Multimedia sensors embedded in smartphones for ambient assisted living and e-health

The final publication is available at link.springer.com[EN] Nowadays, it is widely extended the use of smartphones to make human life more comfortable. Moreover, there is a special interest on Ambient Assisted Living (AAL) and e-Health applications. The sensor technology is growing and amount of embedded sensors in the smartphones can be very useful for AAL and e-Health. While some sensors like the accelerometer, gyroscope or light sensor are very used in applications such as motion detection or light meter, there are other ones, like the microphone and camera which can be used as multimedia sensors. This paper reviews the published papers focused on showing proposals, designs and deployments of that make use of multimedia sensors for AAL and e-health. We have classified them as a function of their main use. They are the sound gathered by the microphone and image recorded by the camera. 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Real-time human ambulation, activity, and physiological monitoring:taxonomy of issues, techniques, applications, challenges and limitations

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Unobtrusive Health Monitoring in Private Spaces: The Smart Home

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A photoplethysmography smartphone-based method for heart rate variability assessment: device model and breathing influences

© 2019 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/A measurement method of heart rate and heart rate variability (HRV) based on smartphone has been developed and validated. The method is based on photoplethysmography (PPG) acquired with the smartphone camera (SPPG). SPPG was compared with the electrocardiogram (ECG), used as the gold standard, and with an external PPG sensor. Twenty-three healthy subjects were measured using two different smartphone models in three different breathing conditions. The error of the first differentiation between SPPG and ECG series is minimized with the fiducial point at maximum first derivative of the SPPG. The obtained standard deviation of error (SDE) between SPPG and ECG is around 5.4 ms and it is similar to SDE between PPG and ECG. Good agreement between SPPG and ECG for NN, SDNN and RMSSD have been found but it is insufficient agreement for LF/HF. Similar levels of agreement for SPPG-ECG and PPG-ECG have been obtained for the HRV indices. Finally, the differences between smartphone models for HRV indices are slight. Therefore, the smartphone can be used for measuring accurately the following HRV indices: NN, SDNN and RMSSD.Peer ReviewedPostprint (published version