5.1. Idle Mode Power Consumption
All measured idle mode power consumption parameters presented in
Section 3 are summarized in
Table 2. The ECG sensor cannot be put in fast advertising and slow advertising modes manually. It alternates between the two advertising modes automatically, and therefore the measurements of individual advertising modes have to be differentiated based on the readings of the multimeter. Both advertising periods are long enough for the values on the multimeter to settle, and reliable current values can be read. The overall average advertising current consumption
can be calculated from both of the measured current consumptions—
and
—as presented with Equation (
4).
In
Table 3, both measured values and model-based values for the idle mode of the ECG sensor are shown.The
and
values represent the measured power and current consumption, respectively, while
and
represent the model-based calculated power and current consumption values, respectively. The results show that the measured and calculated values are very similar, which presents a very good model fit to the actual power and current consumption values, with less than 2% maximal error in current consumption, while average advertising current consumption fits perfectly. The error is calculated as deviation of the modeled value from the measured value, and expressed as percentage of the measured value.
5.3. Analysis of Sensor Autonomy
To translate power consumption to sensor autonomy, we divide the battery capacity by the average current consumption in the selected sensor mode. The analyzed sensor has an integrated 240
lithium-ion battery that stores enough energy for several days of continuous ECG signal streaming. The results of ECG sensor autonomy estimation based on measured average current consumption and estimated current consumption are collected in
Table 6. The results show that by quadrupling the ECG sampling rate and thus quadrupling the amount of bytes transferred, the sensor autonomy is reduced by a factor of two. The typical autonomy of modern smartphones, assuming an average user, is around one day, while the sensor on a single charge lasts for around four days with 512 sps and more than eight days with 128 sps. When the sensor is neither in active mode nor in shutdown mode, it stays in idle mode, where advertising takes place with average advertising power consumption
, which gives us 31.5 days of autonomy while waiting to start ECG measurements. Thus, with regular weekly use, shutting down the sensor seems unnecessary. This further simplifies the usage for non-tech-savvy users.
The most influencing parameter on the sensor autonomy is the ECG sampling rate. Sampling rate directly imposes requirements on the length of connection interval, which has to be, on one hand, short enough to enable transfer of all recorded ECG data, while, on the other hand, long enough not to waste energy with unnecessary empty connection events. By decreasing the length of the connection interval, the density of transmission events increases, which consequently increases the average power consumption. The optimal connection interval for the selected sampling interval is therefore in our case , where 14 samples are packed in a single ECG report packet.
Before providing guidelines for further development of the ECG sensor, additionally to taking into consideration the power anatomy analysis, we also consider the experience gathered from users who bought/rented the device for themselves [
12] or used the device in a renting scheme with weekly turn-around [
13]. While most of the experience is beyond the scope of this article, the most important findings are summarized below. The first finding refers to the current autonomy of the sensor as more than sufficient. While the sensor has been mostly used with maximum transmission power and a very low sampling frequency of 128 Hz, its autonomy far surpassed both the autonomy of smartphones, which it was used in combination with, and the period in which people felt comfortable wearing it continuously. While the latter varies from person to person, most people are inclined to remove it after 2 days of use or less. This is not due to the weight of the device worn on one’s chest—most people find it completely unobtrusive—but because self-adhesive electrodes are required, which are prone to irritating the skin. Therefore, the autonomy could be reduced to just above 2 days under some usage scenarios. The second finding was that the sensor’s sampling frequency of 128 samples/s was often too low for clinical use. The medical personnel examining measurements expressed their wish for more details, which would broaden the specter of potential use of the sensor. Since the sensor is an excellent platform for long-term heart rate variability monitoring, the rate of 250–500 samples/s was taken as a design goal, based on research which excluded lower frequencies as insufficient [
33]. Lastly, the processing requirements of the sensor have not increased, so neither the MCU replacement nor a change in its usage pattern was planned.
Having the power consumption model available, as well as the above experience, both user-subjective and medical, we are able to make recommendations regarding the sensor redesign. Our recommendations are to increase the sampling frequency to 512 and leave radio transmission power at 0 dB, since its effect on autonomy is insignificant. The sampling frequency increase is required to increase the sensor’s capabilities, often required by the medical personnel, and is enabled by the continuous development of more capable smartphone hardware, which no longer struggle with receiving more than 128 samples per second. Furthermore, we envision two scenarios regarding the battery capacity, which can be used to tailor the next version of the sensor. The first scenario is to decrease the battery capacity to 160 , provided that it would also lead to sensor size, weight, and price reduction. While a smaller battery would primarily increase comfort, it might also help reduce the motion-induced measurement artifacts due to reduced sensor weight. Under this scenario, the users would be required to recharge the sensor every 2 days or less, which would still be acceptable since a large portion of users already require a break from the irritable self-adhesive electrodes in nearly the same time. In the second scenario, the battery could be increased to 400 , extending the autonomy to over 5 days at 512 sampling rate, which might be seen as beneficial for health care services where the sensor is lent to a different user every week. The users would therefore not even need a charger, which would make this scenario more user-friendly. The battery would have to be larger and heavier though, which might create some unforeseen adverse effects for the engineers designing the device and for the users wearing it. Given that, so far, no user has complained about the device weight, this might be a path worth exploring.