ArticleWearable technologies2022
An algorithm to reduce human-robot interface compliance errors in posture estimation in wearable robots.
Article in Wearable technologies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis 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.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Use of Lower Limb Exoskeletons as an Assessment Tool for Human Motor Performance: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- A soft 3-DOF interaction force measurement system for estimating the biomechanical effects of a soft wearable robot on the human joint.Wearable technologies · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Assistive forces transmitted from wearable robots to the robot's users are often defined by controllers that rely on the accurate estimation of the human posture. The compliant nature of the human-robot interface can negatively affect the robot's ability to estimate the posture. In this article, we present a novel algorithm that uses machine learning to correct these errors in posture estimation. For that, we recorded motion capture data and robot performance data from a group of participants (
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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.