Abstract: 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.

Abstract: Data from a plurality of sensors representing a patient's condition, including measurement signals and also secondary parameters derived from the measurement signals, are displayed in a simple way by calculating a novelty index constituting a one-dimensional visualization space. The novelty index is based on the distance of the current data point in a multi-dimensional measurement space, whose coordinates are defined by the values of the measurement signals and secondary parameters, from a predefined normal point. This may be achieved by using a suitably trained artificial neural network to sum the distance between the current data point in the measurement space and a plurality of prototype points representing normality.

Abstract: A system for acquiring, and displaying, data such as physiological data, from a plurality of data connection devices, each of which monitor one or more different parameters and output data at different sampling frequencies based on their own system clocks. The system receives the data signals at different sampling frequencies and associates each sample of each signal with a time stamp derived from a single master clock. Low rate and high rate data are treated differently. Low rate data is associated with the current value of the master clock, where as high rate data is time stamped by giving the first sample a time stamp equal to the current value of the current master clock, subsequent samples being given an estimated time stamp based on the expected interval between samples derived from the sampling frequency of the data collection device, and the timescale given to the first example.

Abstract: Data from a plurality of sensors representing a patient's condition, including the measurement signals and also secondary parameters derived from the measurement signals, are displayed in a simple way by mapping them from the multi-dimensional measurement space to a two-dimensional visualisation space. This can be achieved using a mapping which preserves the topography of the data points, for instance by ensuring that the inter-point distances in the visualisation space match as closely as possible the corresponding inter-point distances in the measurement space. Such a mapping, for instance Sammon's mapping is achieved by a suitably trained artificial neural network. The parameters are normalised before the mapping process and the normalisation and mapping are such that mapped points from a patient whose condition is normal appear in the centre of the visualisation space, whereas points from a patient whose condition is abnormal appear at the edge of the visualisation space.

Abstract: A method for combining physiological 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 model may be a Kalman filter. The measured values are compared with the predicted values and the differences 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.

Abstract: A system for acquiring, and displaying, data such as physiological data, from a plurality of data connection devices, each of which monitor one or more different parameters and output data at different sampling frequencies based on their own system clocks. The system receives the data signals at different sampling frequencies and associates each sample of each signal with a time stamp derived from a single master clock. Low rate and high rate data are treated differently. Low rate data is associated with the current value of the master clock, where as high rate data is time stamped by giving the first sample a time stamp equal to the current value of the current master clock, subsequent samples being given an estimated time stamp based on the expected interval between samples derived from the sampling frequency of the data collection device, and the timescale given to the first example.