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Direct respiratory measurements, as key biomarkers, are missing in traditional wrist- or finger-worn wearables, which thus limit their precision in detection of sleep stages and sleep disorders. By contrast, this work introduces a simple, multimodal, skin-integrated, energy-efficient mechanoacoustic sensor capable of synchronized cardiac and respiratory measurements. The mechanical design enhances sensitivity and durability, enabling continuous, wireless monitoring of essential vital signs (respiration rate, heart rate and corresponding variability, temperature) and various physical activities. Systematic physiology-based analytics involving explainable machine learning allows both precise sleep characterization and transparent tracking of each factor\u2019s contribution, demonstrating the dominance of respiration, as validated through a diverse range of human subjects, both healthy and with sleep disorders. 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