Evidence map›Paper›PMID 34057423›Full record

ArticleJMIR serious games2021

User Experience With Dynamic Difficulty Adjustment Methods for an Affective Exergame: Comparative Laboratory-Based Study.

Ali Darzi, Sean M McCrea, Domen Novak

Abstract read
In one paragraph

Article in JMIR serious games, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. General Purpose Haptic/Biometric-Based Dynamic Difficulty Adjustment for Post-Stroke Upper-Limb Rehabilitation Games.IEEE ... International Conference on Rehabilitation Robotics : [proceedings] · 2025
    Article
  4. Article
  5. 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

3 authors.

Ali DarziDepartment of Electrical and Computer Engineering, University of Wyoming, Laramie, WY, United States.ORCID https://orcid.org/0000-0003-4529-9117
Sean M McCreaDepartment of Psychology, University of Wyoming, Laramie, WY, United States.ORCID https://orcid.org/0000-0003-4241-5530
Domen NovakDepartment of Electrical and Computer Engineering, University of Wyoming, Laramie, WY, United States.ORCID https://orcid.org/0000-0001-9143-2682

Funding

Wyoming INBRE Phase 4- Equipment Supplement for x-ray diffractometer for Center for Advanced Scientific InstrumentationP20GM103432 · NIGMS · UNIVERSITY OF WYOMING · PI Nicolas A. Blouin · 2012 to 2026
$56.8M
NIGMS NIH HHS P20 GM103432
6 · The paper itself

Abstract

backgroundIn affective exergames, game difficulty is dynamically adjusted to match the user's physical and psychological state. Such an adjustment is commonly made based on a combination of performance measures (eg, in-game scores) and physiological measurements, which provide insight into the player's psychological state. However, although many prototypes of affective games have been presented and many studies have shown that physiological measurements allow more accurate classification of the player's psychological state than performance measures, few studies have examined whether dynamic difficulty adjustment (DDA) based on physiological measurements (which requires additional sensors) results in a better user experience than performance-based DDA or manual difficulty adjustment.

objectiveThis study aims to compare five DDA methods in an affective exergame: manual (player-controlled), random, performance-based, personality-performance-based, and physiology-personality-performance-based (all-data).

methodsA total of 50 participants (N=50) were divided into five groups, corresponding to the five DDA methods. They played an exergame version of Pong for 18 minutes, starting at a medium difficulty; every 2 minutes, two game difficulty parameters (ball speed and paddle size) were adjusted using the participant's assigned DDA method. The DDA rules for the performance-based, personality-performance-based, and all-data groups were developed based on data from a previous open-loop study. Seven physiological responses were recorded throughout the sessions, and participants self-reported their preferred changes to difficulty every 2 minutes. After playing the game, participants reported their in-game experience using two questionnaires: the Intrinsic Motivation Inventory and the Flow Experience Measure.

resultsAlthough the all-data method resulted in the most accurate changes to ball speed and paddle size (defined as the percentage match between DDA choice and participants' preference), no significant differences between DDA methods were found on the Intrinsic Motivation Inventory and Flow Experience Measure. When the data from all four automated DDA methods were pooled together, the accuracy of changes in ball speed was significantly correlated with players' enjoyment (r=0.38) and pressure (r=0.43).

conclusionsAlthough our study is limited by the use of a between-subjects design and may not generalize to other exergame designs, the results do not currently support the inclusion of physiological measurements in affective exergames, as they did not result in an improved user experience. As the accuracy of difficulty changes is correlated with user experience, the results support the development of more effective DDA methods. However, they show that the inclusion of physiological measurements does not guarantee a better user experience even if it yields promising results in offline cross-validation.

Indexed as

affective computingdynamic difficulty adaptationexergamespersonality characteristicsphysiological measurementspsychophysiologytask performance

Identifiers

PMID34057423
PMCPMC8204235

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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.