This study used an experimental cross-sectional design to investigate frontal brain activity and physical activity during exergaming in younger and older adults. Data were collected at the NeXt Move Core Facility at the NTNU (Norwegian University of Science and Technology), Trondheim, Norway.

This study was approved by the Regional Ethical Committee for Medical and Health Research Ethics in Norway (2018/45) and was conducted in accordance with the Declaration of Helsinki. All participants provided informed, written consent before entering this study. Participant data were deidentified before analysis to ensure confidentiality and privacy. Participants did not receive financial compensation for participation. No images in this paper contain identifiable individuals.

The primary outcome measures were game performance score, movement characteristics, and frontal theta activity. Age group was included as a between-participant factor in the analysis.

Visual inspection of histograms and Q-Q plots, along with the Shapiro-Wilk test, indicated that all variables (game scores, step counts, movement, and EEG measures) were within a normal distribution, supporting the use of parametric analyses.

Means and SDs within each group were computed for demographic and physical activity variables. Group differences were examined using the Mann-Whitney U test. To examine the effects of difficulty level and age group on movement measures and frontal theta activity, repeated measures general linear models were used with difficulty level as a within-participant factor and age group as a between-participant factor. This approach accounts for within-participant dependency in repeated measurements in a balanced design. Sphericity assumptions were checked, and Greenhouse-Geisser corrections were applied where necessary. The significance level was set at P<.05.

Pearson correlation analyses were performed to explore associations between movement, step count, frontal theta EEG activity, and game performance scores. Correlations were computed for younger and older adults separately. To control for multiple comparisons, a Bonferroni correction was applied. In the present analysis, 18 correlations were performed, giving a corrected significance level of P>.003. Only correlations exceeding this corrected threshold were considered statistically significant. All statistical analyses were performed with IBM SPSS Statistics (version 30).

A total of 32 participants (16 younger and 16 older adults) completed this study. Descriptive statistics for participant characteristics are presented in Table 1. Both groups had equal sex distribution (8 women/8 men). Seven of the older adults had some previous experience with exergaming consoles, while all the younger adults had tried exergames before, mainly Wii Sports and EyeToy. None of the participants used exergames on a regular basis. Both the younger and the older adults reported similar levels of physical activity, being physically active 4-5 times per week for approximately 90 minutes per week with medium to high intensity.

The performance scores showed that younger adults significantly outperformed the older adults at all levels (Figure 4A). At the easy level, younger adults had a mean score of 175 (SD 19.7, range 134-201) points, while older adults had a mean score of 142 (SD 13.6, range 112-164; P<.001). Similar results were observed at the medium (175, SD 20.5, range 146-209, vs 138, SD 14.1, range 115-166, respectively) and hard (158, SD 20.7, range 119-190, vs 108, SD 18.7, range 62-134, respectively) levels (all P values <.001). There were significant effects of age group (F_1,30=46.57, P<.001, ηp²=0.61) and difficulty level (F_2,60=82.97, P<.001, ηp²=0.73), as well as a significant interaction between them (F_2,60=7.89, P<.001, ηp²=0.21).

Difficulty level affected the amount of movement (measured by VM) during gameplay for both younger and older adults (Figure 4B). There was a significant main effect of difficulty level on the amount of movement (F_2,58=6.690, P=.002, η²=0.187), indicating that movement amount decreased as game difficulty increased. In general, younger adults displayed more total body movement than older adults (F_1,29=7.931, P=.009, η²=0.215), particularly at the hard level. However, there was no significant interaction between difficulty level and age group (F_2,58=1.326, P=.274, η²=0.044).

For the total number of steps made during a gaming trial (n=29), there was no statistically significant main effect of game level on step count (F_2,54=2.655, P=.079, η²=0.090), although a trend toward fewer steps at higher difficulty levels was observed. There was also no significant main effect of age group (F_1,27=0.015, P=.902, η²=0.001), indicating similar overall step counts between younger and older adults. Furthermore, there was no significant interaction between age group and difficulty level (F_2,54=2.471, P=.094, η²=0.084), indicating that both younger and older adults showed similar patterns of step count across levels (Figure 4C).

Mean frontal theta values (n=21) were similar between younger adults (easy: 32.35, medium: 32.29, and hard: 33.15) and older adults (easy: 32.72, medium: 32.98, and hard: 32.99; Figure 4D). There was neither a significant main effect of game level on frontal theta activity across easy, medium, and hard conditions (F_2,38=1.96, P=.155, η²=0.094), nor a main effect of age group (F_1,19=0.04, P=.844, η²=0.002). Likewise, there was no interaction between difficulty level and age group (F_2,38=1.11, P=.340, η²=0.055).

The amount of movement (VM) during the game shows strong, positive correlations with game scores for both age groups and across all difficulty levels (range 0.67-0.80; Figure 5). Five of the 6 VM correlations remained statistically significant following Bonferroni correction (all P<.003), whereas the correlation at the hard level for older adults (r=0.67; P=.04) did not. For younger adults, the number of steps taken during the game shows moderate, positive correlations with game score across game levels (from easy to hard, r=0.59 to r=0.40; P=.03-.20). For older adults, number of steps shows moderate correlations with game score for the easy level (r=0.52; P=.04), with weaker correlations observed at the medium (r=0.35; P=.18) and hard (r=−0.13; P=.18) levels. None of the correlations between step count and game score remained statistically significant following Bonferroni correction (all P>.003). Frontal theta EEG showed near-0 associations in younger adults across all levels (from easy to hard, range 0.001 to −0.096; P=.86-.99). In older adults, correlations ranged from 0.35 to 0.76 (P=.02-.24). However, none of the correlations between game score and frontal theta activity remained significant following Bonferroni correction (all P>.003).

This laboratory-based experimental study set out to examine how game scores relate to the amount of movement performed and frontal theta activity during exergaming across different difficulty levels and age groups. The findings showed that the overall amount of movement was strongly and consistently associated with game scores across difficulty levels and age groups, whereas step count demonstrated weaker and less consistent relationships. In contrast, frontal theta activity showed neither statistically significant effects of difficulty level or age group nor a significant interaction between these factors, and exhibited only weak associations with game scores. Taken together, these results suggest that, in this exergame, game performance appears to primarily reflect the amount of movement performed in this specific task rather than cognitive-control demands as indexed by frontal theta activity. Consequently, game scores alone appear to have limited sensitivity to cognitive-control demands in the present exergame and under the specific task conditions investigated, especially if cognitive demands are not strongly or systematically manipulated.

Game scores are widely used as indicators of performance in exergaming and often function as the primary feedback mechanism for players and clinicians alike. Importantly, game scores reflect how well a player performs within a given set of task constraints, whereas game difficulty level represents a manipulation of those constraints intended to alter physical and cognitive demands [44]. Yet, their usefulness as proxies for physical activity and cognitive-control demands remains underexplored. In our study, game scores were strongly and consistently associated with the overall amount of movement across difficulty levels and age groups, whereas associations with step count were weaker and less consistent. In contrast, frontal theta activity showed no main effects of difficulty level or age group and exhibited only weak associations with game scores, particularly in younger adults. Collectively, these results indicate that, in this exergame, game scores primarily reflect quantitative aspects of movement (ie, how much participants move) rather than cognitive control–related neural engagement. This aligns with previous research showing that different exergame designs and training protocols can lead to distinct physical and cognitive outcomes [41].

This finding should be interpreted in light of previously reported participant experiences. Prior studies have shown that exergaming is perceived as both physically and cognitively demanding, requiring sustained attention and cognitive effort [39,40]. Motivation during gameplay is often driven by tracking progress and receiving rewards for performance, which reinforces engagement and supports skill development [43]. Game design that provides clear and meaningful feedback on progression and effort has been shown to strengthen the sense of mastery and enhance engagement [36,44]. However, the present results suggest a potential mismatch between subjective experiences of cognitive effort and what is actually captured by the scoring system. In the present exergame, game scores were more strongly associated with movement measures than with frontal theta activity, suggesting that they may not fully reflect all task demands experienced by players under the conditions investigated in this study.

The age-related differences observed in the correlation patterns further emphasize this concern. While frontal theta activity showed near-0 associations with game score in younger adults, older adults demonstrated small-to-moderate positive associations across difficulty levels. One possible interpretation is that older adults may rely more on cognitive-control processes to achieve higher scores, potentially as a compensatory strategy for age-related changes in physical or sensorimotor capacity. However, this interpretation should be treated with caution, as the present results do not provide direct support for this mechanism. In particular, the absence of clear differences in frontal theta activity across difficulty levels suggests that increased cognitive-control engagement in older adults was not consistently reflected in the EEG measure. An alternative explanation is that the observed associations may reflect differences in task strategy or efficiency rather than increased cognitive load per se. While previous literature suggests that older adults may show increased cognitive involvement during motor tasks [39], the current findings do not allow us to confirm such compensatory mechanisms within this specific exergame context.

From a rehabilitation and game design perspective, these findings underscore the need for caution when interpreting game scores as indicators of player performance and engagement. If feedback mechanisms such as scores do not scale with cognitive demand or task complexity, they may inadvertently favor low-effort strategies or obscure meaningful gains in cognitive engagement [35,45]. Consequently, reliance on game scores alone may limit the ability to tailor interventions effectively, particularly when cognitive training is an explicit therapeutic goal.

Rather than abandoning scoring systems altogether, the present findings point toward the potential value of integrating game scores into a broader, multidimensional feedback framework. Combining performance scores with objective measures of movement and cognitive activity could provide a more comprehensive representation of player engagement and support more individualized adjustment of difficulty and feedback [46]. Such an approach may help ensure that game scores reflect meaningful progress in both physical and cognitive domains, rather than superficial performance alone, thereby better supporting rehabilitation outcomes and sustained engagement.

The results of this study indicate a consistent association between the overall amount of movement (VM) and game score across difficulty levels, alongside a reduction in movement as game difficulty increased. This pattern suggests that, in this exergame, higher scores were largely achieved through greater movement output, reinforcing the notion that game performance is strongly driven by the amount of movement performed rather than cognitive demands. The observed decrease in movement at higher difficulty levels indicates that increasing task complexity, through obstacles or added game constraints, did not elicit a greater amount of movement but instead led to more restricted movement behavior. This finding is consistent with previous work showing that exergame design features, such as increased game speed or the addition of cognitively demanding elements, can alter movement strategies and, in some cases, reduce overall movement output [35,40].

From a rehabilitation perspective, this reduction in movement at higher difficulty levels warrants particular attention. One of the core advantages of exergames lies in their ability to promote high movement dosage through repeated, task‑oriented practice, which is essential for addressing musculoskeletal impairments and supporting functional recovery [20,21]. While increasing difficulty is often intended to enhance challenge and engagement, the present findings suggest that, if not carefully designed, higher difficulty levels may inadvertently constrain movement and undermine this key therapeutic benefit. Moreover, although game scores closely tracked movement quantity, especially in younger adults, step count alone showed weaker associations with performance. This highlights that step count may not adequately capture the complexity and quality of movement in exergames, which frequently involve multidirectional, reactive, and whole‑body actions rather than simple repetitive stepping.

A previous study demonstrated that tailoring game speed to individual player ability can enhance both physical activity and perceived exertion during exergaming [46]. This suggests that the movement patterns observed in this study may have been influenced by fixed difficulty levels that did not account for age-related differences in physical capacity. In the present data, older adults showed more steps at the medium level but fewer steps at the hard level compared with younger adults, despite similar reductions in movement magnitude across difficulty levels. Rather than reflecting differences in step length, this pattern likely indicates a shift toward more cautious or conservative movement strategies when task complexity increases. This is consistent with earlier findings showing that older adults adapt stepping behavior and reduce movement amplitude when exergame demands become more challenging [36,45]. Moreover, the overall decrease in movement at higher difficulty levels suggests that the added obstacles constrained rather than increased physical engagement, and that these elements may not provide the intended cognitive challenge, as frontal theta did not increase with difficulty. Together, these findings highlight the potential value of age‑adaptive and ability‑adaptive game design, which could better balance challenge and movement demands across user groups. Such an approach aligns with motor learning principles emphasizing task‑specific, variable, and sufficiently intense practice to support effective rehabilitation [63]. Hence, by adapting game parameters to individual capabilities, particularly in older adults, exergames may better support physical activity as well as therapeutic outcomes over time.

Beyond physical engagement, exergames are increasingly recognized for their cognitive benefits, particularly through dual-task elements that require attention, decision-making, and inhibition [14]. In our study, no statistically significant differences in mean frontal theta activity were detected between age groups or across difficulty levels, and associations with performance were generally weak or inconsistent. While older adults exhibited small-to-moderate correlations between frontal theta and game score at lower difficulty levels, a stronger association was observed at the greatest difficulty level. In younger adults, performance appeared to be largely independent of detectable changes in frontal theta.

Previous work has shown that frontal theta can increase during exergaming compared with performing similar movements without cognitive stimuli, and that such engagement can be sustained over time [64]. However, in this study, frontal theta did not vary with difficulty level, suggesting that the cognitive‑control demands imposed by the task may not have been sufficiently differentiated across levels. This interpretation is supported by recent reviews indicating that neural responses to exergaming, including frontal theta activity, vary considerably depending on task design and measurement approaches, and that evidence linking cognitive demand to neurophysiological measures remains limited and heterogeneous [37]. From this perspective, the weak associations observed between game score and frontal theta may reflect characteristics of the specific game design, limited differentiation of cognitive-control demands across difficulty levels, limitations of the measurement approach, or a combination of these factors.

The absence of frontal theta modulation across difficulty levels may also be understood in relation to our previous work using similar exergaming paradigms [35,48]. In those studies, task difficulty was primarily manipulated through changes in game speed, introducing continuous temporal pressure that likely increased sustained attention and cognitive-control demands. In contrast, the current study manipulated difficulty by adding task elements such as multiple targets and inhibitory components, while maintaining a similar overall task structure. This type of manipulation may increase task complexity without substantially altering the level of cognitive-control demand required during gameplay. Consequently, differences in how difficulty is operationalized, such as temporal pressure vs added task elements, may influence whether frontal theta activity is modulated.

Our findings suggest differences in exergame performance between the younger adults and the relatively active older adults included in this study. In particular, younger adults consistently outperformed older adults across all difficulty levels. This may reflect age-related differences in executive functions such as planning and inhibitory control, capacities known to decline with age due to structural and functional brain changes [65,66]. However, interpretations related to specific executive functions such as planning and inhibitory control should be treated with caution, as the present findings do not provide direct evidence that these processes were differentially engaged across task conditions. At the same time, the present findings should be interpreted as reflecting a comparison between younger adults and a relatively active, high-functioning group of community-dwelling older adults, rather than the broader older adult population. Both younger and older participants reported similar levels of weekly physical activity, which may partly reflect differences in how physical activity is perceived and reported across age groups, as well as the inclusion of a broader range of everyday activities among older adults. In addition, the older participants were recruited from recreational exercise groups, likely resulting in a sample with higher-than-average physical activity levels. As such, the present findings should be interpreted in the context of a relatively fit older population.

Physical activity has been shown to mitigate age-related declines in executive function [67,68], and exergaming may offer an added advantage by combining motor and cognitive stimulation in dynamic, unpredictable environments that require real-time decision-making and flexibility [30,69]. While younger adults may not show substantial cognitive benefits due to higher baseline abilities [70], older adults may benefit more from this combined approach. However, in the present study, increasing task difficulty was not associated with statistically significant increases in frontal theta activity. This is in line with previous findings suggesting that older adults do not necessarily exhibit increased frontal theta with added task difficulty [71]. As the different game levels were designed to vary cognitive-control demands through the addition of moving targets and inhibitory elements, the absence of frontal theta differences suggests either that these manipulations did not produce sufficiently differentiated levels of cognitive-control engagement or that frontal theta was not sensitive enough to detect such differences under the present conditions. The absence of clear frontal theta differences is therefore likely explained by a combination of factors. First, the cognitive demands of the exergame may not have been sufficiently distinct across difficulty levels, despite the inclusion of additional elements such as moving targets and inhibitory components. Second, frontal theta was analyzed as an average across entire gameplay trials. Cognitive demands during exergaming are likely intermittent, occurring during brief decision-making events and interspersed with periods dominated by motor execution, and averaging across the full task may therefore reduce sensitivity to transient increases in cognitive engagement. Together, these findings suggest that the observed pattern may reflect characteristics of the task design, the measurement approach, the limited sample size, and the relatively high functional level of the sample, rather than a true absence of cognitive involvement during gameplay.

This is one of very few studies to simultaneously assess movements and frontal theta EEG during exergaming in younger and older adults. However, this study has several limitations that should be acknowledged. First, the sample size was relatively small, which may limit the generalizability of the findings and the statistical power to detect small-to-moderate effects. This is particularly relevant for the EEG analyses, which were based on the subset of participants contributing to the frontal IC cluster. Consequently, nonsignificant findings should not be interpreted as evidence for the absence of age-related or task-related effects, but rather as findings that require confirmation in larger, adequately powered samples. In addition, a convenience sampling approach was used, and the older adults represented an active and high-functioning group. Future studies should therefore include larger and more diverse samples. Second, only a single exergame was examined, and different game designs may elicit different patterns of movements and frontal theta EEG. Future research should explore a broader range of game types and consider longitudinal designs to evaluate changes over time. Third, although extensive preprocessing procedures were applied to reduce movement-related contamination, EEG acquisition during dynamic exergaming remains methodologically challenging. Residual movement-related influences cannot be fully excluded and should be considered when interpreting neural measures obtained during whole-body movement tasks. Fourth, frontal theta was used as a proxy for cognitive-control demands. However, cognition comprises multiple processes that may not be fully captured by this measure alone. Although simplified EEG setups focused on frontal regions may increase feasibility in applied contexts, the present findings suggest that such approaches may require tasks with clearly differentiated cognitive-control demands to elicit meaningful variation. Fifth, frontal theta activity was analyzed as an average across entire gameplay trials. As cognitive demands during exergaming are likely intermittent and embedded within motor activity, this approach may reduce sensitivity to detect transient changes in cognitive engagement. Future studies may benefit from more temporally resolved analyses, including event-related approaches or the investigation of transient theta bursts, which may be better suited to detecting brief episodes of cognitive-control engagement during gameplay. Sixth, movement quality, such as coordination, accuracy, or balance control, was not assessed. Therefore, the extent to which game scores reflect qualitative aspects of movement remains unclear and should be addressed in future work. Finally, although repeated measures general linear models were appropriate for the balanced design used in this study, linear mixed-effects models provide a more flexible framework for modeling individual variability and repeated observations. Future studies with larger samples may benefit from applying such approaches. Overall, the interpretation of correlation strength should be approached with caution, as no universal standards exist, and the observed associations varied across measures and conditions [72].

This study provides novel insights into how game performance relates to movement and frontal theta EEG during step‑based exergaming across different age groups and difficulty levels. The amount of movement performed was strongly and consistently associated with game scores across difficulty levels and age groups, indicating that performance in this exergame primarily reflects the amount of movement performed in this task, while showing limited association with frontal theta activity under the present game conditions. In contrast, no statistically significant effects of difficulty level or age group were detected for frontal theta EEG, and associations with performance were generally weak or context-dependent. Together, these findings suggest that game scores in this task have limited sensitivity to cognitive-control processes under the present game conditions.

These results highlight the importance of carefully interpreting game performance as an indicator of engagement in exergaming. Reliance on game scores alone may provide an incomplete picture, particularly when cognitive training is an explicit goal. Instead, the findings support the use of multidimensional assessment approaches that integrate movement-based metrics with complementary indicators of cognitive involvement. By combining accelerometry and mobile EEG during whole-body exergaming, this study contributes to a growing but still limited body of research examining the interaction between movement and neurophysiological activity in dynamic, ecologically relevant tasks. Importantly, the results underscore that cognitive engagement should not be assumed based on task complexity alone but depends on how cognitive demands are operationalized within game design.

From a practical perspective, these findings suggest that exergame design should incorporate clearly differentiated and sufficiently challenging cognitive elements if the goal is to engage cognitive-control processes in addition to physical activity. Future research should extend these findings using larger and more diverse samples, as well as task designs that more effectively manipulate cognitive demand. Overall, this study provides a foundation for better understanding what exergame performance reflects and highlights the need for more nuanced approaches to measuring and designing engagement in digital rehabilitation.