Accuracy of camera-based heart rate (HRcb) measurement is often impaired by artifacts, which leads to erroneous HRcb and reduced confidence in the measurement. To avoid erroneous HRcb, we investigated six signal quality indexes (SQIs) from the literature in terms of their effect size and combined them to a novel SQI-filter. All analyses were performed on the “Binghamton-Pitts-burgh-RPI Multimodal Spontaneous Emotion Database” (BP4D+) in three important color channels. Signal-to-noise ratio, average maximum cross correlation of consecutive segments, and relative difference of spectral peaks were the most powerful SQIs. The SQI-filter increased accuracies of all color channels. Largest improvements (up to 60 %) were achieved in the green channel resulting in 80 % accuracy. The overall highest accuracy of 84 % was reached in the hue channel. Motion-rich videos benefited most from the developed SQI-filter. The presented methodology helps to discard distorted signals. This enables more reliable HRcb data in further applications and increases confidence in the measurement.