SYSTEMS AND METHOD FOR IDENTIFYING NON-CORRUPTED SIGNAL SEGMENTS FOR USE IN DETERMINING PHYSIOLOGICAL PARAMETERS

摘要

According to embodiments, non-corrupted signal segments are detected by a data modeling processor implementing an artificial neural network. The neural network may be trained to detect artifact in the signal (e.g., a PPG signal or some wavelet representation of a PPG signal) and gate valid signal segments for use in determining physiological parameters, such as, for example, pulse rate, oxygen saturation, pulse rate, respiration rate, and respiratory effort. When an artifact is detected, previously received known-good signal segments may be buffered and replace the signal segment or segments containing artifact. A regression analysis may also be performed in order to extrapolate new data from previously received known-good signal segments. In this way, more accurate and reliable physiological parameters may be determined.