Sleep apnea disorder is one of the most widespread respiratory syndromes, interrupting breathing by preventing air from entering the lungs. This paper documents the design and implementation of a cost-effective and easy-to-conduct screening method for detecting and predicting sleep apnea events using a small number of sensors and a small, lightweight wearable device. The proposed sleep apnea system comprises sensors for heart rate, SpO2, and chest movement, an Arduino Uno microcontroller and a Bluetooth low-energy module. Sensory data were collected while the test subject was sleeping and compared with the benchmark home sleep apnea test device. Statistical analyses confirmed the performance of this study’s system, with experimental results closely conforming to the Benchmark; the proposed system’s accuracy was 99.94% for heart rate and SpO2 measurements, according to a Bland-Altman test requiring at least 95% concordance.
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