Novel Human Computer Interaction Principles for Cardiac Feedback using Google Glass and Android Wear

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Richer R, Maiwald T, Pasluosta CF, Hensel B, Eskofier B
Editor(s): IEEE
Publication year: 2015
Conference Proceedings Title: 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)
ISBN: 978-1-4673-7201-5
ISSN: 2376-8894
Language: English


Abstract





This work presents a system for unobtrusive cardiac feedback in daily life. It addresses the whole pipeline from data acquisition over data processing to data visualization including wearable integration. ECG signals are recorded with a novel ECG sensor supporting Bluetooth Low Energy, which is able to transmit raw ECG data as well as estimated heart rate. ECG signals are processed in real-time on a mobile device to automatically classify the user's heart beats. A novel application for Android-based mobile devices was developed for data visualization. It offers several modes for cardiac feedback, from measuring the current heart rate to continuously monitoring the user's heart status. It also allows to store acquired data in an internal database as well as in the Google Fit platform. Further, the application provides extensions for wearables like Google Glass and smartwatches running on Android Wear. Hardware performance evaluation was performed by comparing the course of heart rate between the novel ECG sensor and a commercial ECG sensor. The mean absolute error between the two sensors was 4.83 bpm with a standard deviation of 4.46 bpm, and a Pearson correlation of 0.922. A qualitative evaluation was performed for the Android application with special emphasis on the daily usability and the wearable integration. When the Google Glass was integrated, the subjects rated the application as 2.8/5 (0 = Bad, 5 = Excellent), whereas when the application was integrated with a smartwatch the rating increased to 4.2/5.





 



FAU Authors / FAU Editors

Eskofier, Björn Prof. Dr.
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Hensel, Bernhard Prof. Dr.
Max Schaldach-Stiftungsprofessur für Biomedizinische Technik
Maiwald, Tim
Lehrstuhl für Technische Elektronik
Pasluosta, Cristian Federico
Stiftungs-Juniorprofessur für Sportinformatik (Digital Sports)
Richer, Robert
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)


How to cite

APA:
Richer, R., Maiwald, T., Pasluosta, C.F., Hensel, B., & Eskofier, B. (2015). Novel Human Computer Interaction Principles for Cardiac Feedback using Google Glass and Android Wear. In IEEE (Eds.), 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN). Cambridge, MA, US.

MLA:
Richer, Robert, et al. "Novel Human Computer Interaction Principles for Cardiac Feedback using Google Glass and Android Wear." Proceedings of the 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN), Cambridge, MA Ed. IEEE, 2015.

BibTeX: 

Last updated on 2018-19-04 at 03:30