Related Experiment Video
Updated: Jun 12, 2026
Multi-Modal Home Sleep Monitoring in Older Adults
Published on: January 26, 2019
Are parent-reported sleep logs essential? A comparison of three approaches to guide open source accelerometry-based
Sarah Burkart1, Michael W Beets1, Christopher D Pfledderer2,3
1Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
Insights
Children's sleep estimates from accelerometers differ slightly with or without a sleep log. Factors like screen time and weekend/summer nights influence these sleep data discrepancies.
Area of Science:
- Pediatric Sleep Medicine
- Biomedical Data Analysis
- Wearable Technology in Health
Background:
- Accurate measurement of children's sleep is crucial for health research.
- Accelerometers are widely used for objective sleep monitoring.
- The impact of using sleep logs versus algorithmic processing on accelerometer-derived sleep data in children is not fully understood.
Purpose of the Study:
- To compare children's nocturnal sleep estimates derived from accelerometry data processed with and without a sleep log.
- To identify factors associated with discrepancies in sleep estimates between these processing methods.
Main Methods:
- 722 children (aged 5-12 years) wore wrist-based accelerometers for 14 days.
- Sleep data were processed using parent-reported bed/wake times (sleep log) and an automated algorithm (no log).
- Comparisons included sleep period, duration, wake after sleep onset (WASO), and timing; discrepancies were analyzed using tobit regression.
Main Results:
- Sleep log processing resulted in longer sleep periods but shorter duration compared to the no-log approach.
- Significant differences were observed in WASO and sleep timing parameters between the two methods.
- Discrepancies were associated with smartphone ownership, bedroom screens, non-traditional parent work schedules, and data collected on weekend/summer nights.
Conclusions:
- While accelerometry provides objective sleep data, processing methods (with vs. without sleep logs) yield comparable, yet distinct, results in children.
- Factors such as technology use and non-standard sleep schedules contribute to variability in sleep estimates.
- Researchers should consider these factors when interpreting accelerometer-derived sleep data in pediatric populations.
Abstract:
We examined the comparability of children's nocturnal sleep estimates using accelerometry data, processed with and without a sleep log. In a secondary analysis, we evaluated factors associated with disagreement between processing approaches. Children (n = 722, age 5-12 years) wore a wrist-based accelerometer for 14 days during Autumn 2020, Spring 2021, and/or Summer 2021. Outcomes included sleep period, duration, wake after sleep onset (WASO), and timing (onset, midpoint, waketime). Parents completed surveys including children's nightly bed/wake time. Data were processed with parent-reported bed/wake time (sleep log), the Heuristic algorithm looking at Distribution of Change in Z-Angle (HDCZA) algorithm (no log), and an 8 p.m.-8 a.m. window (generic log) using the R-package 'GGIR' (version 2.6-4). Mean/absolute bias and limits of agreement were calculated and visualised with Bland-Altman plots. Associations between child, home, and survey characteristics and disagreement were examined with tobit regression. Just over half of nights demonstrated no difference in sleep period between sleep log and no log approaches. Among all nights, the sleep log approach produced longer sleep periods (9.3 min; absolute mean bias [AMB] = 28.0 min), shorter duration (1.4 min; AMB = 14.0 min), greater WASO (11.0 min; AMB = 15.4 min), and earlier onset (13.4 min; AMB = 17.4 min), midpoint (8.8 min; AMB = 15.3 min), and waketime (3.9 min; AMB = 14.8 min) than no log. Factors associated with discrepancies included smartphone ownership, bedroom screens, nontraditional parent work schedule, and completion on weekend/summer nights (range = 0.4-10.2 min). The generic log resulted in greater AMB among sleep outcomes. Small mean differences were observed between nights with and without a sleep log. Discrepancies existed on weekends, in summer, and for children with smartphones and screens in the bedroom.
