocturnal hypoxic dipping and EEG periodicity were positively correlated with the subsequent morning systolic and diastolic blood pressures (p < 0.02). About 20% of the variance in systolic and diastolic blood pressure could be accounted for by the amount of either hypoxic dipping or EEG periodicity. The results of this study suggest that acute changes in awake blood pressure can be caused by sleep apnoea. It agrees with other data suggesting that OSA can have an independent influence on morning BP, but that this effect may have worn off by the afternoon and evening. Some of the discrepancies between the numerous studies in this area may be due to the timing of blood pressure measurements.

Aged↗

PubMed1993

Pulse oximetry: theoretical and experimental models.

In the paper a pulse oximetry model is developed using an approach which combines both theoretical and empirical modelling. The optical properties of whole blood are measured as a function of cuvette depth by transmission spectrophotometry using red (660 nm) and infra-red (950 nm) light-emitting diodes as light sources. Twersky's theoretical model gives the best fit to the experimental data. A simple theoretical model which takes into account the nonlinear relationship between optical density and cuvette depth is then used to obtain an expression for the R:IR ratio, which relates the measurement of transmission at the two wavelengths. The R:IR ratio is found to be more or less independent of cuvette depth (SD = 0.14 at 100 per cent SaO2). To validate the predictions of the theoretical model, the results of a previous experiment in which the relationship between SaO2 and the R:IR ratio was recorded using a flexible cuvette are used. The experimental values are found to lie within one standard deviation from the theoretical curve relating SaO2 and the R:IR ratio. It is argued that a reasonably accurate model for pulse oximetry which is based on whole blood and not haemoglobin solutions has been developed.

Humans↗

PubMed1993

Reflectance pulse oximetry measurements from the retinal fundus.

Conventional transmission pulse oximetry is a noninvasive technique for the continuous monitoring of arterial oxygen saturation (SaO2) from peripheral vascular beds such as the finger tip or earlobe. In this paper we propose to exploit the unique transparency of the ocular media to make reflectance pulse oximetry measurements on the retinal fundus. This technique potentially offers significant advantages over conventional pulse oximetry, primarily the ability to monitor cerebral, as opposed to peripheral, oxygen saturation. We have developed an in vitro system to stimulate the retinal circulation and ocular optics. This system consists of a flexible cuvette located in a model eye and an extracorporeal blood circuit to stimulate arterial blood flow. The system was used to investigate the relationship between SaO2 and the R/IR ratio in reflectance pulse oximetry. To enable in vivo measurements to be made, we also modified a standard haptic contact lens to hold the pulse oximeter probe in front of the pupil. In a preliminary study, the lens was fitted to an awake volunteer and cardiac-synchronous signals were detected by the retinal pulse oximeter.

Contact Lenses↗

PubMed1993

On-chip learning with analogue VLSI neural networks.

Results from simulations of weight perturbation as an on-chip learning scheme for analogue VLSI neural networks are presented. The limitations of analogue hardware are modelled as realistically as possible. Thus synaptic weight precision is defined according to the smallest change in the weight setting voltage which gives a measurable change at the output of the corresponding neuron. Tests are carried out on a hard classification problem constructed from mobile robot navigation data. The simulations show that the degradation in classification performance on a 500-pattern test set caused by the introduction of realistic hardware constraints is acceptable: with 8-bit weights, updated probabilistically and with a simplified output error criterion, the error rate increases by no more than 7% when compared with weight perturbation implemented with full 32-bit precision.

Algorithms↗

PubMed1992

New method of automated sleep quantification.

Since its discovery some 50 years ago, the electro-encephalogram (EEG) has formed the basis for classification of sleep into several stages, either laboriously performed by visual examination of the EEG and related signals or, more recently, by automated techniques. Both visual scoring and most automated analyses are highly subjective and rely on application of a predefined set of rules. A method of analysing the EEG which requires no such application of rules and aims to give some indication of the dynamics of sleep in humans is proposed in the paper.

Adult↗