Abstract
In this paper, we present an Android application to control and monitor the physiological sensors from the Shimmer platform and its synchronized working with a driving simulator. The Android app can monitor drivers and their parameters can be used to analyze the relation between their physiological states and driving performance. The app can configure, select, receive, process, represent graphically, and store the signals from electrocardiogram (ECG), electromyogram (EMG) and galvanic skin response (GSR) modules and accelerometers, a magnetometer and a gyroscope. The Android app is synchronized in two steps with a driving simulator that we previously developed using the Unity game engine to analyze driving security and efficiency. The Android app was tested with different sensors working simultaneously at various sampling rates and in different Android devices. We also tested the synchronized working of the driving simulator and the Android app with 25 people and analyzed the relation between data from the ECG, EMG, GSR, and gyroscope sensors and from the simulator. Among others, some significant correlations between a gyroscope-based feature calculated by the Android app and vehicle data and particular traffic offences were found. The Android app can be applied with minor adaptations to other different users such as patients with chronic diseases or athletes.
Highlights
Mobile devices are increasingly present in our daily life
The Android application has been tested with four Android devices and with different number of sensors, sampling rates, and signals to obtain in each sensor
We focused on the data extracted from the gyroscope and the variables computed by the Android app from these data
Summary
Mobile devices are increasingly present in our daily life. With the widespread use of these devices, there is a huge demand for applications to address the need of millions of users in many fields such as education, health, business, commerce, and entertainment. Wearable sensors have gained a lot of importance in different fields such as education [2] and health [3,4] These sensors play a main part in ambient intelligence research on its way to revolutionize daily human life by making people’s environments sensitive, flexible, and responsive [5]. Sensors should have the features required for m-health (mobile health) to address its four main challenges: continuous monitoring, full involvement, interoperability, and disappearing interaction [7]. They have to be Sensors 2019, 19, 399; doi:10.3390/s19020399 www.mdpi.com/journal/sensors
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