Photoplethysmography (PPG) provides a noninvasive technique for recording human vital signs. However, PPG is normally collected via wearable devices that are prone to suffer from artifacts. Signal corruption by artifacts will negatively influence measurement accuracy. Regards to this, a signal quality assessment (SQA) system is essential for obtaining reliable measurement. Traditionally, the design flow of SQA mainly relies on the expert's subjective annotations. In this work, we present an ECG-aided signal quality assessment system for PPG. By utilizing the physiological connection between PPG and ECG (electrocardiography), proposed SQA has a higher ability to recognize low-quality signals. Finally, we verified our system on the application of heart rate estimation. Compared to the conventional methods, the proposed system has a better rejection rate of high-error signals (0.816 v.s. 0.776), hence, achieving a lower mean absolute error in the estimated heart rate (1.699 bpm v.s. 1.901 bpm).