SCIENTIFIC HUB

Follow the evidence.

SCIENTIFIC LITERATURE · MED

Implications of heart rate variability measured using wearable electrocardiogram devices in diagnosing Parkinson's disease and its association with neuroimaging biomarkers: a case-control study.

Front Aging Neurosci · 2025-05-12

DOI: 10.3389/fnagi.2025.1530240PMID: 40421102

Open accessresearch-article; Journal ArticleOriginal source ↗

Research overview

The text below is the source article’s original abstract under a verified reuse license. cc by

IntroductionHeart rate variability (HRV) reflects cardiac autonomic regulation, and reduced HRV is associated with Parkinson's disease (PD). However, studies regarding the implications of HRV measures for the clinical manifestations of PD have shown inconclusive results. We examined the relationship between HRV measures obtained via long-term monitoring using a wearable electrocardiogram (ECG) device and the diagnosis and clinical characteristics of PD.MethodsSeventeen controls and 20 patients with PD were prospectively enrolled. The HRV measures were recorded using a wearable ECG device for up to 72 h. Time- and frequency-domain measures were derived from the HRV analysis, and their association with PD diagnosis and clinical features was investigated. We investigated their association with neuroimaging biomarkers using magnetic resonance imaging to explore the underlying neural correlates.ResultsThe diagnosis of PD was associated with several HRV measures, including a decreased standard deviation of N-N intervals, standard deviation of all heart rates, and low-frequency (LF) power. Among these HRV measures, only LF power was associated with clinical features of PD. LF power was positively correlated with the tremor sub-score (r = 0.500; p = 0.035) and negatively associated with the left (r = -0.598; p = 0.024) and right (r = -0.693; p = 0.006) cerebellar hemispheres in patients with PD.ConclusionLow-frequency power may be used as a biomarker for tremor-associated pathophysiology of PD. Moreover, a wearable ECG device with its capability for long-term monitoring might be a promising tool for diagnosing PD.

Scientific assessment

01

Research question

Assess the question within the original study’s scope.

02

Methods & sample

Check the source article for study design and sample details.

03

Key findings

An editorially approved findings summary is not yet published for this record.

04

Limitations

Generalizability, bias and clinical meaning require separate assessment.

Methods, samples and clinical conclusions are not inferred from bibliographic metadata.