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Kamal Shah leads smartwatch study to detect cardiac arrest
The study explores how machine learning can enhance wearable health technology to identify life-threatening cardiac events.
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Malvika Choudhary - Thu, 03, Apr 2025
- 16:42 EDT
- 58
Kamal Shah along with his colleague / bioe.uw.edu
University of Washington (UW) Bioengineering alumnus Kamal Shah led a groundbreaking study on using smartwatches to detect cardiac arrest.
The study, ‘Automated loss of pulse detection on a consumer smartwatch’, published in Nature, explores how machine learning can enhance wearable health technology to identify life-threatening cardiac events.
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The research team developed an algorithm that uses data from a smartwatch’s photoplethysmography (PPG) sensor—a technology that measures blood flow—to automatically detect sudden loss of pulse, a key indicator of cardiac arrest. Given that unwitnessed cardiac arrests are often fatal, a wearable device capable of recognizing the event and alerting emergency services could be life-saving.
To validate the system, researchers conducted controlled experiments simulating pulselessness by temporarily cutting off blood flow in the arm. The smartwatch PPG signals recorded during these tests closely resembled those seen in ventricular fibrillation (Vfib), a life-threatening heart rhythm disorder associated with cardiac arrest.
The algorithm was trained using data from these simulations and real-world conditions. In prospective studies, it achieved a sensitivity of approximately 67 percent while generating minimal false alarms—just one unintended emergency call per 21.67 user-years—indicating its potential viability for public use.
“We hope that our research, and the Loss of Pulse Detection feature that came from it, can help improve outcomes from unwitnessed loss of pulse events,” said Shah.
Currently a research scientist at Google specializing in health and safety feature R&D for consumer electronics, Shah continues to work on innovations in wearable health technology. His contributions mark a significant step toward leveraging smart devices for early detection of critical medical conditions, with the potential to improve survival rates through timely intervention.
Shah earned his Doctorate In Bioengineering from the University of Washington (2015–2020), where he worked on mobile phone-based diagnostic tests for infectious diseases. His research was supported by fellowships, including the National Science Foundation Graduate Research Fellowship (NSF GRFP) and the UW College of Engineering Dean’s Fellowship. He has published multiple peer-reviewed articles and presented at various conferences.
He holds a bachelor of science in bioengineering and global health technologies from Rice University (2011–2015), where he co-designed healthcare technologies for low-resource settings. He was recognized as the 2015 Herbert Allen Outstanding Senior, a 2013 Barry M. Goldwater Scholar, and a 2013–14 Arnold and Mabel Beckman Foundation Scholar.
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