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Updated: Jan 9, 2026

Multi-Modal Home Sleep Monitoring in Older Adults
Published on: January 26, 2019
Respiration Rate Monitoring During Sleep using an Ambient PIR Sensor Array
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Ambient sensor-based medical systems are increasingly being adopted in both clinical and consumer settings for non-invasive monitoring. This study utilizes a passive infrared (PIR) sensor array in conjunction with advanced machine learning techniques to estimate respiration rates during sleep. A new algorithm is introduced to classify periodic and non-periodic body movements captured by the PIR sensor array, enabling the identification of activity and sleep segments. To enhance data fusion and reduce noise, a Kalman filter-based algorithm is employed. Respiration rates are estimated during sleep based on subtle, periodic chest movements, achieving an accuracy of 96.8% when compared to a medical-grade chest belt and airflow sensor. These results highlight the potential of PIR sensor arrays for non-invasive sleep monitoring.
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