Evidence map›Paper›PMID 33776207›Full record

ArticleJournal of intelligent & robotic systems2020

A 3D Computer Vision-Guided Robotic Companion for Non-Contact Human Assistance and Rehabilitation.

Tao Shen, Md Rayhan Afsar, He Zhang, Cang Ye, Xiangrong Shen

Abstract read
In one paragraph

Article in Journal of intelligent & robotic systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Tao ShenCollege of Aeronautics and Engineering, Kent State University.
Md Rayhan AfsarDepartment of Mechanical Engineering, The University of Alabama.
He ZhangCollege of Engineering, Virginia Commonwealth University.
Cang YeCollege of Engineering, Virginia Commonwealth University.
Xiangrong ShenDepartment of Mechanical Engineering, The University of Alabama.

Funding

NRI: Collaborative Research: Quadrupedal Human-Assistive Robotic Platform (Q-HARP)R01NR016151 · NINR · UNIVERSITY OF ALABAMA IN TUSCALOOSA · PI SHEN, XIANGRONG · 2015 to 2017
$1.0M
NINR NIH HHS R01 NR016151
6 · The paper itself

Abstract

With the rapid aging of the U.S. population, the mobility impairment is becoming a more and more challenging issue that affects a large number of individuals. The research presented in this paper aims at helping the mobility-challenged individuals with a novel robotic companion, which is a walker-type mobile robot capable of accompanying the human user and keeping user at the center for protection and possible power assistance. The robotic companion is equipped with a 3D computer vision system, which provides a unique capability of sensing the human-robot relative position/orientation without physical contact or the need for wearable sensors. As such, the robotic companion enables the user to walk freely with minimum disturbance to his/her normal gait, relieving the user from the physical and cognitive loads associated with the use of traditional assistive devices. For the development of the robotic companion, the authors designed and fabricated a low-cost, differentially steered mobile robotic platform, and also developed a unique image processing system to extract the position/orientation information from the 3D camera-captured images. Furthermore, an advanced motion control system was developed for the robotic companion, which provides novel solutions to the unique challenges such as sway reduction and noise reduction in digital differentiation. To quantify the performance, component and system-level experimentation was conducted, and the results demonstrated that robotic companion and its key components function as desired and the system is expected to reduce the user load and improve the user mobility in real-world scenarios.

Identifiers

PMID33776207
PMCPMC7990042

What OpenQuestion holds

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Registered trials

None linked

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.