To meet the demands on a comfortable screening, or even diagnostic, equipment without interfering with the sleep, this study develops a level IV portable system, equipped with two tri-axial accelerometers (TAA) measuring the thoracic and abdominal respiratory efforts, and one oximeter measuring the oxygen saturation (SpO2), to identify obstructive sleep apnea (OSA), central sleep apnea (CSA), and hypopnea (HYP) events. The prototype integrates all the hardware and software for physiological information extraction. In addition, an automatic event detection algorithm is proposed to reduce the labor-intensive work on scoring the events. Based on 63 subjects, with 80% data for training and 20% for validation, the classification accuracy of the apnea hypopnea-index (AHI) is 84.13%. The results indicate that the proposed algorithm has great potential to classify the severity of patients in clinical examinations for both the screening and the homecare purposes.