The heart is an amazing organ, not because it has to work ceaselessly throughout an entire lifetime, but because it has to do that under constantly variable conditions, literally without missing a beat. While fitness trackers do a pretty good job of counting these beats in a low-resolution way, the techniques used to do it are not all that accurate, at least not in medical terms.
Optoelectronics is probably the most common technique used for pulse rate measurement in wearable devices. However, because it uses light, it can be subject to ambient light levels, as well as proximity (fitness tracker manufacturers usually recommend a close, tight fit on the strap for best results). Of course, having some indication of your heart’s activity is better than having none, even if the results may vary. The medical profession counts the heart rate as one of the four vital signs (alongside temperature, respiratory rate, and blood pressure). However, the heart can offer much more information and by analyzing that data, it is possible to detect a broader range of conditions.
Each time the heart beats, its cells undergo something called depolarization and repolarization; the electrical charge in the heart’s cells changes and in doing emit a small amount of their charge. This electrical activity can be detected using sensors placed on the body, something most people will recognize as an electrocardiograph or ECG.
Thanks to developments in integrated electronics and embedded software, ECGs are becoming available for use outside of hospitals and even by non-medical people. This signals a change in the way we approach healthcare, by making it simpler for concerned consumers to monitor their bodies, using equipment that can be seen as "medical-grade."
The Internet of Medical Things, or IoMT, is also a factor. The emerging infrastructure, such as cloud connectivity and platforms as a service, allows the data gathered to be analyzed by medical professionals or even expert AI systems. This can be used to detect the warning signs that often precede a cardiac event. Trend data gathered over longer periods, when compared against larger samples across carefully classified parts of the population, could even lead to much earlier diagnoses of preventable heart conditions. This is the real potential of the IoMT.
Semiconductor manufacturers are now supporting this application area with solutions that could be used to develop more diverse and, importantly, more mobile ECG devices. The level of processing, while significant, can now be handled by more modest and cost-effective integrated solutions. Microchip Technology, for example, has imagined an ECG solution in which a large part of the digital signal processing needed to detect the small signals picked up by the sensors is handled by a member of its PIC18 family of 8-bit microcontrollers. The complete solution also draws in Microchip’s portfolio of instrumentation amplifiers and Sigma Delta ADCs to create a robust Analog Front End to the system.
While ECG has many benefits in healthcare, it could be argued that its main drawback is the need to have the sensors in close contact with the skin. In a home care scenario where long-term monitoring is required, this could be considered unsustainable; a more viable solution would be a non-contact form of measurement.
One technique that shows real promise is Ballistocardiology (BCG), which measures the heart’s activity differently. Instead of detecting electrical pulses, the sensors used pick up the effect on the body of blood being pumped out of the left ventricle and into the aortic artery. As the blood is forced into the aorta it ‘pushes back’ against the rest of the body (the ballistic part of the name), sending tiny but discernable vibrations through the body.
Incredible as it may sound, if a patient lays still enough on a suitable platform, such as a well sprung mattress and bed, these movements can be detected and interpreted to give a level of information similar to that provided by an ECG.
The significant advantage of BCG monitoring is that the device can be placed under the mattress and be completely non-invasive, allowing measurements to be taken as a matter of course without the need for any user intervention. To demonstrate this, Murata has developed a complete platform, the SCA11H, which includes WiFi connectivity for relaying measurements to a server or cloud platform. The module that empowers the platform, the SCA10H, is also available. It is enabled by one of Murata’s most accurate MEMS accelerometers, the SCA61T, which has a noise density that is around 20 times better than the MEMS sensors typically used in fitness trackers.
Thanks to the IoT and a general thirst for knowledge healthcare is evolving rapidly. Taking control over your physical condition is becoming simpler, enabled by trends like fitness trackers, wearable electronics, and cloud-based AI systems.