Wearable sensor device-based detection of decreased heart rate variability in Parkinson’s disease

• Published in: Journal of Neural Transmission 2022-10, Vol.129 (10), p.1299-1306
• Main Authors: Suzuki, Masashi, Nakamura, Tomohiko, Hirayama, Masaaki, Ueda, Masamichi, Hatanaka, Mai, Harada, Yumiko, Nakatochi, Masahiro, Nakatsubo, Daisuke, Maesawa, Satoshi, Saito, Ryuta, Fujiwara, Koichi, Katsuno, Masahisa
• Format: Article
• Language: English
• Subjects: Medicine; Medicine & Public Health; Neurology; Neurology and Preclinical Neurological Studies - Original Article; Neurosciences; Psychiatry
• ISSN: 0300-9564; 1435-1463
• DOI: 10.1007/s00702-022-02528-y

The evidence that heart rate variability (HRV) decreases during early Parkinson's disease (PD) largely depends on electrocardiogram data. In this study, we examined HRV in PD using wearable sensors and assessed various evaluation methods for detecting disease-related alterations. We evaluated 27 patients with PD and 23 disease controls. The wearable sensors POLAR V800 HR and POLAR H10 were used for the HRV measurements. The participants wore the two sensors for approximately 24 h, and long-term HRV data were acquired. We analyzed the standard deviation of normal R-R intervals (SDNN) and coefficient of variation of R-R intervals (CVRR) for every 100 consecutive beats. Focusing on the fluctuation of SDNN and CVRR, we extracted the minimum, first decile, first quartile, and median values of SDNN and CVRR. The area under the receiver operating characteristic curve (AUC) for each HRV parameter was calculated to differentiate PD from the disease controls. The minimum values of SDNN and CVRR had the highest AUC (SDNN: AUC 0.90, 95% confidence interval [CI] 0.78–0.96; CVRR: AUC 0.90, CI 0.76–0.96) among the evaluation methods tested. The minimum values of SDNN and CVRR were significantly decreased in PD (SDNN: 9.5 ± 4.0 ms vs. 4.4 ± 2.0 ms, p