| Title: | Daily-Life Walking Speed, Quality and Quantity Derived from a Wrist Motion Sensor: Large-Scale Normative Data for Middle-Aged and Older Adults |
| Journal: | Sensors |
| Published: | 10 Aug 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39204870/ |
| DOI: | https://doi.org/10.3390/s24165159 |
| URL: | http://dx.doi.org/10.3390/s24165159 |
Publication 12986
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Abstract
Walking is crucial for independence and quality of life. This study leverages wrist-worn sensor data from UK Biobank participants to establish normative daily-life walking data, stratified by age and sex, to provide benchmarks for research and clinical practice. The Watch Walk digital biomarkers were developed, validated, and applied to 92,022 participants aged 45-79 who wore a wrist sensor for at least three days. Normative data were collected for daily-life walking speed, step-time variability, step count, and 17 other gait and sleep biomarkers. Test-retest reliability was calculated, and associations with sex, age, self-reported walking pace, and mobility problems were examined. Population mean maximal and usual walking speeds were 1.49 and 1.15 m/s, respectively. The daily step count was 7749 steps, and step regularity was 65%. Women walked more regularly but slower than men. Walking speed, step count, longest walk duration, and step regularity decreased with age. Walking speed is associated with sex, age, self-reported pace, and mobility problems. Test-retest reliability was good to excellent (ICC ≥ 0.80). This study provides large-scale normative data and benchmarks for wrist-sensor-derived digital gait and sleep biomarkers from real-world data for future research and clinical applications.</p>
12 Keywords
- Aged
- Female
- Gait
- Humans
- Male
- Middle Aged
- Quality of Life
- Reproducibility of Results
- Walking
- Walking Speed
- Wearable Electronic Devices
- Wrist
3 Authors
- Lloyd L. Y. Chan
- Stephen R. Lord
- Matthew A. Brodie
1 Application
| Application ID | Title |
|---|---|
| 56109 | Prognostic value of movement quality parameters derived from wrist sensor data in a large population |
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