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# 2024 PATCH-IT Wearables |
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PATCH-IT Wearables offers a breakthrough in patient monitoring by using deep learning algorithms to detect adverse events, such as organ failure or sepsis, up to 5.5 hours before they occur. By analysing digital biomarkers from common wearable devices, the technology enables continuous, real-time monitoring in acute care and beyond. This proactive approach reduces the burden on healthcare staff, improves patient outcomes, and ensures timely interventions, even in resource-limited settings
Kanika Dheman received her PhD at ETH Zurich, Switzerland and is now a postdoctoral researcher at the institution. Her focus is on translating smart bio-medical devices, especially AI-enabled diagnostic algorithms in low-power wearables for patient monitoring and management, at home and in the hospital. She aims to automate the process of predicting and pre-empting organ failure and adverse events leading to patient deterioration. Her research is funded by many prestigious national funding programs, such as the Postdoctoral Excellence Program (PEP) at the Basel Research Center for Child Health (BRCCH), Bridge Proof of Concept and the ETH for Development (ETH4D) fund. more
Nanyang Technological University
Targeted antimicrobial treatment for resistant infections
Early detection and non-invasive correction of breech pregnancies
