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

Health sensors and remote measurement tools have saved lives through the possibility of continuous monitoring and inter- vention tools, and over the years their use has expanded to non-medical areas such as fitness and perceived well-being. This expansion has led to unprecedented data collection, especially since biomedical sensors are now ubiquitous in everyday devices such as smartwatches and smartphones. While these devices can be disruptive research tools and even clinical tools, they pose technological and socio-economic challenges that can limit their impact. Here, we highlight these challenges, including the use of proxies for clinical reference measurements, uncertainties resulting from the presence of noise, com- plexity of physiological systems, and statistical methods used for data interpretation

Atrial Fibrillation Detection via Accelerometer and Gyroscope of a Smartphone

Atrial Fibrillation (AFib), which utilizes the built-in accelerometer and gyroscope sensors (Inertial Measurement Unit, IMU) in the detection. Depending on the patient’s situation,it is possible to use the developed smartphone application either regularly or occasionally for making a measurement of the subject. The smartphone is placed on the chest of the patient who is adviced to lay down and perform a non-invasive recording, while no external sensors are needed. After that, the application determines whether the patient suffers from AFib or not. The presented method has high potential to detect paroxysmal (”silent”) AFib from large masses. In this paper, we present the pre-processing, feature extraction, feature analysis and classification results of the envisioned AFib detection system based on clinical data acquired with a standard mobile phone equipped with Google Android OS. Test data was gathered from 16 AFib patients (validated against ECG), as well as a control group of 23 healthy individuals with no diagnosed heart diseases. We obtained an accuracy of 97.4% in AFib vs. healthy classification (a sensitivity of 93.8% and a specificity of 100%). Due to the wide availability of smart devices/sensors with embedded IMU, the proposed methods could potentially also scale to other domains such as embedded body-sensor networks.</p

Measuring of pulse rate using smartphone

Tato bakalářská práce se zabývá možností měření tepové frekvence pomocí chytrého telefonu. V dnešní době velká část lidí vlastní chytrý mobilní telefon a novější přístroje díky svým senzorům a dalšímu vybavení dokáží zaznamenávat různá data. Aktuální trend je využití těchto dat tak, aby mobilní telefon nahradil přístroje jiné, např. navigaci, fotoaparát, videokameru či multimediální přehrávač. V poslední době nacházejí mobilní telefony uplatnění také v oblasti medicíny a díky jejich masovému rozšíření je zde potenciál využití k včasnému odhalení zdravotních problémů. S funkční mobilní aplikací se vyšetření stává levné, rychlé, stále dostupné a snadné pro širokou veřejnost. Na začátku práce je uveden základní anatomický a fyziologický popis srdce a oběhové soustavy, dále je zde pojednáno o měření TF, historii měření, metodách měření TF a problematice měření TF pomocí chytrého telefonu. Dále jsou popsány dvě navržené metody využívající mikrofon a akcelerometr mobilního telefonu. U každé metody je popsáno provedené testování a statistické vyhodnocení. Práce potvrdila možnost využití těchto metod pro relativně přesné měření tepové frekvence, a to i za různých podmínek měření. Vytvořené aplikace s grafickým uživatelským rozhraním jsou v práci popsány i s ukázkami. Poslední část obsahuje porovnání metod, doporučení pro měření a závěrečné vyhodnocení.This bachelor thesis deals with the possibility to measure heart rate using a smartphone. Today, many people own a smartphone. Newer devices can record various data thanks to its sensors and additional equipment. The current trend is to use the data so that the mobile phone can replace other devices, e.g. navigation, camera, camcorder or multimedia player. Recently, mobile phones have also been used in the field of medicine and, thanks to their mass extension, there is the potential to use them to detect health problems early on. With a functional mobile application, testing becomes cheap, fast, always available and easy to the general public. The beginning of the thesis describes the basic facts about physiology and anatomy of the heart, and circulatory system. Methods of heart rate monitoring using standard devices and smartphones, and measurement history are discussed as well. Two proposed methods using the smartphone's microphone and accelerometer are described below. For each method, testing and statistical evaluation are described. The thesis confirmed the possibility of using these methods for relatively accurate pulse rate measurement, even under different measuring conditions. Created applications with graphical user interfaces are described in the thesis including examples. The last part contains a comparison of methods, recommendations for measurement and final evaluation.