Evidence map›Paper›PMID 33192437›Full record

ArticleFrontiers in neurorobotics2020

A Smart Robotic Walker With Intelligent Close-Proximity Interaction Capabilities for Elderly Mobility Safety.

Xiaoyang Zhao, Zhi Zhu, Mingshan Liu, Chongyu Zhao, Yafei Zhao, Jia Pan, Zheng Wang, Chuan Wu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurorobotics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.2field-weighted citation impact, top 10% of its field
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

12 citing papers in PubMed, 51 citations in OpenAlex.

  1. Functions and Sensors of Smart Walkers From 2015 to 2024: Scoping Review.JMIR rehabilitation and assistive technologies · 2026
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  11. Multimodal fusion and human-robot interaction control of an intelligent robot.Frontiers in bioengineering and biotechnology · 2023
    Article
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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

8 authors at 3 institutions in 2 countries.

Xiaoyang ZhaoDepartment of Computer Science, Faculty of Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
Zhi ZhuDepartment of Computer Science, Faculty of Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
Mingshan LiuDepartment of Computer Science, Faculty of Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
Chongyu ZhaoDepartment of Computer Science, Faculty of Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
Yafei ZhaoDepartment of Mechanical Engineering, Faculty of Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
Jia PanDepartment of Computer Science, Faculty of Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
Zheng WangDepartment of Mechanical Engineering, Faculty of Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
Chuan WuDepartment of Computer Science, Faculty of Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
Hong Kong University of Science and Technology · HKUniversity of Hong Kong · HKSouthern University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The elderly population has rapidly increased in past years, bringing huge demands for elderly serving devices, especially for those with mobility impairment. Present assistant walkers designed for elderly users are primitive with limited user interactivity and intelligence. We propose a novel smart robotic walker that targets a convenient-to-use indoor walking aid for the elderly. The walker supports multiple modes of interactions through voice, gait or haptic touch, and allows intelligent control via learning-based methods to achieve mobility safety. Our design enables a flexible, initiative and reliable walker due to the following: (1) we take a hybrid approach by combining the conventional mobile robotic platform with the existing rollator design, to achieve a novel robotic system that fulfills expected functionalities; (2) our walker tracks users in front by detecting lower limb gait, while providing close-proximity walking safety support; (3) our walker can detect human intentions and predict emergency events, e.g., falling, by monitoring force pressure on a specially designed soft-robotic interface on the handle; (4) our walker performs reinforcement learning-based sound source localization to locate and navigate to the user based on his/her voice signals. Experiment results demonstrate the sturdy mechanical structure, the reliability of multiple novel interactions, and the efficiency of the intelligent control algorithms implemented. The demonstration video is available at: https://sites.google.com/view/smart-walker-hku.

Indexed as

coaxial front followingelderly safetyfalling protectionhuman-robot interactionintelligent controlsoft-robotic interfacesound source localization

Identifiers

PMID33192437
PMCPMC7642877
OpenAlexW3093871509

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.