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https://doi.org/10.21256/zhaw-24219| Publikationstyp: | Working Paper – Gutachten – Studie |
| Titel: | Visualization and analysis of wearable health data from COVID-19 patients |
| Autor/-in: | Suter, Susanne Spinner, Georg Hoelz, Bianca Rey, Sofia Thanabalasingam, Sujeanthraa Eckstein, Jens Hirsch, Sven |
| et. al: | No |
| DOI: | 10.21256/zhaw-24219 |
| Umfang: | 17 |
| Erscheinungsdatum: | 19-Jan-2022 |
| Verlag / Hrsg. Institution: | arXiv |
| Andere Identifier: | arXiv:2201.07698 |
| Sprache: | Englisch |
| Schlagwörter: | Wearable vital sign; COVID-19 patient; Visualization |
| Fachgebiet (DDC): | 005: Computerprogrammierung, Programme und Daten 616: Innere Medizin und Krankheiten |
| Zusammenfassung: | Effective visualizations were evaluated to reveal relevant health patterns from multi-sensor real-time wearable devices that recorded vital signs from patients admitted to hospital with COVID-19. Furthermore, specific challenges associated with wearable health data visualizations, such as fluctuating data quality resulting from compliance problems, time needed to charge the device and technical problems are described. As a primary use case, we examined the detection and communication of relevant health patterns visible in the vital signs acquired by the technology. Customized heat maps and bar charts were used to specifically highlight medically relevant patterns in vital signs. A survey of two medical doctors, one clinical project manager and seven health data science researchers was conducted to evaluate the visualization methods. From a dataset of 84 hospitalized COVID-19 patients, we extracted one typical COVID-19 patient history and based on the visualizations showcased the health history of two noteworthy patients. The visualizations were shown to be effective, simple and intuitive in deducing the health status of patients. For clinical staff who are time-constrained and responsible for numerous patients, such visualization methods can be an effective tool to enable continuous acquisition and monitoring of patients' health statuses even remotely. |
| URI: | https://arxiv.org/abs/2201.07698 https://digitalcollection.zhaw.ch/handle/11475/24219 |
| Lizenz (gemäss Verlagsvertrag): | CC BY-NC-ND 4.0: Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International |
| Departement: | Life Sciences und Facility Management |
| Organisationseinheit: | Institut für Computational Life Sciences (ICLS) |
| Enthalten in den Sammlungen: | Publikationen Life Sciences und Facility Management |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2022_Suter-etal_Wearable-health-data-COVID19-patients.pdf | 1.4 MB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Suter, S., Spinner, G., Hoelz, B., Rey, S., Thanabalasingam, S., Eckstein, J., & Hirsch, S. (2022). Visualization and analysis of wearable health data from COVID-19 patients. arXiv. https://doi.org/10.21256/zhaw-24219
Suter, S. et al. (2022) Visualization and analysis of wearable health data from COVID-19 patients. arXiv. Available at: https://doi.org/10.21256/zhaw-24219.
S. Suter et al., “Visualization and analysis of wearable health data from COVID-19 patients,” arXiv, Jan. 2022. doi: 10.21256/zhaw-24219.
SUTER, Susanne, Georg SPINNER, Bianca HOELZ, Sofia REY, Sujeanthraa THANABALASINGAM, Jens ECKSTEIN und Sven HIRSCH, 2022. Visualization and analysis of wearable health data from COVID-19 patients [online]. arXiv. Verfügbar unter: https://arxiv.org/abs/2201.07698
Suter, Susanne, Georg Spinner, Bianca Hoelz, Sofia Rey, Sujeanthraa Thanabalasingam, Jens Eckstein, and Sven Hirsch. 2022. “Visualization and Analysis of Wearable Health Data from COVID-19 Patients.” arXiv. https://doi.org/10.21256/zhaw-24219.
Suter, Susanne, et al. Visualization and Analysis of Wearable Health Data from COVID-19 Patients. arXiv, 19 Jan. 2022, https://doi.org/10.21256/zhaw-24219.
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