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Towards the Development of Sensor Platform for Processing Physiological Data from Wearable Sensors

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10842)

Abstract

The paper outlines a mobile sensor platform aimed at processing physiological data from wearable sensors. We discuss the requirements related to the use of low-cost portable devices in this scenario. Experimental analysis of four such devices, namely Microsoft Band 2, Empatica E4, eHealth Sensor Platform and BITalino (r)evolution is provided. Critical comparison of quality of HR and GSR signals leads to the conclusion that future works should focus on the BITalino, possibly combined with the MS Band 2 in some cases. This work is a foundation for possible applications in affective computing and telemedicine.

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Fig. 1.
Fig. 2.

Notes

  1. 1.

    With the use of e.g. AWARE framework, see http://www.awareframework.com/.

  2. 2.

    For details see http://bitalino.com/.

  3. 3.

    For details see https://www.cooking-hacks.com/documentation/tutorials/ehealth-biometric-sensor-platform-arduino-raspberry-pi-medical.

  4. 4.

    See: http://psychopy.org.

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Correspondence to Szymon Bobek .

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Kutt, K., Binek, W., Misiak, P., Nalepa, G.J., Bobek, S. (2018). Towards the Development of Sensor Platform for Processing Physiological Data from Wearable Sensors. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2018. Lecture Notes in Computer Science(), vol 10842. Springer, Cham. https://doi.org/10.1007/978-3-319-91262-2_16

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  • DOI: https://doi.org/10.1007/978-3-319-91262-2_16

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