Methods for Wearable-Derived Pulse Rate Measures and Their Application to Modeling the Relationship between Pulse...

Area of Science:

• Neurology
• Cardiology
• Biomedical Engineering

Background:

• Narcolepsy type 1 (NT1) is a chronic neurological disorder resulting from orexin neuron loss, impacting sleep-wake cycles and potentially heart rate regulation.
• Wearable devices offer continuous physiological monitoring, but data quality challenges like artifacts and missing information must be addressed for clinical research utility.

Purpose of the Study:

• To develop robust methodologies for preprocessing wrist-worn smartwatch pulse rate data in clinical research settings.
• To investigate the association between pulse rate and motor activity in individuals with Narcolepsy type 1 using wearable data.

Main Methods:

• Collected 2-week baseline smartwatch (Empatica) pulse rate data from 110 participants with NT1 in a phase 2 clinical trial.
• Screened minute-level pulse rate data for artifacts and derived daily measures (24-h, daytime, nighttime averages).
• Quantified associations between pulse rate and motor activity using linear mixed-effects models, evaluating data stability with varying valid data proportions.

Main Results:

• Approximately 23.5% of epoch-level pulse rate data were invalid; a 70% valid daily data threshold yielded an average of 10.3 days of data per participant.
• Mean pulse rates were 72.8 (24-h), 83.3 (daytime), and 66.2 (nighttime) bpm; mean motor activity counts were 40.6 (24-h), 61.5 (daytime), and 10.3 (nighttime).
• Pulse rate showed a significant positive association with motor activity, explaining up to 80% of pulse rate variance.

Conclusions:

• A robust framework for preprocessing smartwatch pulse rate data was established for clinical research applications.
• Smartwatch data confirmed a significant positive association between pulse rate and motor activity in individuals with NT1 during the baseline period.