; Wireless Monitoring of Heart Rate and Respiration Using RADAR

Venture Beat recently named the “Quantified Self” movement as a top trend for 2012. That publication defined the movement as “self-knowledge through numbers” and cited a number of gadgets that enable their users to quantify everyday activities such as workouts, sleep, heart rate, and galvanic skin response.

Hugo Campos is a proponent of this movement: He uses aFitBit device to keep track of his daily activity level, a Withings blood pressure monitor, a WiFi scale, and a Zeo sleep monitor. He cannot, however, access the data in his implantable cardiac defibrillator (ICD) because such data is off limit to patients. The data from his ICD can, however, be accessed by his physician and the device’s manufacturer.

In his quest to learn about his condition and ICDs, Campos attends cardiology conferences, takes classes on how to program ICDs, and “does everything [he] can to raise [his] own level of health literacy,” as he explained in a recent TEDx talk. He firmly supports the e-patient movement, in which “networked patients are shifting from being just mere passengers to becoming responsible drivers of their care.”

Campos explains in the talk that he wants “to paint a broader picture in high resolution of what [his] health looks like.” But Campos, who is at risk for sudden cardiac arrest, gets no data from his $30,000 ICD—which includes information on heart rhythm, variations in chest impedance, and battery life.

Researchers at TNO, the Dutch Institute for Applied Science, have developed a vital signs monitor for measuring body motion, heart rate and respiration wirelessly at a distance of up to 10 meters. The system was presented at a Quantified Self meetup in Amsterdam.  It uses RADAR technology and allows continuous monitoring of motion, heart rate and respiration without the need for attaching sensors to the body. Radar pulses are emitted and reflected from the person (or cat) under observation. Based on the detection time and frequency of the reflected pulses, information can be derived about the movement of the body with a spatial resolution of  up to 1mm. According to the presentation it may also be possible to estimate sleep cycles based on the measured parameters.  The system is currently being trialled by TNO and further development is still required, however the team hopes to bring the system to market within the next 6-12 months.

Here’s video of the presentation with a great technical overview of the system and a demo of it being used to monitor a sleeping infant from a distance.

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