| abstract |
A data processing environment processes a plurality of signals to detect a system state. The specific system can be, for example, a living human, where the signals are biological parameters. A processor operates the data points from two signals by defining respective classes of contiguous runs of a prescribed length of the data. The processor then assigns quantitative values to measure the regularity and stability of similar patterns between the first and second sets of classes of data points from the defined classes. These assigned quantitative values are aggregated to quantify the degree of asynchrony or conditional irregularity between the signals. |