IEEE Transactions on Neural Systems and Rehabilitation EngineeringBioengineeringPeer-reviewed journal article
Continuous Monitoring of Head Turns: Compliance, Kinematics, and Reliability of Wearable Sensing
Abstract
Wearable devices offer objective mobility metrics for continuous monitoring but often focus on traditional measures like step count or gait speed. Other quantitative metrics such as head kinematics may provide valuable insights into mobility, balance, and sensory integration, given the heads central role in coordinating vestibular, ocular, and postural control. Yet, basic knowledge about capturing daily living head turns, including participant compliance, algorithms, normative data, and reliability, is not yet established. This study aimed to resolve this knowledge gap by capturing head and trunk movement kinematics over a 7-day period and to establish normative data in healthy adults. Participants (n = 24) wore head-mounted sensors for an average of 16.38 hours per day (SD = 4.43), completing 5,163 (SD = 1,466) head turns daily, with 72% occurring independently of trunk motion. Head turn amplitude (M = 58.18{degrees}, SD = 4.26{degrees}) was comparable to lumbar turns, while peak velocity was higher for head turns (M = 104.49{degrees}/s, SD = 12.08{degrees}/s). By the second day, all head turn metrics achieved excellent reliability (ICC > 0.9), supporting the feasibility of multi-day monitoring. Additionally, we examined the relationship between head motion and other mobility metrics and established recommendations for implementing similar protocols for capturing future studies, including the minimum number of days required for reliable data collection. Findings from this study provide a foundation for future multi-day continuous monitoring of head kinematics in both healthy and clinical populations.
- organism: human
- assay: imaging
- research focus: benchmarking
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- approach: experimental assay
- Citations
- 4
- FWCI
- 1.41
- Field percentile
- top 18%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Moving through everyday life: distinct developmental timescales for head-rotation magnitude and rotation efficiency in infancy
Zachary J. Petroff, Rajat Kapgate, … Kathryn Bonnen·bioRxiv·Aug 18, 2026
- Visual Motion Detection Thresholds Can Be Reliably Measured During Walking and Standing
Stephen J. DiBianca, John J. Jeka, Hendrik Reimann·Frontiers in Human NeurosciencePeer-reviewed·Nov 9, 2023
- Head engagement during visuomotor tracking is determined by postural demands and aging
Petros Georgiadis, Vassilia Hatzitaki, … Dimitris Voudouris·bioRxiv·Feb 19, 2025
- OpenSense: An open-source toolbox for Inertial-Measurement-Unit-based measurement of lower extremity kinematics over long durations
M. Al Borno, J. O'Day, … S. Delp·Journal of NeuroEngineering and RehabilitationPeer-reviewed·Feb 20, 2022
- Measuring Clinically Relevant Knee Motions With A Self-Calibrated Wearable Sensor
T. J. Hullfish, F. Qu, … J. R. Baxter·bioRxiv·May 10, 2018
- Accuracy and Reliability of a Suite of Digital Measures of Walking Generated Using a Wrist-worn Sensor: Performance Characterization Study
Nathan Kowahl, Sooyoon Shin, … Ritu Kapur·bioRxiv·Apr 21, 2023