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A new understanding about the role and importance of sleep in health combined with rapidly aging demographics presents opportunities for research and development of new approaches in sleep monitoring. As well, challenges with the current sleep-monitoring solution can be addressed by studying the suitability of new monitoring technologies. This paper presents a small-scale validation of the unobtrusive pressure sensor array compared with traditional polysomnography (PSG), for use as a central apnea (CA) screening tool. Algorithms developed for the pressure sensor array provided a very good detection of the CAs as compared to the gold-standard data for the six patients studied whose body-mass index was appropriate for the sensor. For the retained patients, the algorithm classified CA events with an average sensitivity of 87.6%, specificity of 99.9%, and Cohen's kappa value of 0.875. This work evaluates the ability of an algorithm applied to the unobtrusive pressure sensor array to detect CAs. The sensor array was compared to three other signals: 1) expert PSG interpreters; 2) inductance plethysmography (IP) bands alone; and 3) IP bands combined with an airflow or oxygen-saturation sensor. The impact of unobtrusive CA detection on an older adult's health could be in the areas of broadening of the access to sleep monitoring, longitudinal monitoring of the disease progression, and possibly providing information on the interaction between CA and other disease processes.