Physiologic Monitoring

This pilot study aims to evaluate the feasibility and safety of continuous bowel sound monitoring in healthy term newborn infants using a novel wireless acoustic monitoring system. Participants will undergo a single 4-hour recording during routine postnatal care while bowel sounds are continuously recorded using wearable abdominal sensors. Feasibility will be assessed by participant recruitment and study completion, as well as the acquisition of high-quality, analyzable acoustic data. Bowel sounds will be characterized by assessing the temporal and spectral features of bowel sounds during the early neonatal period and exploring their relationship with routine caregiving activities and feeding.

This prospective observational study aims to evaluate the accuracy, safety, and feasibility of the ANNE® Chest wireless wearable sensor for continuous monitoring of heart rate, respiratory rate, oxygen saturation, and skin temperature in hospitalized neonates, infants, and children (0 days to 12 years of age) in the neonatal and pediatric intensive care units (NICU and PICU). Measurements obtained from the wireless device will be compared with standard-of-care bedside monitoring and capnography. The study will also assess skin tolerability, signal reliability, and caregiver and healthcare provider perceptions of the device.

This prospective observational study aims to evaluate the accuracy, safety, and feasibility of the Wireless MicroPremVitals Button Sensor System for continuous monitoring of electrocardiography (ECG), heart rate, respiratory rate, oxygen saturation, and skin temperature in newborn infants in the delivery room. Measurements obtained from the wireless sensor system will be compared with standard-of-care monitoring. The study will also assess skin tolerability, signal quality, and parent and healthcare provider perceptions of the device.

This study aims to develop a millimeter wave radar technology-based patient monitoring system that allows for the monitoring of physiological and movement-based data in healthcare settings without requiring physical contact with individuals. The study will involve the creation of hardware and software components for processing, analyzing, and converting signals obtained through radar sensors into clinically meaningful data.