ArticleSensors (Basel, Switzerland)2021
Contactless Gait Assessment in Home-like Environments.
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 9 papers.
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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.
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Who cites it
9 citing papers in PubMed.
- Edge-AI Instrumentation Framework for Multimodal Biometric Sensing in Active Aging Environments.Sensors (Basel, Switzerland) · 2026Article
- Feasibility of Privacy-Preserving LiDAR-Based Continuous Gait and Activity Monitoring in Three People with Multiple Sclerosis: A Technical Proof-of-Concept Case Study.Sensors (Basel, Switzerland) · 2026Article
- A Reliability Study of Small, Portable, Easy-to-Use, and IMU-Based Sensors for Gait Assessment.Sensors (Basel, Switzerland) · 2025Article
- Unobtrusive measurement of gait parameters using seismographs: An observational study.Scientific reports · 2024Observational
- A Transferable Lidar-Based Method to Conduct Contactless Assessments of Gait Parameters in Diverse Home-like Environments.Sensors (Basel, Switzerland) · 2024Article
- Automatic Radar-Based Step Length Measurement in the Home for Older Adults Living with Frailty.Sensors (Basel, Switzerland) · 2024Article
- Probabilistic Estimation of Cadence and Walking Speed From Floor Vibrations.IEEE journal of translational engineering in health and medicine · 2024Article
- Development of an Open-source and Lightweight Sensor Recording Software System for Conducting Biomedical Research: Technical Report.JMIR formative research · 2023Article
- Monitoring Mobility at Home: The GAIT-HUB Sensor-Based Protocol for Remote Gait Analysis.Digital biomarkersArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Gait analysis is an important part of assessments for a variety of health conditions, specifically neurodegenerative diseases. Currently, most methods for gait assessment are based on manual scoring of certain tasks or restrictive technologies. We present an unobtrusive sensor system based on light detection and ranging sensor technology for use in home-like environments. In our evaluation, we compared six different gait parameters, based on recordings from 25 different people performing eight different walks each, resulting in 200 unique measurements. We compared the proposed sensor system against two state-of-the art technologies, a pressure mat and a set of inertial measurement unit sensors. In addition to test usability and long-term measurement, multi-hour recordings were conducted. Our evaluation showed very high correlation (r>0.95) with the gold standards across all assessed gait parameters except for cycle time (r=0.91). Similarly, the coefficient of determination was high (R2>0.9) for all gait parameters except cycle time. The highest correlation was achieved for stride length and velocity (r≥0.98,R2≥0.95). Furthermore, the multi-hour recordings did not show the systematic drift of measurements over time. Overall, the unobtrusive gait measurement system allows for contactless, highly accurate long- and short-term assessments of gait in home-like environments.
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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.