Optical heart rate measurement at the earbud: Page 3 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 1: Standing still


Fig. 2: Measuring the amplitude oversampling
rate provides information about the heart rate.

Figure 2 shows the spectrum of raw data with the amplitude plotted against the sampling rate. The pulse beats can be identified over time by the peak values. Without movement, the signal is very clear and the heart rate can be determined via the peak position and the known sampling rate.

The optical sensor records heart rates in two LED colors—infrared and red—with four channels each. In this way, differentiation can be made between the measurements with the two different color channels and the more robust variant can be selected. The signals of the various channels are shown in Figure 3a. With six channels, a clearly defined signal can be identified, while two channels are saturated. To achieve a stronger and more robust signal, the algorithm adds the respective unsaturated channels and calculates the heart rate. Figure 3b shows the heart rate for the red channel (top) and the infrared channel (bottom) and simultaneously indicates the confidence level for the measurement by means of the color scale. Multiples of the heart rate are also given, whereby the original signal (dashed line) can be distinguished by the sampling rate and the confidence indication.


Fig. 3: The red region (a) shows a four-channel
measurement for standing still, while the infrared
region (b) shows raw and summed data.
 

In summary, with no motion, the signal is strong and has no obstructing noise, so the algorithm can determine the rate with high confidence. The signal from the infrared channel is stronger than that from the red one.

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