Optical heart rate measurement at the earbud: Page 5 of 6

November 18, 2019 //By Christoph Kämmerer
heart rate
Advancements in sensor technology have transformed how and where people diagnose their vitals and health. Portable, noninvasive measurement techniques permit fast and simple measurements that can be performed while we go about our daily lives. But although this diagnostic technology has become very popular in the fitness industry, there were limits to its accuracy that we have only recently overcome.

Test Scenario 4: Walking

While the previous scenarios addressed stationary measurement conditions, the test person in this case moves uniformly in one direction at a low speed (about 50 steps per minute).

As shown in Figure 6, the heart rate mixes with the walking pace in the PPG signal and the sum of the various channels shows a very blurry signal. While no defined heart rate can be calculated in the red signal field, the algorithm finds a fit in the infrared one. As a result of the large fluctuations and the low confidence matrix, however, additional motion data from an accelerometer would be tremendously helpful, especially because, up to now, measurements were only made at a low walking speed.


Fig. 6: The red region (a) shows a four-channel
measurement for walking and the infrared region (b)
shows raw and summed data.

Test Scenario 5: Running and jumping


Fig. 7: The red region (a) shows a four-channel
measurement for running and jumping and the
infrared region (b) shows raw and summed data.

Instead of measuring uniform movement, Scenario 5 introduces alternating sprinting and jumping intervals. The motion artifacts can now be very clearly identified, whereby the algorithm has great difficulty isolating a correct heart rate as shown in Figure 7. The need for motion sensor support seems to be unavoidable.

Design category: 

Vous êtes certain ?

Si vous désactivez les cookies, vous ne pouvez plus naviguer sur le site.

Vous allez être rediriger vers Google.