ArticleSensors (Basel, Switzerland)2020
A Wearable Sensor System to Measure Step-Based Gait Parameters for Parkinson's Disease Rehabilitation.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05605912 (Efficacy of the Myosuit for Increasing Daily Life Gait Performance in the Home and Community Setting and Gait Capacity in People With Incomplete Spinal Cord Injury), which is not on this map. Cited by 8 papers.
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.
Efficacy of the Myosuit for Increasing Daily Life Gait Performance in the Home and Community Setting and Gait Capacity in People With Incomplete Spinal Cord Injury
Who cites it
8 citing papers in PubMed.
- IMU-based gait analysis methods: a systematic review of techniques for different body locations.Frontiers in sports and active living · 2026Review
- Comparison of Wearable and Depth-Sensing Technologies with Electronic Walkway for Comprehensive Gait Analysis.Sensors (Basel, Switzerland) · 2025Article
- Automatic gait events detection with inertial measurement units: healthy subjects and moderate to severe impaired patients.Journal of neuroengineering and rehabilitation · 2024Article
- Agreement between Optoelectronic System and Wearable Sensors for the Evaluation of Gait Spatiotemporal Parameters in Progressive Supranuclear Palsy.Sensors (Basel, Switzerland) · 2023Article
- Motion Capture Technologies for Ergonomics: A Systematic Literature Review.Diagnostics (Basel, Switzerland) · 2023Review
- A Sensor-Based Perspective in Early-Stage Parkinson's Disease: Current State and the Need for Machine Learning Processes.Sensors (Basel, Switzerland) · 2022Article
- Wearable Inertial Gait Algorithms: Impact of Wear Location and Environment in Healthy and Parkinson's Populations.Sensors (Basel, Switzerland) · 2021Article
- Comparison of Subjective and Objective Assessments on Improvement in Gait Function after Carotid Endarterectomy.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Spatiotemporal parameters of gait serve as an important biomarker to monitor gait impairments as well as to develop rehabilitation systems. In this work, we developed a computationally-efficient algorithm (SDI-Step) that uses segmented double integration to calculate step length and step time from wearable inertial measurement units (IMUs) and assessed its ability to reliably and accurately measure spatiotemporal gait parameters. Two data sets that included simultaneous measurements from wearable sensors and from a laboratory-based system were used in the assessment. The first data set utilized IMU sensors and a GAITRite mat in our laboratory to monitor gait in fifteen participants: 9 young adults (YA
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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.