Evidence map›Paper›PMID 42356663›Full record

ArticleSensors (Basel, Switzerland)2026

Electroencephalogram-Based Analysis of Monomodal and Multimodal Interaction in Mixed Reality Games.

Pratheep Kumar Paranthaman, Nikesh Bajaj, Logan LaMont

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. 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
–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

0 citing papers in PubMed.

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

3 authors.

Pratheep Kumar ParanthamanDepartment of Computer Science, Elon University, Elon, NC 27244, USA.ORCID 0000-0001-7791-1329
Nikesh BajajSchool of Physical and Chemical Sciences, Queen Mary University, London E1 4NS, UK.ORCID 0000-0002-3361-0118
Logan LaMontDepartment of Computer Science, Elon University, Elon, NC 27244, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mixed reality (MR) technologies enable users to experience computer-generated content within the physical environment through spatial computing and head-mounted displays. By supporting real-time interaction through speech, gesture, gaze, and movement, MR offers new opportunities for game design beyond productivity and educational applications. However, relatively few studies have examined interaction modalities in MR games. In this paper, we present the design and deployment of four MR games on the Microsoft HoloLens 2: three that use monomodal input (speech, gaze, or gesture) and one that uses multimodal input (speech, gaze, and gesture). We conducted a study with ten participants and evaluated player experience using subjective self-reports of task load, emotional engagement, and comfort alongside objective measures, namely brain activity data collected with a five-channel electroencephalogram (EEG) device. Our preliminary findings suggest two clusters of interaction modalities based on subjective measures, a pattern that is also reflected in the objective EEG measures. Our analysis combining subjective and EEG data indicates that interaction modality influences task load and emotional engagement. Additionally, our functional connectivity analysis showed links in activity across the prefrontal, temporal, and occipital brain regions for different input modalities in the MR games.

Indexed as

ElectroencephalographyVideo GamesAdultBrainFemaleGesturesHumansMaleSpeechUser-Computer InterfaceVirtual RealityEEG analysiselectroencephalogramextended reality gamesinteraction modalitiesmixed realityNASA task load indexplayer experienceSelf-Assessment Manikin

Identifiers

PMID42356663
PMCPMC13307432

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.