Accuracy and Systematic Biases of Heart Rate Measurements by Consumer-Grade Fitness Trackers in Postoperative Patients: Prospective Clinical Trial
Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-299679
- Background: Over the recent years, technological advances of wrist-worn fitness trackers heralded a new era in the continuous monitoring of vital signs. So far, these devices have primarily been used for sports. Objective: However, for using these technologies in health care, further validations of the measurement accuracy in hospitalized patients are essential but lacking to date. Methods: We conducted a prospective validation study with 201 patients after moderate to major surgery in a controlled setting to benchmark the accuracy of heartBackground: Over the recent years, technological advances of wrist-worn fitness trackers heralded a new era in the continuous monitoring of vital signs. So far, these devices have primarily been used for sports. Objective: However, for using these technologies in health care, further validations of the measurement accuracy in hospitalized patients are essential but lacking to date. Methods: We conducted a prospective validation study with 201 patients after moderate to major surgery in a controlled setting to benchmark the accuracy of heart rate measurements in 4 consumer-grade fitness trackers (Apple Watch 7, Garmin Fenix 6 Pro, Withings ScanWatch, and Fitbit Sense) against the clinical gold standard (electrocardiography). Results: All devices exhibited high correlation (r≥0.95; P<.001) and concordance (rc≥0.94) coefficients, with a relative error as low as mean absolute percentage error <5% based on 1630 valid measurements. We identified confounders significantly biasing the measurement accuracy, although not at clinically relevant levels (mean absolute error<5 beats per minute). Conclusions: Consumer-grade fitness trackers appear promising in hospitalized patients for monitoring heart rate.…
Autor(en): | Philipp Helmer, Sebastian Hottenrott, Philipp Rodemers, Robert Leppich, Maja Helwich, Rüdiger Pryss, Peter Kranke, Patrick MeybohmORCiD, Bernd E. Winkler, Michael Sammeth |
---|---|
URN: | urn:nbn:de:bvb:20-opus-299679 |
Dokumentart: | Artikel / Aufsatz in einer Zeitschrift |
Institute der Universität: | Fakultät für Mathematik und Informatik / Institut für Informatik |
Medizinische Fakultät / Klinik und Poliklinik für Anästhesiologie (ab 2004) | |
Medizinische Fakultät / Institut für Klinische Epidemiologie und Biometrie | |
Sprache der Veröffentlichung: | Englisch |
Titel des übergeordneten Werkes / der Zeitschrift (Englisch): | Journal of Medical Internet Research |
Erscheinungsjahr: | 2022 |
Band / Jahrgang: | 24 |
Heft / Ausgabe: | 12 |
Aufsatznummer: | e42359 |
Originalveröffentlichung / Quelle: | Journal of Medical Internet Research 2022, 24(12):e42359. DOI: 10.2196/42359 |
DOI: | https://doi.org/10.2196/42359 |
Allgemeine fachliche Zuordnung (DDC-Klassifikation): | 6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit |
Freie Schlagwort(e): | Apple Watch 7; Fitbit Sense; Garmin Fenix 6 Pro; Withings ScanWatch; health tracker; internet of things; personalized medicine; photoplethysmography; smartwatch; wearable |
Datum der Freischaltung: | 17.03.2023 |
Sammlungen: | Open-Access-Publikationsfonds / Förderzeitraum 2022 |
Lizenz (Deutsch): | CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International |