Evidence map›Paper›PMID 42879759›Full record

ArticleJMIR serious games2026

A Tangible Multimodal Sensing Interface for Collaborative Task Engagement in Children With Autism Spectrum Disorder: Cross-Sectional Mixed Methods Feasibility Study.

Won Kim, Chaeyeon Lim, Minwoo Seong, SeungJun Kim

Abstract read
In one paragraph

Article in JMIR serious games, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

4 authors.

Won Kim *Department of AI, Gwangju Institute of Science and Technology, Dasan Building 201, Cheomdangwagi-ro 123, Gwangju, 61005, Republic of Korea, 82 62 715 5352.ORCID http://orcid.org/0000-0001-6696-3756
Chaeyeon Lim *Department of AI, Gwangju Institute of Science and Technology, Dasan Building 201, Cheomdangwagi-ro 123, Gwangju, 61005, Republic of Korea, 82 62 715 5352.ORCID http://orcid.org/0009-0006-2334-8482
Minwoo SeongDepartment of AI, Gwangju Institute of Science and Technology, Dasan Building 201, Cheomdangwagi-ro 123, Gwangju, 61005, Republic of Korea, 82 62 715 5352.ORCID http://orcid.org/0009-0007-5847-9666
SeungJun KimDepartment of AI, Gwangju Institute of Science and Technology, Dasan Building 201, Cheomdangwagi-ro 123, Gwangju, 61005, Republic of Korea, 82 62 715 5352.ORCID http://orcid.org/0000-0003-0470-2483

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Social engagement is critical for the developmental progress of children with autism spectrum disorder (ASD). While tangible technologies and serious games (SGs) show promise, a dual-purpose platform that both facilitates collaborative interaction and enables sensing of collaborative task engagement is required. Existing tangible interfaces often lack integrated sensing capabilities, while devices designed for complex input are typically not optimized for the sensory and interaction needs of this population. Objective: This study aims to present InteractiSense, a tangible prototype designed to support collaborative play while enabling engagement estimation for children with ASD through embedded multimodal sensing. Our primary objectives were twofold: (1) to evaluate the prototype's preference, usability, and workload, and (2) to assess the feasibility of its embedded sensor data in generating valid inputs for preliminary machine learning (ML)-based engagement classification. Methods: We developed InteractiSense, a spherical, soft-textured prototype embedded with 7 physio-behavioral sensors, alongside a collaborative SG promoting key social skills, and evaluated it against a familiar Xbox controller as a practical baseline. Fifteen children with ASD (mean age 11, SD 3 years; 10 males and 5 females) participated in a cross-sectional feasibility evaluation using a within-subjects mixed methods design. Preference data were analyzed using the McNemar test and Bayesian analysis, and usability and workload scores were compared using 2-tailed paired Results: InteractiSense showed a tendency toward higher preference and comparable usability and workload metrics relative to the Xbox controller. Caregivers associated its round shape, soft texture, and simplified configuration with favorable perceptions and noted peer collaboration during the SG and interest in home use. Signal quality varied across sensing modalities: selected modalities provided analyzable data, whereas audio quality was low and pressure data were excluded from SNR and ML analyses. XGBoost achieved 83% (CI 0.76-0.90) balanced accuracy in binary engagement classification, exceeding random and majority-class baselines. Conclusions: These findings provide initial evidence that InteractiSense can serve as a dual-purpose platform supporting collaborative play and engagement-aware sensing within the same tangible interface. Unlike prior systems focused on either interaction support or separate monitoring, InteractiSense combines embedded multimodal sensing with a social play interface in one platform for children with ASD. This study offers a proof-of-concept for extending tangible play systems toward engagement-related sensing and inference, with implications for future therapeutic and educational tools that monitor play and support adaptive intervention. However, feasibility was shown only at a preliminary level, requiring validation in larger cohorts and over longer observation periods.

Indexed as

children with autism spectrum disordercollaborative and social serious gameengagementinteraction and sensing technologiesmachine learning

Identifiers

PMID42879759
PMCPMC13671684

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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.