We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today!
Researchers from MIT’s Computer Science AI Lab (CSAIL) are developing methods for using wireless radio signals to detect sensors inside the human body. The ReMix system could be used to find ingestible microchip implants, a technique its creators hope can someday assist in medical imaging, delivering drugs to specific parts of the body, or tracking the movement of tumors.
A study detailing the team‘s findings is being presented this week at the SIGCOMM international conference in Budapest, Hungary.
Initial tests were conducted by placing a microchip inside a fake tumor and then placing that fake tumor into varying forms of animal tissue, like a whole chicken, pork belly, or containers of chicken fat or phantom human tissue.
The system was created in collaboration with researchers from Massachusetts General Hospital. Professor Dina Katabi, who led the study, has previously used wireless signals to track human movement or measure a person’s breathing or heart rate through walls.
Today ReMix is able to detect the location of a microchip with 1.4 centimeter accuracy, though Katabi believes the AI needs to be accurate within millimeters to be considered in a clinical setting.
Should ReMix gain accuracy, it could also assist in proton therapy for cancer treatment. Since the treatment method requires using large amounts of radiation, pinpointing the exact location of invasive cancer cells is essential.
CSAIL’s work is the latest development in a series of efforts exploring how potential applications of radio waves with implantable devices could help people. In June, researchers at MIT announced the creation of the In Vivo Networking (IVN) system, a wireless system to power devices implanted in the human body.
Also in June, Caltech researchers debuted a sensor that rests in a person’s eye for years at a time to transit data about pressure buildup, which is an indication a person may have glaucoma, a leading cause of blindness.
In other recent examples of researchers advancing health care tech to pass clinical thresholds and gain wide availability, last week Google’s DeepMind Health — together with ophthalmologists and researchers from Moorfields Eye Hospital and University College London — published a paper claiming its AI can recommend treatment for more than 50 eye diseases at a rate of 94 percent accuracy.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Learn more about membership.