Evidence map›Paper›PMID 35627984›Full record

ArticleHealthcare (Basel, Switzerland)2022

Investigation of Methods to Create Future Multimodal Emotional Data for Robot Interactions in Patients with Schizophrenia: A Case Study.

Kyoko Osaka, Kazuyuki Matsumoto, Toshiya Akiyama, Ryuichi Tanioka, Feni Betriana, Yueren Zhao, Yoshihiro Kai, Misao Miyagawa, Tetsuya Tanioka, Rozzano C Locsin

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

10 authors at 6 institutions in 2 countries.

Kyoko OsakaDepartment of Psychiatric Nursing, Nursing Course of Kochi Medical School, Kochi University, Kochi 783-8505, Japan.
Kazuyuki MatsumotoGraduate School of Engineering, Tokushima University, Tokushima 770-8506, Japan.ORCID 0000-0002-9820-1470
Toshiya AkiyamaGraduate School of Health Sciences, Tokushima University, Tokushima 770-8509, Japan.
Ryuichi TaniokaGraduate School of Health Sciences, Tokushima University, Tokushima 770-8509, Japan.
Feni BetrianaGraduate School of Health Sciences, Tokushima University, Tokushima 770-8509, Japan.ORCID 0000-0002-8248-367X
Yueren ZhaoDepartment of Psychiatry, School of Medicine, Fujita Health University, Toyoake 470-1192, Japan.
Yoshihiro KaiDepartment of Mechanical Engineering, Tokai University, Tokyo 259-1292, Japan.
Misao MiyagawaDepartment of Nursing, Faculty of Health and Welfare, Tokushima Bunri University, Tokushima 770-8514, Japan.
Tetsuya TaniokaInstitute of Biomedical Sciences, Tokushima University, Tokushima 770-8509, Japan.ORCID 0000-0002-2847-1862
Rozzano C LocsinInstitute of Biomedical Sciences, Tokushima University, Tokushima 770-8509, Japan.
Tokushima University · JPFlorida Atlantic University · USFujita Health University · JPKōchi University · JPTokai University · JPTokushima Bunri University · JP

Funding

Japan Society for the Promotion of Science 17K17504
6 · The paper itself

Abstract

Rapid progress in humanoid robot investigations offers possibilities for improving the competencies of people with social disorders, although this improvement of humanoid robots remains unexplored for schizophrenic people. Methods for creating future multimodal emotional data for robot interactions were studied in this case study of a 40-year-old male patient with disorganized schizophrenia without comorbidities. The qualitative data included heart rate variability (HRV), video-audio recordings, and field notes. HRV, Haar cascade classifier (HCC), and Empath API

Indexed as

human–robot interactionmultimodal datamultimodal emotion recognitionschizophrenia

Identifiers

PMID35627984
PMCPMC9140390
OpenAlexW4229447666

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.