A Time-of-Flight and Radar Dataset of a neonatal Thorax Simulator with synchronized Reference Sensor Signals for...

Area of Science:

• Biomedical Engineering
• Medical Device Development
• Neonatal Monitoring

Background:

• Acquiring respiratory data from neonates is challenging.
• Limited open-source datasets exist for neonatal respiratory monitoring research.

Purpose of the Study:

• To present an open-source Time-of-Flight (ToF) and radar dataset.
• To facilitate the development of respiratory rate detection algorithms for neonates.

Main Methods:

• Developed a neonatal thorax simulator to mimic respiration.
• Recorded ToF and radar data at various respiratory rates (5-80 BPM) and upstroke heights.
• Utilized a laser micrometer as the gold standard for validation.

Main Results:

• Collected a comprehensive dataset of neonatal thorax movements.
• Demonstrated the feasibility of using ToF and radar for respiratory monitoring.
• Established a benchmark for algorithm development.

Conclusions:

• The open-source dataset supports research in non-contact respiratory rate detection.
• Enables testing and validation of novel algorithms for neonatal monitoring.
• Addresses the need for accessible data in this critical field.