BACKGROUND: Cardiac autonomic dysfunction is a prevalent yet underdiagnosed non-motor manifestation in Parkinson disease (PD), and difficult to monitor in daily life. Wrist-worn photoplethysmography (PPG) allows for continuous pulse rate monitoring, with potential to measure cardiac autonomic dysfunction in PD. However, motion artifacts pose significant challenges. We propose a two-step approach to account for PPG motion artifacts, and explore the association between pulse rate characteristics and cardiac autonomic dysfunction in PD. METHODS: In 444 people with early PD, we used continuous wrist PPG and accelerometer data, collected during two weeks using a one research-grade device model (Verily Study Watch), with an average wear time of 22 h/day. Step 1 filters low-quality segments based on PPG morphology using a logistic regression classifier. Step 2 removes remaining segments with periodic motion artifacts (e.g. introduced by tremor). Weekly aggregates were calculated for resting (daytime, nighttime) and maximum (daytime) pulse rates. We studied the effect of filtering on the pulse rate estimates and assessed the relationship between pulse rate aggregates and both subjective and objective autonomic dysfunction measures. RESULTS: Median proportion of high-quality PPG data was 29.2% [IQR: 24.0% to 35.9%] during the daytime, and 86.1% [IQR: 79.3% to 90.6%] during the night. Proportions of high-quality PPG data were similar across different rest tremor severity and dyskinesia scores. However, filtering out periodic motion artifacts (step 2) reduced overestimation of the maximum HR in persons with mild or severe rest tremor. More symptoms of autonomic dysfunction were associated with a lower maximum pulse rate(β:-0.17, 95% CI [-0.33, -0.00]), while resting pulse rate showed no association. No significant differences in pulse rate metrics were found between individuals with or without orthostatic hypotension. CONCLUSIONS: PPG-based heart rate estimation in PD improves when periodic motion artifacts are accommodated, representing an important step toward developing digital biomarkers of cardiac autonomic dysfunction. Maximum pulse rate in daily life only demonstrated a weak association with autonomic dysfunction, highlighting the need for more specific markers such as pulse rate variability.