Estimation of Blood Pressure and Pulse Transit Time Using Your Smartphone

It is widely recognized today that there is an alarming rise of lifestyle-induced chronic diseases (e.g., type II diabetes) in our society. Therefore, a strong need exists for cost-effective and non-invasive devices that can measure blood pressure (BP) to monitor, diagnose and follow-up patients at risk, but also healthy population in general. One promising method for arterial BP estimation is to measure a surrogate marker of it, such as, Pulse Transit Time (PTT) and derive pressure values from it. However, current methods for measuring PTT require complex sensing and analysis circuitry and the related medical devices are expensive and inconvenient for the user to wear. In this paper, we present a new smartphone-based method to estimate PTT reliably and subsequently BP from the baseline sensors on smartphones. This new approach involves determining PTT by simultaneously measuring the time the blood leaves the heart, by recording the heart sound using the standard microphone of the phone and the time it reaches the finger, by measuring the pulse wave using the phone’s camera. Moreover, we also describe algorithms that can be executed directly on current smartphones to obtain clean and robust heart sound signals and to extract the pulse wave characteristics using smartphones. We also present methods to ensure a synchronous capture of the waveforms, which is essential to obtain reliable PTT values with inexpensive sensors. Our experiments show that the computational overhead of the proposed two-phase processing method is minimum, with the ability to reliably measure the PTT values in a fully accurate (beat-to-beat) fashion using directly state-of-the-art smartphones as medical devices

Methods for reliable estimation of pulse transit time and blood pressure variations using smartphone sensors

Hypertension is known to affect around one third of adults globally and early diagnosis is essential to reduce the effects of this affliction. Today’s Blood Pressure (BP) monitoring cuffs are obtrusive and in- convenient for performing regular measurements, and continuous non-invasive blood pressure devices are too complex and expensive for ambulatory use. Hence, there is a strong need for affordable systems that can measure blood pressure (BP) variations throughout the day as this will allow to monitor, diagnose and follow-up not only patients at risk, but also healthy population in general for early diagnosis. A promising method for arterial BP estimation is to measure the Pulse Transit Time (PTT) and derive pres- sure values from it. However, current methods for measuring this surrogate marker of BP require com- plex sensing and analysis circuitry and the related medical devices are expensive and inconvenient for the user. In this paper, we present new methods to estimate PTT reliably and subsequently BP, from the baseline sensors of smartphones. This new approach involves determining PTT by simultaneously mea- suring the time the blood leaves the heart, by recording the heart sound using the standard microphone of the phone, and the time it reaches the finger, by measuring the pulse wave using the phone’s camera. We present algorithms that can be executed directly on current smartphones to obtain clean and robust heart sound signals and to extract the pulse wave characteristics. We also present methods to ensure a synchronous capture of the waveforms, which is essential to obtain reliable PTT values with inexpen- sive sensors. Additionally, we combine Autocorrelation and Fast Fourier Transform (FFT)-based methods for reliably estimating the user heart rate (HR) from his/her heart sounds, and describe how to use the calculate HR to compensate for the camera frame rate variations and to improve the robustness of PTT estimation. Our experiments show that the computational overhead of the proposed processing meth- ods is minimum, which allows real-time feedback to the user, and that the PTT values are fully accurate (beat-to-beat), thereby enabling state-of-the-art smartphones to be used as affordable medical devices

Ultra-Low Power Design of Wearable Cardiac Monitoring Systems

This paper presents the system-level architecture of novel ultra-low power wireless body sensor nodes (WBSNs) for real-time cardiac monitoring and analysis, and discusses the main design challenges of this new generation of medical devices. In particular, it highlights first the unsustainable energy cost incurred by the straightforward wireless streaming of raw data to external analysis servers. Then, it introduces the need for new cross-layered design methods (beyond hardware and software boundaries) to enhance the autonomy of WBSNs for ambulatory monitoring. In fact, by embedding more onboard intelligence and exploiting electrocardiogram (ECG) specific knowledge, it is possible to perform real-time compressive sensing, filtering, delineation and classification of heartbeats, while dramatically extending the battery lifetime of cardiac monitoring systems. The paper concludes by showing the results of this new approach to design ultra-low power wearable WBSNs in a real-life platform commercialized by SmartCardia. This wearable system allows a wide range of applications, including multi-lead ECG arrhythmia detection and autonomous sleep monitoring for critical scenarios, such as monitoring of the sleep state of airline pilot