In a recent interview to Medgadget, a blog that is internationally considered a reference in reporting the latest medical technology news, IT researchers Ana Fred and Hugo Silva talked about their extensive work with Bitalino project that allows people to build body monitoring devices. In the Bitalino project, Ana Fred and Hugo Silva are developing an approach to integrate electrocardiography in everyday objects, were the sensors do not need to be with the person, but are embedded into the object (ex: a computer keyboard), hence being more pervasive. A major advantage of this approach is the fact that the sensor placement does not require a voluntary action from the user, unlike, for example, a smart watch.
In terms of the technology implementation requirements, the users need to have both left and right limbs in contact with the sensors. For instance, in the case of a keyboard implementation both hand palms would need to be in contact at the same time, even if momentarily. The researchers explain that “At the software level, this is intrinsically a signal processing and big data pattern recognition problem, but the solutions are becoming stabilized. Data acquisition has an intermittence to it (e.g. periodic loss of contact due to hands off events, or noise introduced by friction in the skin/sensor interface), which requires powerful de-noising and outlier detection algorithms. Once the sensors are placed in an interface that can be shared by multiple people (e.g. a steering wheel), determining even if a rough match between the collected data and its owner can also be an important requirement. Furthermore, the sheer volume of data collected that needs to be processed requires suitable frameworks to be dealt with”.
With prevention being one of the key-factors in managing the risks associated with cardiovascular diseases, there is a major role to be played by new solutions that can complement current practices and accelerate the detection of abnormalities. Ana Fred and Hugo Silva see pervasive ECG being used in an array of objects such as the hand rest of a laptop, a steering wheel of a car or any other object with which a subject regularly interacts. Other features derived from ECG signals, particularly Heart Rate Variability (HRV) or indicators such as mental workload, fatigue and overall affective state of the user, may extend the use of pervasive ECG to ergonomics, health and safety at work, or user-tuned personalisation of controllable workplace settings.