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Review
. 2018 Feb;28(2):144-150.
doi: 10.1016/j.tcm.2017.08.003. Epub 2017 Aug 9.

Wearable technology for cardiology: An update and framework for the future

Joshua M Pevnick  1 , Kade Birkeland  2 , Raymond Zimmer  3 , Yaron Elad  4 , Ilan Kedan  5
Affiliations
Review

Wearable technology for cardiology: An update and framework for the future

Joshua M Pevnick et al. Trends Cardiovasc Med. 2018 Feb.

Abstract

The field of cardiology has long used wearable medical devices to monitor heart rate and rhythm. The past decade has seen the emergence of many new wearable devices, including several that have been widely adopted by both physicians and consumers. In this review, we discuss existing and forthcoming devices designed to measure activity, heart rate, heart rhythm, and thoracic fluid. We also offer several frameworks to classify and better understand wearable devices, such that we may weigh their potential benefit in improving healthcare with the many challenges that must be addressed to reap these benefits.

Keywords: Biosensors; Cardiology; Clinical decision support; Patient-generated data; Wearables.

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Conflict of interest statement

Conflict of Interest: There were no other relevant funding sources, and the authors have no conflicts of interest with this work.

Figures

Figure 1
Figure 1
A Taxonomy of Wearable Data Collection Mechanisms. Wearable data can be either actively or passively acquired in a continuous or intermittent manner. These data can then be transmitted continuously or stored and then later retrieved. Based on these categorizations, all wearable devices manage data in one of the six ways described above.
Figure 2
Figure 2
Wearable data feedback loop. Wearable data is acquired and then analyzed. The analyzed data can offer decision support and effect modification of behavior or management.
Figure 3
Figure 3
A taxonomy of decision support derived from wearable data: Devices may offer built-in therapies. In non-therapeutic devices, the data generated may offer decision support to inform diagnosis, management, prognosis, or be of uncertain utility.
Figure 4
Figure 4
Wearables leveraging data measured at the cellular, physiological and individual levels to better synthesize affiliations of data on a group/family, population/community, and regional/environmental/ecosystems level. Aggregation of data for assessing bidirectional changes in patterns of actions.
See this image and copyright information in PMC

Comment in

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