Isis Innovation Limited

Oxford Biosignals Limited

Oxford University Innovation Limited

Obs Medical Limited

Rolls-royce Corporation

Oxford Medical Limited

Lionel Tarassenko

Paul Robert Hayton

David Andrew Clifton

Dennis M King

Paul Anuzis

Neil William Townsend

Stephen Peter King

Alessandro Guazzi

Paul Michael Hayton

Mauricio Christian Villarroel Montoya

Alan Patterson

Iain Guy Strachan

Stephen John Roberts

Robert William Slater

Syed Ahmar Shah

Michael Richard Dadswell

Mark Jeremy Laister

Drew Birrenkott

James Pardey

Simukai Utete

Steve P King

Catherine Laura Mason

Ken Astley

James David Price

Nicholas Hughes

Alistair Hann

David J Ault

Steven P King

Jonathan Daly

Mauricio Villarroel Montoya

Marco Pimentel

Delaram Jarchi

Susannah Fleming

Methods, devices and systems for determining the frequency of a periodic physiological process of a subject, particularly respiration rate or heart rate, are disclosed. In one arrangement plural time windows of physiological data are obtained. Reference features corresponding to modulation modes are identified. Modulations of the reference features are extracted. Quality parameters are obtained by processing the extracted modulations. The quality parameters represent how strongly the extracted modulation exhibits a waveform of the periodic physiological process. The extracted modulations are processed to calculate the frequency of the periodic physiological process of the subject. The frequency of the periodic physiological process may be calculated using only a subset of the extracted modulations, the subset being selected using the quality parameter, or using a combination of the extracted modulations wherein each extracted modulation has a weighting defined by the quality parameter of the extracted modulation.

Method of determining the frequency of a periodic physiological process of a subject, and a device and system for determining the frequency of a periodic physiological process of a subject

A method and apparatus for estimating the frequency of a dominant periodic component in an input signal by modelling the input signal using auto-regressive models of several different orders to generate candidate frequencies for the periodic component, generating synthetic sinusoidal signals of each of the candidate frequencies, and calculating the cross-correlation of the synthetic signals with the original signal. The frequency of whichever of the synthetic signals has the highest cross-correlation with the original signal is taken as the estimate of the frequency for the dominant periodic component of the input signal. The method may be applied to any noisy signal which has a suspected periodic component, for example physiological signals such as photoplethysmogram signals, and in the estimation of heart rate and breathing rate from such physiological signals.

Signal processing method and apparatus

A method of monitoring changes in oxygen saturation of a subject by analysing a three colour channel video image of the exposed skin of the subject. Within each colour channel a normalised signal obtained by dividing the intensity signal by its mean value, and the normalised signals are averaged across plural regions of interest within the exposed skin area image of the subject. Regions of interest are selected on the basis of the signal-to-noise ratios for the heart rate and breathing rate components. A single representative waveform for each colour channel is obtained by signal averaging and the ratio of the amplitudes of the representative waveforms from two different colour channels, e.g. blue and red, is taken. The changes in the ratio of amplitudes is output as a measure of changes in blood oxygen saturation.

Method and apparatus for vital signs measurement

Haemodynamic parameters such as the amplitude and phase of a pulse wave passing through a region of interest can be obtained from a video image of the exposed skin of a patient by processing of the reflectance photoplethysmographic signal using signal averaging. The region of interest is defined and a reflectance photoplethysmographic signal obtained by finding the mean pixel intensity across the region of interest for each video frame. Signal averaging is performed on the resulting pulsatile waveform by detecting peaks in the waveform, selecting those parts of the waveform which lie within a window centered on the peaks, and summing the selected parts of the waveform to find an average pulse waveform. The region of interest is then divided into sub-regions and an average pulse waveform for the video sequence is found for each of the sub-regions in the same way. The amplitudes of the average pulse waveforms for the sub-regions can be measured and displayed, for example as a spatial map across the region of interest. The phase of the average pulse waveforms in the sub-regions in the sub-regions relative to the average pulse waveform for the whole region of interest can be measured and displayed, again as a spatial map. The phase and amplitude maps give an indication of the quality of perfusion across the region of interest.

Method and apparatus for measuring and displaying a haemodynamic parameter

Vibration amplitudes are recorded as a function of rotation speed and of frequency and the data is analyzed to estimate a noise floor amplitude threshold for each of a plurality of different speed and frequency sub-ranges. On the basis of training data known to be normal speed-frequency areas which contain significant spectral content in normal operation are deemed 'known significant spectral content', so that during monitoring of new data points which correspond to significant vibration energy at speeds and frequencies different from the known significant spectral content can be deemed 'novel significant spectral content' and form the basis for an alert. The estimation of the noise floor is based on a probabilistic analysis of the data in each speed-frequency area and from this analysis an extreme value distribution expressing the probability that any given sample is noise is obtained.

Method and apparatus for monitoring and analyzing vibrations in rotary machines

An image of a human, animal or machine subject, is analysed to detect regions which include strong periodic intensity variations, such as a photoplethysmogram (PPG) signal in a human or animal, or some periodic vibration in a machine. The image is divided into plural regions of fixed order is fitted to a representative intensity signal for that region. The poles of the fitted autoregressive model are thresholded by magnitude to select only the pole or poles with a magnitude greater than the threshold. The pole magnitude therefore acts as a signal quality index. The dominant pole is representative of the strongest periodic information and the frequency of that spectral component can be derived from the phase angle of the pole. The image may be redisplayed with image attributes, e.g. color-coding, according to the pole magnitude in each region of interest and/or the dominant pole phase angle in each region of interest. In the case of a PPG image signal this can give maps of heart rate and breathing rate.

Method and system for signal analysis

A method of remote monitoring of vital signs by detecting the PPG signal in an image of a subject taken by a video camera such as a webcam. The PPG signal is identified by auto-regressive analysis of ambient light reflected from a region of interest on the subject's skin. Frequency components of the ambient light and aliasing artefacts resulting from the frame rate of the video camera are cancelled by auto-regressive analysis of ambient light reflected from a region of interest not on the subject's skin, e.g. in the background. This reveals the spectral content of the ambient light allowing identification of the subject's PPG signal. Heart rate, oxygen saturation and breathing rate are obtained from the PPG signal. The values can be combined into a wellness index based on a statistical analysis of the values.

Remote monitoring of vital signs

A method of obtaining a consistent evaluation of the state of the system which has been monitored by measurement of multiple parameters of that system. The multiple parameters are used to calculate a single dimensional value based on the distance between the current state and normal states of the system using a Parzen Windows probability function. Consistent single dimensional values regardless of the dimensionality of the original data set can be obtained by finding a relationship between the single dimensional value and the probability of status of the system. Different relationships are obtained for different dimensionalities of data sets. Sensor malfunction can also be detected by testing the probability of the state implied by measuring all of the available parameters against the probability of the state implied by ignoring different individual ones of the parameters. A significant disparity in the two probabilities indicate possible sensor malfunction.

Novelty detection with missing parameters

A method of analysing biomedical signals, for example electrocardiograms, by using a Hidden Markov Model for subsections of the signal. In the case of an electrocardiogram two Hidden Markov Models are used to detect respectively the start and end of the QT interval. The relationship between the QT interval and heart rate can be computed and a contemporaneous value for the slope of this relationship can be obtained by calculating the QT/RR relationship for all of the beats in a sliding time window based on the current beat. Portions of electrocardiograms taken on different days can efficiently and accurately be compared by selecting time windows of the ECGs at the same time of day, and looking for similar beats in those time windows.

Method of biomedical signal analysis including improved automatic segmentation

A way of quantifying the shape of an ECG waveform is disclosed by detecting the JT segment using two Hidden Markov Models and calculating the analytic signal of the JT segment. Parameters calculated from the analytic signal are used as shape descriptors for the JT segment. The shape descriptors may be displayed in a dimensionality-reduced mapping. Templates representing characteristic shapes can be produced by finding cluster centers in the shape descriptor space, and the novelty of new waveforms can be quantified by comparing the position in shape descriptor space of new shape descriptors to a predefined normal training set or to previously encountered waveforms. Novel shape descriptors can be used to retrieve the corresponding waveforms, and templates of such novel shapes can be created by averaging such waveforms, using dynamic time warping to allow for variations in heart rate. The templates can be manually segmented and the manual segmentation propagated back into other waveforms having similar shape descriptors.

Biomedical signal morphology analysis method

Improvement in the reliability of segmentation of a signal, such as an ECG signal, is achieved through the use of duration constraints. The signal is analysed using a hidden Markov model. The duration constraints specify minimum allowed durations for specific states of the model. The duration constraints can be incorporated either in the model itself or in a Viterbi algorithm used to compute the most probable state sequence given a conventional model. The derivation of a confidence measure from the model can be used to assess the quality and robustness of the segmentation and to identify any signals for which the segmentation is unreliable, for example due to the presence of noise or abnormality in the signal.

Signal analysis method

A method and apparatus for detecting an abnormality in e.g. in operating characteristics or function of a machine, apparatus or system, the method including providing a data sample set comprising n values of a measured physical parameter associated with the apparatus or system generated by repeating a measurement of the physical parameter n times. An extremal measured parameter value is selected from amongst the data sample set, determining a probability of observing the selected parameter value (e.g. of observing a value not exceeding the selected parameter value) by applying the selected parameter value to an extreme value probability distribution function having a location parameter and a scale parameter. The value of the location parameter and the value of the scale parameter are each constructed using an integer value m (e.g. notionally representing the size of a sub-sample data set comprising m of said measured parameter values) in which m is less than n (i.e. m&#x3c;n). A conditional indication is given that the selected parameter value is abnormal according to the value of the probability.

Novelty detection

A method for combining measurements from two or more independent measurement channels, particularly physiological measurements such as heart rate. Independent measurements of heart rate, for instance by ECG and pulse oximetry, can be combined to derive an improved measurement eliminating artefacts on one channel. A model of the process generating the physiological parameter, e.g., the heart rate, is constructed and is run independently for each channel to generate predictions of the parameter. The measured values are compared with the predicted values and the differences are used as an indication of the confidence in the measurement. The measurements from the two channels are ombined using weights calculated from the respective differences.

Combining measurements from different sensors

A method of analysing tachometer and vibration response data from an apparatus having one or more rotary components is provided. The method comprises the steps of: providing vibration response data and corresponding tachometer data from the apparatus for a period over which a rotary component of the apparatus varies in rotational speed, the tachometer data being for that component; repeatedly performing at intervals throughout the period the sub-steps of: determining a forcing frequency of the component from the tachometer data and a corresponding vibration response frequency of the apparatus from the vibration response data, comparing the forcing and vibration response frequencies to determine the relative phase difference between the frequencies, and determining the corresponding amplitude of the vibration response from the vibration response data; and plotting the relative phase differences and vibration amplitudes on a polar diagram. The plot trajectory is characteristic of the behavior of the apparatus over the period.

Method and system for analysing tachometer and vibration data from an apparatus having one or more rotary components

A method for combining breathing rate measurements from two or more independent measurement channels. Independent measurements of breathing rate, for instance by impedance pneumography and photoplethysmography, can be combined to derive an improved measurement eliminating artefacts on one channel. A model of the process generating the breathing rate, is constructed and is run independently for each channel to generate predictions of the breathing rate. The model may be a Kalman filter. The measured values are compared with the predicted values and the difference is used as an indication of the confidence in the measurement, the higher the difference the lower the confidence. The measurements from the two channels are combined using weights calculated from the respected differences.

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Oxford, United Kingdom

Lionel Tarassenko