Medical Electronics
Figure 3: An HRM/HRV evaluation system, using an AS7000 mounted in a wristband
RR intervals). As Figure 1 shows, these peaks are sharp and narrow. Even in a noisy signal, it is comparatively easy to time the RR intervals. To measure PRV, the peak-to-peak interval must also be timed. As Figure 2 shows, however, the peaks in the PPG waveform are shallower and flatter, and are therefore more difficult to measure accurately, even under stationary (relatively low noise) conditions. Noise in the form of motion artefacts is very difficult to distinguish from PPG peaks, and so movement makes PRV measurement even harder to accomplish.
In the setting of a wristband, motion artefacts can be generated by even very slight movements. For instance, finger movements that stretch or contract the tendons below the wristband’s photosensor have a marked impact on the PPG signal. In addition, any movement of the wristband itself will slightly change the pressure of the sensor on the skin. As a result, a wristband can only reliably capture PRV measurements during sampling intervals when the user is completely still.
Optimising the electrical, optical and mechanical design Assuming that the user remains still, the measurement device must still capture the reflected light signals, which are of very low intensity, discriminate reliably between signals and noise, and then accurately detect the peak in a signal with the smooth
waveform shown in Figure 2. This calls for optimisation of the electrical, optical and mechanical elements of a wristband. A wristband implementation based on the AS7000 benefits from ams’s inherently low-noise and high-sensitivity analogue circuitry (an attribute of its proprietary semiconductor fabrication technology). In the AS7000, however, ams has also implemented specific design techniques such as modulation and demodulation of the LED output, combined with amplifiers optimised for the modulation frequency; this reduces noise without greatly affecting power consumption. The AS7000 also includes filters to reduce the sensor’s bandwidth, again to remove noise. ams also provides detailed guidelines for the opto-mechanical design of the whole system. These comprehensive guidelines address the design and materials of the wriststrap and the overlay on the base of the device. The aim should be to achieve a tight comfortable fit in order to couple the device closely to the user’s skin. These guidelines ensure that motion-induced noise is kept to a minimum. Finally, ams supplies the algorithm for converting the PPG signal into a set of PRV peak-to-peak times, running in the AS7000. An I2C interface to the host provides the PRV times in milliseconds. In other words, the AS7000 provides a complete hardware and software solution for PRV measurement in a wristband.
Figure 5: Scatter plot showing both the AS7000 PRV output and the reference output
But can an AS7000-based implementation produce accurate PRV measurements?
Comparison with reference measurements ams has evaluated the PRV measurement performance of the AS7000 by comparing it to a gold standard reference: HRV measurements captured by an ECG. The test set-up involved an AS7000 placed in an armband on the wrist (see Figure 3). The AS7000 calculated the PRV output in ms, and sent the data via a Bluetooth wireless interface to a mobile phone, which was used as a data logger. The same test subject also wore paediatric limb clamp electrodes to capture an ECG signal. The RR peaks in the ECG signal were calculated offline. The two sets of measurements can be
compared to each other in three ways. Figure 4 shows a direct comparison of the HRV (ECG) measurements against the PRV (PPG) measurements captured by the
The medical profession commonly uses a Bland-Altman plot to compare a gold standard measurement with a new measurement and determine whether the difference between the two is significant. The plot uses Cartesian coordinates, in which the x axis marks the average of the two methods, and the y axis marks the difference, as plotted in Figure 6. Figure 6 shows that almost every data point is within a +/-1.96 standard deviation of the mean. According to the accepted Bland-Altman method, this means that the reference measurement method and the new PRV measurement method implemented by the AS7000-based wristband are interchangeable.
Conclusion
A wristband using the AS7000 may be worn 24/7 to provide PRV results almost as accurate as HRV measurements captured with a gold standard ECG device, and as clinically valid according to the Bland- Altman analysis.
Figure 6: Bland-Altman plot of PRV measurements against reference measurements
AS7000. The close match between the two curves shows that the AS7000’s output is very close to that of the reference output.
This comparison can also be displayed in the form of a scatter plot (see Figure 5). Figures 4 and 5 show that there is only a
Figure 4: The HRV and PRV measurements closely match one another. The x axis shows the time in ms
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small difference between the PRV measurements made by the AS7000 and the reference HRV measurements. But is this difference statistically significant?
This means that a convenient comfortable wristband may be used to provide the PRV indicators for, for instance, stress levels or sleep quality. This opens up a new field of applications for the end user, benefiting from the innovations in the AS7000 to provide reliable, accurate heart rate measurements as a natural and convenient part of everyday life.
www.ams.com Components in Electronics May 2017 27
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