Evidence map›Paper›PMID 36617030›Full record

ArticleSensors (Basel, Switzerland)2022

SoftSAR: The New Softer Side of Socially Assistive Robots-Soft Robotics with Social Human-Robot Interaction Skills.

Yu-Chen Sun, Meysam Effati, Hani E Naguib, Goldie Nejat

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. 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
0.4field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  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

4 authors at 1 institution in 1 country.

Yu-Chen SunAutonomous Systems and Biomechatronics Laboratory (ASBLab), Department of Mechanical & Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada.
Meysam EffatiAutonomous Systems and Biomechatronics Laboratory (ASBLab), Department of Mechanical & Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada.
Hani E NaguibToronto Smart Materials and Structures (TSMART), Department of Mechanical & Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada.
Goldie NejatAutonomous Systems and Biomechatronics Laboratory (ASBLab), Department of Mechanical & Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada.ORCID 0000-0002-7080-6857
University of Toronto · CA

Funding

Age-Well Inc. N/ACanada Research Chairs N/ANatural Sciences and Engineering Research Council N/A
6 · The paper itself

Abstract

When we think of "soft" in terms of socially assistive robots (SARs), it is mainly in reference to the soft outer shells of these robots, ranging from robotic teddy bears to furry robot pets. However, soft robotics is a promising field that has not yet been leveraged by SAR design. Soft robotics is the incorporation of smart materials to achieve biomimetic motions, active deformations, and responsive sensing. By utilizing these distinctive characteristics, a new type of SAR can be developed that has the potential to be safer to interact with, more flexible, and uniquely uses novel interaction modes (colors/shapes) to engage in a heighted human-robot interaction. In this perspective article, we coin this new collaborative research area as SoftSAR. We provide extensive discussions on just how soft robotics can be utilized to positively impact SARs, from their actuation mechanisms to the sensory designs, and how valuable they will be in informing future SAR design and applications. With extensive discussions on the fundamental mechanisms of soft robotic technologies, we outline a number of key SAR research areas that can benefit from using unique soft robotic mechanisms, which will result in the creation of the new field of SoftSAR.

Indexed as

RoboticsSmart MaterialsBiomimeticsHumansSmart Materialshuman–robot interactionsocially assistive robotssoft robotics

Identifiers

PMID36617030
PMCPMC9824785
OpenAlexW4313471539

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.