An apparatus and method for improving signal quality of a sensor signal, wherein an AI-based anomaly detector is configured to recognize an anomaly in a sensor output data stream. This approach can be used to predict and identify rare anomaly signals that are not handled properly by noise removal algorithms and help subsequent algorithms to get better decisions on the fly to better handle anomalous samples.