Wavelet Medical has received an award from the Advanced Research Projects Agency for Health to support validation of its fetal brain monitoring technology.
The award is worth up to US$2.14 million over 12 months and begins in June 2026. It will support further development and validation of Wavelet’s non-invasive, AI-powered fetal electroencephalography monitoring platform.
This is relevant as fetal monitoring during delivery still relies heavily on fetal heart rate monitoring, which does not directly measure neurological function. According to Wavelet, fetal heart rate monitoring can be indeterminate in up to 85 per cent of births, creating uncertainty for clinicians during labour and delivery.
The clinical consequences can be significant. Missed cases of hypoxia may contribute to lifelong disability, while false positives can lead to unnecessary caesarean sections. Wavelet noted that more than 35,000 infants in the United States suffer brain injuries at birth each year, while approximately one-third of U.S. births are delivered by caesarean section.
Wavelet is developing what it describes as the first non-invasive, AI-powered fetal EEG monitoring platform. The technology is designed to detect fetal brain distress in real time and help prevent avoidable brain injury at birth.
The platform captures fetal brain signals through the mother’s abdomen, without invasive scalp electrodes or added risk to the mother or baby. It then uses proprietary AI algorithms to reconstruct and analyse auditory-evoked brain responses that may indicate neurological distress.
This differentiates the system from conventional fetal heart rate monitoring by targeting the organ directly affected by hypoxic injury: the fetal brain. If validated, the technology could provide clinicians with more specific information during labour and help guide decisions on whether intervention is needed.
The system is currently being tested at three clinical sites and is preparing for expanded trials. The ARPA-H award provides non-dilutive support for validation, which is important for early-stage medical device companies working on technologies that require clinical evidence before regulatory and commercial adoption.
The development sits within a larger need to improve obstetric decision-making. Labour and delivery teams must often act quickly with incomplete information. A monitoring tool that better distinguishes true neurological distress from uncertain heart rate patterns could support more appropriate intervention and reduce both under-treatment and over-treatment.
