Evidence map›Paper›PMID 41942540›Full record

ArticleScientific data2026

An emotion recognition dataset using millimeter wave radar and physiological reference signals.

Jialong Cai, Xinyan Zhang, Yang Pan, Hui Zhou

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. 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. Article
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.

Jialong CaiSchool of Automation, Nanjing University of Science and Technology, Nanjing, China.
Xinyan ZhangDepartment of Rehabilitation, Nanjing Brain Hospital affiliated to Nanjing Medical University, Nanjing, China.
Yang PanDepartment of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Hui ZhouSchool of Automation, Nanjing University of Science and Technology, Nanjing, China. zhouhui@njust.edu.cn.ORCID 0000-0002-4900-4294

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We propose an emotion recognition dataset based on millimeter-wave (mmWave) radar and physiological reference signals. Compared to conventional methods, mmWave radar could obtain vital signs in a non-contact method without privacy concerns. We used validated stimuli to induce participants' emotions and simultaneously recorded three types of signals: mmWave signals, photoplethysmography (PPG) pulse signals, and galvanic skin response (GSR) signals. Participants used the Self-Assessment Manikin (SAM) to provide subjective emotion ratings. We collected signals and emotion rating data from 15 participants and validated the effectiveness of emotion induction and the data quality. The dataset can be used for research such as: (1) mmWave radar-based vital sign extraction; (2) comparison of emotion recognition performance across different signals; (3) multi-modal fusion for emotion recognition; (4) individual differences in emotional responses; (5) cross-subject emotion recognition, among others.

Indexed as

EmotionsRadarGalvanic Skin ResponseHumansManikinsPhotoplethysmography

Identifiers

PMID41942540
PMCPMC13230574

What OpenQuestion holds

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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.