ArticleSensors (Basel, Switzerland)2021
A Pilot Study to Validate a Wearable Inertial Sensor for Gait Assessment in Older Adults with Falls.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 23 citations in OpenAlex.
- Classification of fallers and non-fallers in older adults using electrical IMU signal for gait analysis and explainable deep learning.Scientific reports · 2026Article
- Wearable AI for on-device frailty assessment.Nature communications · 2025Article
- Economic Perspective of the Use of Wearables in Health Care: A Systematic Review.Mayo Clinic proceedings. Digital health · 2024Review
- A Computer Vision-Based System to Help Health Professionals to Apply Tests for Fall Risk Assessment.Sensors (Basel, Switzerland) · 2024Article
- Kinematic Analysis of Human Gait in Healthy Young Adults Using IMU Sensors: Exploring Relevant Machine Learning Features for Clinical Applications.Bioengineering (Basel, Switzerland) · 2024Article
- Navigating Through Innovation in Elderly's Health: A Scoping Review of Digital Health Interventions.Public health reviews · 2024Article
- Predictors of fall risk in older adults using the G-STRIDE inertial sensor: an observational multicenter case-control study.BMC geriatrics · 2023Observational
- Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor.Scientific reports · 2023Article
- Article
- The digital transformation of hepatology: The patient is logged in.Hepatology (Baltimore, Md.) · 2022Review
- Detecting Fall Risk and Frailty in Elders with Inertial Motion Sensors: A Survey of Significant Gait Parameters.Sensors (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The high prevalence of falls and the enormous impact they have on the elderly population is a cause for concern. We aimed to develop a walking-monitor gait pattern (G-STRIDE) for older adults based on a 6-axis inertial measurement (IMU) with the application of pedestrian dead reckoning algorithms and tested its structural and clinical validity. A cross-sectional case-control study was conducted with 21 participants (11 fallers and 10 non-fallers). We measured gait using an IMU attached to the foot while participants walked around different grounds (indoor flooring, outdoor floor, asphalt, etc.). The G-STRIDE consisted of a portable inertial device that monitored the gait pattern and a mobile app for telematic clinical analysis. G-STRIDE made it possible to measure gait parameters under normal living conditions when walking without assessing the patient in the outpatient clinic. Moreover, we verified concurrent validity with convectional outcome measures using intraclass correlation coefficients (ICCs) and analyzed the differences between participants. G-STRIDE showed high estimation accuracy for the walking speed of the elderly and good concurrent validity compared to conventional measures (ICC = 0.69;
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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.