Sleep-disordered breathing and Cheyne–Stokes breathing are often not diagnosed, especially in cardiovascular patients. An automated system based on photoplethysmographic signals might provide a convenient screening and diagnostic solution for patient evaluation at home or in an ambulatory setting. We compared event detection and classification obtained by full polysomnography (the ‘gold standard’) and by an automated new algorithm system in 74 subjects. Each subject underwent overnight polysomnography, 60 in a hospital cardiology department and 14 while being tested for suspected sleep-disordered breathing in a sleep laboratory. The sleep-disordered breathing and Cheyne–Stokes breathing parameters measured by a new automated algorithm system correlated very well with the corresponding results obtained by full polysomnography. The sensitivity of the Cheyne–Stokes breathing detected from the system compared to full polysomnography was 92% [95% confidence interval (CI): 78.6–98.3%] and specificity 94% (95% CI: 81.3–99.3%). Comparison of the Apnea Hyponea Index with a cutoff level of 15 shows a sensitivity of 98% (95% CI: 87.1–99.6%) and specificity of 96% (95% CI: 79.8–99.3%). The detection of respiratory events showed agreement of approximately 80%. Regression and Bland–Altman plots revealed good agreement between the two methods. Relative to gold-standard polysomnography, the simply used automated system in this study yielded an acceptable analysis of sleep- and/or cardiac-related breathing disorders. Accordingly, and given the convenience and simplicity of its application, this system can be considered as a suitable platform for home and ambulatory screening and diagnosis of sleep-disordered breathing in patients with cardiovascular disease.