Test Scenario 2: Standing still and chewing
In Scenario 2, additional chewing motions are introduced. The recorded spectra are shown in Figure 4. Unlike in Test Scenario 1,
motion artifacts can be clearly seen, which are reflected in the signal as jumps. They also become clear in the sum of the channels, which no longer exhibit such clearly differentiated rates. Nevertheless, the algorithm is capable of correctly determining the heart rate with a high confidence without the additional help of motion sensors. Interestingly, the infrared signal strength is once again greater than that of the red channel.
measurement for standing still and chewing and the
infrared region (b) shows raw and summed data.
The heart rate (black line) can be determined from the
summed data by the algorithm. The heart rate can
be determined without an accelerometer.
Test Scenario 3: Working at a desk
measurement for working at a desk and the infrared
region (b) shows raw and summed data. The heart rate
(black line) can be determined from the summed data
by the algorithm.
In Scenario 3, another everyday situation is tested. The test person sits at a desk and carries out normal tasks and the movements associated with them. Similarly to Scenario 2, motion artifacts can be detected, whereby the algorithm can identify the heart rate in both channels. As can be seen in Figure 5, the infrared signals dominate here, too.