ArticleMeasurement : journal of the International Measurement Confederation2022
Measuring Gait Parameters from Structural Vibrations.
Article in Measurement : journal of the International Measurement Confederation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 10 citations in OpenAlex.
- Probabilistic Estimation of Cadence and Walking Speed From Floor Vibrations.IEEE journal of translational engineering in health and medicine · 2024Article
- A Multi-Sensor Stochastic Energy-Based Vibro-Localization Technique with Byzantine Sensor Elimination.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Measuring gait parameters (e.g. speed, cadence, step duration) accurately is invaluable for evaluation during treatment of older adults who struggle with disability onset, disease progression, balance, and injurious falls. Traditionally stopwatches or timing gates are used to measure gait speed in clinical settings, and these are limited to measuring gait speed. Other wearable and non-wearable technologies offer the ability to measure additional gait parameters though patients are known to walk differently with the devices and even tend to slow down before engaging with a non-wearable such as a floor mat. Floor vibrations are a promising option to measuring gait parameters while not being intrusive and not requiring line-of-sight to the patient for measurements. This paper presents methodology for extracting gait parameters using vibrations with comparisons to APDM Wearable Technologies Mobility Lab sensors and stopwatch measurements. Performance is examined across 97 participants for self-selected speed forward, full speed forward, and backwards walks at three different testing sites for a total of 1039 walks. Gait speed vibrations measurements demonstrated excellent reliability with APDM Mobility Lab (ICC: 0.98; 99% CI: 0.01±0.01 m/s) and stopwatch (ICC: 0.97; 99% CI: -0.01±0.01 m/s) measurements. Similar excellent results are reported for cadence, gait cycle duration, step duration, and stride length parameters.
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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.