TUHH Open Research
Help
  • Log In
    New user? Click here to register.Have you forgotten your password?
  • English
  • Deutsch
  • Communities & Collections
  • Publications
  • Research Data
  • People
  • Institutions
  • Projects
  • Statistics
  1. Home
  2. TUHH
  3. Publications
  4. Contactless radar-based heart rate estimation in palliative care – a feasibility study and possible use in symptom management
 
Options

Contactless radar-based heart rate estimation in palliative care – a feasibility study and possible use in symptom management

Citation Link: https://doi.org/10.15480/882.14059
Publikationstyp
Journal Article
Date Issued
2024-11-30
Sprache
English
Author(s)
Grießhammer, Stefan  
Malessa, Anke  
Lu, Hui  
Hochfrequenztechnik E-3  
Yip, Julia Beatriz  
Leuschner, Julie
Christgau, Florian
Albrecht, Nils Christian  orcid-logo
Hochfrequenztechnik E-3  
Oesten, Marie  
Tran, Thanh Truc
Richer, Robert  
Heckel, Maria  
Eskofier, Björn  
Kölpin, Alexander  orcid-logo
Hochfrequenztechnik E-3  
Steigleder, Tobias  
Ostgathe, Christoph  
TORE-DOI
10.15480/882.14059
TORE-URI
https://hdl.handle.net/11420/52592
Journal
BMC palliative care  
Volume
23
Issue
1
Article Number
273
Citation
BMC Palliative Care 23 (1): 273 (2024)
Publisher DOI
10.1186/s12904-024-01592-3
Scopus ID
2-s2.0-85211117383
Publisher
BioMed Central
Background: Heart rate (HR) monitoring is a medical standard to provide information about a patient’s health status. In palliative care, relationship and social engagement are crucial therapeutic concepts. For fear of disrupting communication, social contact, and care, continuous HR monitoring is underutilised despite its potential to inform on symptom burden and therapeutic effects. This study investigates radar-based HR monitoring as an innovative and burden-free approach for palliative care patients, compares its accuracy with conventional ECG methods, and shows potential for therapeutic guidance. Methods: A single-centre, comparative clinical trial was conducted with palliative care patients at the ward of the Department of Palliative Medicine of the University Hospital of Erlangen. The HR measurements obtained with radar were compared with Holter ECG (study arm I, overnight) and Task Force® Monitor (TFM)-based ECG validation recordings (study arm II, one hour). In addition, long-term radar measurements without validation were analysed in comparison with clinical health records (study arm III). Results: Both validation methods showed correlation by scatter plot, modified Bland-Altman plot, and equivalence testing. N = 34 patients participated in study arm I. HR of 4,079 five-minute intervals was analysed. Radar measurements and ECG showed high agreement: difference of HRs was within 5 bpm in 3780 of 4079 (92.67%) and within ±13.4 bpm (1.96 times the SD of the mean) in 3979 (97.55%) intervals, respectively. In study arm II, n = 19 patients participated. 57,048 heart beats were analysed. The HR difference was within 5 bpm for 53,583 out of 57,048 beats (93.93%) and within 8.2 bpm (± 1.96 times the SD of the mean) in 55,439 beats (97.25%), respectively. Arm III showed HR changes extracted from radar data in correlation with symptoms and treatment. Conclusion: Radar-based HR monitoring shows a high agreement in comparison with ECG-based HR monitoring and thus offers an option for continuous and above all burden-free HR assessment, with the potential for use in symptom management in palliative care, among others. Further research and technological advancements are still necessary to fully realize this innovative approach in enhancing palliative care practices.
Subjects
Artificial intelligence | Machine learning | Palliative Care | Radar technology | Symptom management | Vital signs
MLE@TUHH
DDC Class
610: Medicine, Health
621.3: Electrical Engineering, Electronic Engineering
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by/4.0/
Loading...
Thumbnail Image
Name

s12904-024-01592-3.pdf

Type

Main Article

Size

2.95 MB

Format

Adobe PDF

TUHH
Weiterführende Links
  • Contact
  • Send Feedback
  • Cookie settings
  • Privacy policy
  • Impress
DSpace Software

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science
Design by effective webwork GmbH

  • Deutsche NationalbibliothekDeutsche Nationalbibliothek
  • ORCiD Member OrganizationORCiD Member Organization
  • DataCiteDataCite
  • Re3DataRe3Data
  • OpenDOAROpenDOAR
  • OpenAireOpenAire
  • BASE Bielefeld Academic Search EngineBASE Bielefeld Academic Search Engine
Feedback