A review of patient-led data acquisition for atrial fibrillation detection to prevent stroke. (August 2021)

• Record Type: Journal Article
• Authors: Kareem, Murtadha; Lei, Ningrong; Ali, Ali; Ciaccio, Edward J.; Acharya, U. Rajendra; Faust, Oliver
• Is Part Of: Biomedical signal processing and control. Volume 69(2021)
• Publication Date: 2021-08
• Subjects: Patient-led data acquisition -- Atrial fibrillation monitoring -- Stroke prevention -- Human factors -- Service design -- Arrhythmia -- Physiological signal; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2021.102818
• Languages: English
• ISSNs: 1746-8094

Abstract

Abstract: In this paper we review devices that can be used in the home environment for Atrial Fibrillation (AF) detection. Detection and subsequent treatment of this heart rhythm disorder is an important strategy for stroke prevention, because AF increases stroke risk fivefold. The device review was carried out in two steps. In the first step, we have examined technology used, human factors, and cost. The findings were utilized to create a taxonomy of patient-led data acquisition systems. In the second step, we used that taxonomy to review practical stroke risk monitoring services. On a technical level, such services belong either to the signal recording or event trigger category. Signal recording systems deal with data which can serve as evidence for human decision-making. In contrast, event trigger systems address information which has a significantly lower data rate when compared with raw signal data. Another finding of our review is that a stroke risk monitoring service can either be directed at patients or at healthcare providers. Being directed at patients implies that the service is rendered by a health gadget which can only be used to raise a suspicion about the stroke risk. Only medical devices can direct their services at healthcare providers who must pay for data and information that can help with a diagnosis. Our investigation shows that patient-led data acquisition is a practical way to increase the measurement duration of physiological signals and thereby help to detect and treat more AF which might prevent stroke.