Another focus is the interpretation of sensor data rather than the measurement itself. Emerging multisensor platforms combine glucose readings with additional physiological parameters such as body temperature, heart activity, and physical activity to distinguish clinically relevant events from measurement artifacts.
One example is the detection of nocturnal compression related false low glucose events, a common limitation of conventional CGM systems. By providing physiological context instead of glucose values alone, this approach could help reduce false alarms, improve confidence in sensor data and may provide automated insulin delivery systems with more contextual information for dosing decisions.