Researchers at Worcester Polytechnic Institute (WPI; MA, USA) developed the app, which analyzes video clips recorded while the patient’s fingertip is pressed against the lens of the camera. Like a standard clinical pulse oximeter, it then captures small changes in light reflected by the pulsing blood in the capillaries, and translates these changes to the actual vital signs by using some of the same algorithms employed in professional devices.

To test for accuracy, volunteers at WPI donned standard clinical monitoring devices measuring respiration, pulse rate, heart rhythm, and SpO2 content. Simultaneously, they pressed a finger onto the camera of a Motorola Droid phone. While all devices were recording, the volunteers went through a series of breathing exercises while their vital signs were captured. Subsequent analysis of the data showed that the smart phone monitor was as accurate as the traditional devices. Furthermore, since the new technology can measure heart rhythm, the researchers believe the smart-phone app could also be used to detect atrial fibrillation (AF), which is the most common form of cardiac arrhythmia. The study describing the technology was published on July 29, 2011, in the journal IEEE Transactions on Biomedical Engineering.

“Imagine a technician in a nursing home who is able to go into a patient's room, place the patient's finger on the camera of a tablet, and in that one step capture all their vital signs,” said lead author Prof. Ki Chon, PhD, head of biomedical engineering at WPI. “We believe there are many applications for this technology, to help patients monitor themselves, and to help clinicians care for their patients.”

“This gives a patient the ability to carry an accurate physiological monitor anywhere, without additional hardware beyond what’s already included in many consumer mobile phones,” added Professor Chon. “One of the advantages of mobile phone monitoring is that it allows patients to make baseline measurements at any time, building a database that could allow for improved detection of disease states.”

Related Links:
Worcester Polytechnic Institute