ArticleFrontiers in physiology2020
Wearable Inertial Measurement Units for Assessing Gait in Real-World Environments.
Article in Frontiers in physiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04702035 (Walking Pattern Characteristics in Normal Pressure Hydrocephalus. A Phase I/II Open-label Single Center Trial to Characterize Disease-specific Walking Patterns Using Wearable Gyroscopes), which is not on this map. Cited by 48 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Walking Pattern Characteristics in Normal Pressure Hydrocephalus. A Phase I/II Open-label Single Center Trial to Characterize Disease-specific Walking Patterns Using Wearable Gyroscopes
Who cites it
48 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pressure Sensors for Measuring Tibiofemoral Contact Mechanics in Meniscal Root Repair: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Physical Activity in Community-Dwelling Older Adults: Which Real-World Accelerometry Measures Are Robust? A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Artificial intelligence application versus physical therapist for squat evaluation: a randomized controlled trial.Scientific reports · 2021Trial
- Possible osteosarcopenia is associated with loss in intrinsic capacity and early cognitive deficits: a longitudinal study of older adults in Singapore.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026Article
- Article
- Perioperative real-life mobility assessment using wearable step counts in idiopathic normal pressure hydrocephalus after ventriculoperitoneal shunt surgery: a prospective pilot study.Neurosurgical review · 2026Article
- Wearable IMU-Derived Kinematic Reference Profiles of Lower-Limb Kick and Wipe Gestures for Contactless Automotive Tailgate Activation.Sensors (Basel, Switzerland) · 2026Article
- Parkinson's disease focused multimodal wearable vision based gait monitoring system with real time feedback to support mobility and caregiver well-being.Discover mental health · 2026Article
- Classification of fallers and non-fallers in older adults using electrical IMU signal for gait analysis and explainable deep learning.Scientific reports · 2026Article
- Comparison of 3D ankle kinematics between minimal inertial measurement units configuration and optical motion capture system under diverse walking conditions.Scientific reports · 2026Article
- Article
- Bridging the Methodological Gap Between Inertial Sensors and Optical Motion Capture: Deep Learning as the Path to Accurate Joint Kinematic Modelling Using Inertial Sensors.Sensors (Basel, Switzerland) · 2025Article
- Evaluation of the Validity and Reliability of NeuroSkin's Wearable Sensor Gait Analysis Device in Healthy Individuals.Bioengineering (Basel, Switzerland) · 2025Article
- Reduced Motor Individuality in Older Adults Revealed by Network-Based Gait Fingerprinting.Medicina (Kaunas, Lithuania) · 2025Article
- A Review of Gait Analysis Using Gyroscopes and Inertial Measurement Units.Sensors (Basel, Switzerland) · 2025Review
- Head kinematic variability is minimal near preferred cadence and independent of the vestibular control of locomotion.Scientific reports · 2025Article
- Predicting fall risk through step width variability at increased gait speed in community dwelling older adults.Scientific reports · 2025Article
- Gait Speed and Task Specificity in Predicting Lower-Limb Kinematics: A Deep Learning Approach Using Inertial Sensors.Mayo Clinic proceedings. Digital health · 2025Article
- Predicting community walking after stroke.Frontiers in stroke · 2025Article
- Validity of Wearable Inertial Sensors for Gait Analysis: A Systematic Review.Diagnostics (Basel, Switzerland) · 2024Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWalking patterns can provide important indications of a person's health status and be beneficial in the early diagnosis of individuals with a potential walking disorder. For appropriate gait analysis, it is critical that natural functional walking characteristics are captured, rather than those experienced in artificial or observed settings. To better understand the extent to which setting influences gait patterns, and particularly whether observation plays a varying role on subjects of different ages, the current study investigates to what extent people walk differently in lab versus real-world environments and whether age dependencies exist.
methodsThe walking patterns of 20 young and 20 elderly healthy subjects were recorded with five wearable inertial measurement units (ZurichMOVE sensors) attached to both ankles, both wrists and the chest. An automated detection process based on dynamic time warping was developed to efficiently identify the relevant sequences. From the ZurichMOVE recordings, 15 spatio-temporal gait parameters were extracted, analyzed and compared between motion patterns captured in a controlled lab environment (10 m walking test) and the non-controlled ecologically valid real-world environment (72 h recording) in both groups.
resultsSeveral parameters (
conclusionElderly test subjects walked differently in controlled lab settings compared to their real-world environments, which indicates the need to better understand natural walking patterns under ecologically valid conditions before clinically relevant conclusions can be drawn on a subject's functional status. Moreover, the greater inter-group differences in real-world environments seem promising regarding the sensitive identification of subjects with indications of a walking disorder.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.