Analogue preprocessor for the measurement by a digital computer of R-R intervals and R wave widths

Microprocessor detection of electrocardiogram R-waves

ECG monitoring devices for coronary care units require reliable R-wave dectors as a prerequisite for subsequent analysis. A simple algorithm has been developed for the detection of R-waves in an ECG signal with a microprocessor (Motorola MC6800). Detection criteria used were gradient and duration of a single upslope or downslope. Rejection of muscle noise and other artifiacts was achieved by setting system constants to optimum values which were determined by a short preliminary trial. This constant threshold system has been shown to cope with sudden changes of QRS complex amplitude better than some self adjusting systems. Assessment runs using patient tapes from a coronary care unit show total errors due to false positives and negatives are typically about 1% of the actual number of R-wave occurrences.

The present state of trend detection and prediction in patient monitoring

An investigation has been carried out into the suitability of the following techniques for trend detection and forecasting in patient monitoring: Cusum; Trigg's Tracking Signal; The Patient Condition Factor; The Patient Alarm Warning System; Box-Jenkins models and the Harrison-Stevens Bayesian approach. The latter holds considerable promise since it is flexible and can be implemented on a microprocessor. Consideration has also been given to the need for a better knowledge of the statistical properties of the variables to be monitored and the problems of combining trends detected in severable variables.

A comparison of two methods for the computer analysis of arterial blood pressure waveforms

Two different methods, one analogue and one digital, for the analysis of the arterial blood pressure waveform are described and compared. Little difference was found in the systolic and diastrlic pressures determined by the two methods.