Microchip Sensor Could Prevent Sudden Infant Death Syndrome

Researchers at Tyndall National Institute at University College Cork (UCC; Ireland) have developed a microchip-based sensor that can detect respiratory rate without having to make contact with the patient. Suitable for constantly monitoring babies to prevent sudden infant death syndrome (SIDS), the new sensor could also be used to monitor hospital patients and others at risk of obstructive sleep apnea and alert drivers when they begin to fall asleep at the wheel.

Based on ultra-wide-band pulse radar technology, the microchip can detect subcentimeter movements. When it sends very short radar pulses toward the chest, it can detect the echo reflected in proximity of the skin, enabling it to monitor chest movements. This is the first time that such an ultra-wide-band pulse radar has been integrated into a single silicon chip, according to Domenico Zito, leader of the research team focused on the design of single-chip transceivers for emerging wireless technologies at Tyndall National Institute and lecturer in microelectronic engineering at UCC. The device also operates in accordance with worldwide medical device standards.

"This microchip is the result of a dedicated and highly skilled research team at Tyndall National Institute which have been developing this microchip for a considerable time within a fruitful cooperation with the research group in bioengineering led by Professor Danilo De Rossi at the University of Pisa, Italy," Zito remarks. "We believe that this microchip has the potential to make a profound impact on monitoring respiratory diseases, as well as the number of deaths resulting from sudden infant death syndrome or accidents arising from driver fatigue. The microchip gives doctors access to extensive data recorded over long observation intervals, which will allow them to understand more about pathologies and their manifestations."

In addition to monitoring infants' respiratory movements, sleep apnea, and driver fatigue, the technology could be used for a variety of patient home-care applications in which data are sent in real-time to physicians and first-aid medical staff. It could also be used for fitness (fatigue) monitoring and personalized healthcare applications, enabling patients to live independently.