Smartphone as an ultra-low cost medical tricorder for real-time cardiological measurements via ballistocardiography

Abstract

In this preliminary study, we investigate the potential use of smartphones as portable heart-monitoring devices that can capture and analyse heart activity in real time. We have developed a smartphone application called "Medical Tricorder" that can exploit smartphone's inertial sensors and when placed on a subject's chest, it can efficiently capture the motion patterns caused by the mechanical activity of the heart. Using the measured ballistocardiograph signal (BCG), the application can efficiently extract the heart rate in real time while matching the performance of clinical-grade electrocardiographs (ECG). Although the BCG signal can provide much richer information regarding the mechanical aspects of the human heart, we have developed a method of mapping the chest BCG signal into an ECG signal, which can be made directly available to clinicians for diagnostics. Comparing the estimated ECG signal to empirical data from cardiovascular diseases, may allow detection of heart abnormalities at a very early stage without any medical staff involvement. Our method opens up the potential of turning smartphones into portable healthcare systems which can provide patients and general public an easy access to continuous healthcare monitoring. Additionally, given that our solution is mainly software based, it can be deployed on smartphones around the world with minimal costs.

Biomedical Signal Processing: The Cornerstone of Artificial Intelligence in Healthcare Wearables

“…Clinically validated data acquisition systems found in hospitals are cumbersome to use and require specialized technicians [1][2][3]. The availability of miniaturized cardiovascular wearable diagnostic sensors worn usually on the chest or wrists for cardiorespiratory or body-motion detection typically in smartphones have allowed for (i) longer durations of ambulatory monitoring for at-risk patients [4]; (ii) a prolonged use of wearables by asymptomatic, healthy subjects for assessing physical fitness or improving individual perception of well-being [5]; (iii) and the implementation of follow-up protocols for at-risk patients, in the form of alerts sent to patients or caregivers. Textile wearables are widely used as well [6].…”

“…Developers are provided with generic sensors for devising software for "well-being" applications, which are likely to be the output of team programmers, without the involvement of clinicians or biomedical engineers who understand the underlying physiological and sensor mechanisms. It is therefore not surprising that, between the beginning of 2020 and the end of 2021, the number of mHealth apps available to Android users reached over 65,300 thousand, 4 the majority of which lack scientific evidence of their function, and only four of these have been subjected to clinical trials [5]. This is a concern as there is a high-risk of implications for the use of 'well-being' applications of wearables due to misinformation, misdiagnosis or even mistreatment that can be caused by these Apps.…”

ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

“…In general, cost reduction is also an extremely important objective of many performance-based monitoring systems. Different approaches lead to cost reduction, including the use of low-cost devices, such as smartphones [232,[244][245][246]. Other studies proposed special low-cost circuit designs [247].…”

Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection

“…The heartbeat fiducial points on the m-ACC signal associated to the sharp cardiac vibration waves in concomitance to the systolic activity can be detected using an electrocardiogram (ECG)-independent processing algorithm, and used to compute the cardiac interbeat interval, thus obtaining corresponding beat-to-beat time series. The feasibility and accuracy of measuring the beat-to-beat heart rate using smartphone accelerometers has been recently demonstrated [7,8,9,10,11,12,13].…”