VARSE: Android app for real-time acquisition and analysis of heart rate signals
UNIVERSAL IDENTIFIER: http://hdl.handle.net/11093/3085
EDITED VERSION: https://linkinghub.elsevier.com/retrieve/pii/S1386505622000065
UNESCO SUBJECT: 3304.99 Otras
DOCUMENT TYPE: article
Background and objective: nowadays, numerous mobile applications capable of measuring the Heart Rate (HR) are continuously being launched. However, these tools do not allow to record and label the acquired HR signals while users are doing activities such as practising sports or viewing images. They do not allow to perform simultaneous HR acquisition and real-time HRV analysis, either. VARSE is an app for Android mobile devices capable of acquiring and labelling HR signals and of performing real-time HRV analysis.Methods: VARSE was developed for Android devices. It includes functionalities to acquire HR signals from any Bluetooth device that implements the Heart Rate Profile specification (such as a chest strap), while labelling segments of the HR data in different situations. Not only can these signals be stored, but also time and frequency HRV analyses can be carried out over them. The application is distributed under the MIT license , and it is also available to be installed via Google Play . Functionality, ease-of-use and friendliness of VARSE were evaluated employing an User Experience Questionnaire (UEQ). Its reliability was proven by comparative studies against other existing acquisition (gVARVI) or HRV analysis (RHRV) software.Results: high values were obtained for all the dimensions evaluated in the UEQ, proving the quality of the application, as well as its ease-of-use and efficiency. Both HR signal acquisition and HRV analysis yielded results similar to the ones obtained using other applications.Conclusions: VARSE is a tool with complete functionality, that can be easily downloaded or installed on Android mobile devices. It can be used by anyone who wishes to record HR signals while performing different activities, and also by the medical scientific community to perform real-time HRV analyses easily. Future versions will improve its capabilities and allow its integration with other open source applications.
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