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 [Formula: see text]5 bpm in 3780 of 4079 (92.67%) and within ±13.4 bpm ([Formula: see text]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 [Formula: see text]5 bpm for 53,583 out of 57,048 beats (93.93%) and within [Formula: see text]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.
Keywords: Artificial intelligence; Machine learning; Palliative Care; Radar technology; Symptom management; Vital signs.
© 2024. The Author(s).