Methods for Wearable-Derived Pulse Rate Measures and Their Application to Modeling the Relationship Between Pulse Rate and Motor Activity in Narcolepsy Type 1

Introduction: Narcolepsy type 1 (NT1) is a chronic, rare neurological disorder caused by loss of orexin neurons that disrupts the sleep-wake cycle. Current research suggests a link between orexin neuropeptide deficiency and heart rate regulation. Wrist-worn devices enable continuous monitoring of physiological data, including heart rate. We aim to effectively utilize wearables in clinical research by developing robust methodologies to address challenges including data artifacts and missing data. Methods: Empatica wrist-worn smartwatch data were collected for 2 weeks at baseline in the TAK-861-2001 randomized, phase 2 clinical trial (NCT05687903) from participants with NT1. Epoch-level (minute-level) pulse rate data were rigorously screened for artifacts. Daily pulse rate measures (24-h, daytime, and nighttime averages) were derived. Numerical experiments were conducted to evaluate the stability of daily measures as a function of the proportion of valid minute-level data within a given day. Mean pulse rate and motor activity daily measures and the association between the two were quantified using linear mixed-effects models. Results: Participants (n=110) had a mean age of 34.0 years and 51.8% were female. Approximately 23.5% of the epoch-level pulse rate observations were invalid due to non-wear, missing data, or artifacts. With a ≥70% threshold for valid daily wearable data, participants contributed an average of 10.3 days of data. Mean pulse rates were 72.8, 83.3, and 66.2 beats per minute and mean motor activities were 40.6, 61.5, and 10.3 epoch-level Activity Counts for 24-h, daytime, and nighttime averages, respectively. Pulse rate was significantly positively associated with motor activity daily measures, with up to 80% of pulse rate variance explained by motor activity levels and individual differences in baseline pulse rate and pulse rate-motor activity association. Conclusion: This work proposes a robust framework for preprocessing smartwatch pulse rate data for analyses in clinical research. The findings from our smartwatch data demonstrate a significant positive associateion between pulse rate and motor activity in participants with NT1 during a 2-week baseline period.

Publication Details

Journal
Digital Biomarkers
Published
2026-03-24
DOI
https://doi.org/10.1159/000551257
Primary Topic
Sleep and Wakefulness Research
Type
article
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article

Methods for Wearable-Derived Pulse Rate Measures and Their Application to Modeling the Relationship Between Pulse Rate and Motor Activity in Narcolepsy Type 1

Digital Biomarkers
Sleep and Wakefulness Research
article

Methods for Wearable-Derived Pulse Rate Measures and Their Application to Modeling the Relationship Between Pulse Rate and Motor Activity in Narcolepsy Type 1

article en

Abstract

Introduction: Narcolepsy type 1 (NT1) is a chronic, rare neurological disorder caused by loss of orexin neurons that disrupts the sleep-wake cycle. Current research suggests a link between orexin neuropeptide deficiency and heart rate regulation. Wrist-worn devices enable continuous monitoring of physiological data, including heart rate. We aim to effectively utilize wearables in clinical research by developing robust methodologies to address challenges including data artifacts and missing data. Methods: Empatica wrist-worn smartwatch data were collected for 2 weeks at baseline in the TAK-861-2001 randomized, phase 2 clinical trial (NCT05687903) from participants with NT1. Epoch-level (minute-level) pulse rate data were rigorously screened for artifacts. Daily pulse rate measures (24-h, daytime, and nighttime averages) were derived. Numerical experiments were conducted to evaluate the stability of daily measures as a function of the proportion of valid minute-level data within a given day. Mean pulse rate and motor activity daily measures and the association between the two were quantified using linear mixed-effects models. Results: Participants (n=110) had a mean age of 34.0 years and 51.8% were female. Approximately 23.5% of the epoch-level pulse rate observations were invalid due to non-wear, missing data, or artifacts. With a ≥70% threshold for valid daily wearable data, participants contributed an average of 10.3 days of data. Mean pulse rates were 72.8, 83.3, and 66.2 beats per minute and mean motor activities were 40.6, 61.5, and 10.3 epoch-level Activity Counts for 24-h, daytime, and nighttime averages, respectively. Pulse rate was significantly positively associated with motor activity daily measures, with up to 80% of pulse rate variance explained by motor activity levels and individual differences in baseline pulse rate and pulse rate-motor activity association. Conclusion: This work proposes a robust framework for preprocessing smartwatch pulse rate data for analyses in clinical research. The findings from our smartwatch data demonstrate a significant positive associateion between pulse rate and motor activity in participants with NT1 during a 2-week baseline period.

Digital Biomarkers
Openalex Percentile: Top 14%
Sleep and Wakefulness Research
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Methods for Wearable-Derived Pulse Rate Measures and Their Application to Modeling the Relationship Between Pulse Rate and Motor Activity in Narcolepsy Type 1 · Digital Biomarkers (2026) | TGRS Research Map | TGRS