This study adopts a qualitative case study approach to explore how XR technologies can support the detection of fatigue-related symptoms in children with brain injuries. As defined by Yin [27], case studies investigate contemporary phenomena in real-life contexts, especially when the boundaries between the phenomenon and the context are not clearly evident. This method is well-suited for addressing “how” and “why” questions, such as how specific gamification and XR design elements facilitate or hinder engagement and effective fatigue response during at-home rehabilitation for a child with a brain injury. A single qualitative case study was selected because it enables a deep, contextual understanding of how a child’s engagement with XR motor rehabilitation fluctuates with fatigue, and what type of content supports engagement during use of the solution. Direct feedback from children immediately after XR solution trial sessions, along with observations and discussions with clinical teams and parents, provided rich data to enhance understanding of the phenomena related to the research question. Co-design with the child, parents, and the clinical team translated these insights into tailored, engaging content and fatigue-aware adaptations (eg, dynamic difficulty adjustment, micro-breaks, and session pacing) to optimize usability and adherence. The prototype was developed as a motor rehabilitation support tool intended to increase engagement and provide a structured, safe, home-like training experience. Although fatigue detection was discussed during the workshops, this study did not aim to validate automated fatigue detection. Instead, fatigue was treated as a design constraint, explored through stakeholder feedback and clinician-observed behaviors during short sessions.

The case centers on co-developing an XR rehabilitation solution with clinicians (eg, physical and occupational therapists), children with ABIs, and their parents. Data collection involved 25 participants, including members of the clinical rehabilitation team, children with ABI, and their parents (Figure 1). Multiple data sources—including workshops, interviews, observations, and the Engagement Scale and Virtual and Mixed Reality Fatigue Scale (VMRFS) surveys (see Multimedia Appendix 1)—provided deep insights into user needs and therapeutic impact. Following Yin’s [27] principles—clear case boundaries, multiple sources of evidence, and a maintained chain of evidence—the study used an iterative, reflective process to inform design decisions, ensuring that the solution is engaging, clinically grounded, and responsive to real-world needs. The study results were reported in accordance with Journal Article Reporting Standards [28].

The research team combined complementary expertise: EK led data collection and analysis, supported by NP’s contributions to study design and workshop facilitation, and AKSC’s assistance with data collection. Clinical partners IKHR, ÅB, NSM, and KGSO contributed to patient recruitment, provided clinical insight, and reviewed the manuscript. Senior academics—PG, SS, and the lead supervisor, MP—strengthened the methodological and scientific quality of the study, with MP overseeing study conception, ethics, project coordination, and consolidation of the manuscript for publication.

Participants were recruited through collaboration with the Norwegian Municipality, Norwegian hospitals, and researcher networks (healthy children) using purposive sampling [29]. XR generally benefits from age-appropriate design; however, in pediatric brain injury rehabilitation, adaptation based on functional capacity and fatigue was prioritized over chronological age in this study. Purposive sampling was used to recruit participants who could provide information-rich insights relevant to the study’s aims, specifically (1) children with ABI who represented typical rehabilitation cases in terms of functional variability and fatigue patterns; (2) clinicians with direct experience treating such children; and (3) healthy children who could contribute to early-stage usability and interaction design. This approach ensured diversity in functional abilities, therapeutic roles, and user perspectives, rather than diversity in demographic characteristics such as chronological age.

A description of participant recruitment is provided in the participant flow diagram (see Multimedia Appendix 2). Overall, 25 individuals—healthy children, clinicians, and children with ABI—were contacted about the study. In total, 22 participants provided consented data: 10 healthy children (ideation phase), 4 children with ABI, 4 parents, and 4 clinicians. Data collection proceeded in 3 stages: (1) an early ideation workshop with healthy children and initial clinician interviews; (2) iterative co-design and playtesting workshops with children with ABI, parents, and clinicians; and (3) follow-up clinician interviews after the final iteration.

The first phase of the study included a workshop with 10 healthy children aged 9-16, followed by a meeting with 6 clinicians and individual interviews with 3 clinicians who had hands-on expertise in the rehabilitation of children with ABI. The first workshop was conducted as part of the OsloMet Design for Experience course. This workshop aimed to gain a general understanding of preferences for rehabilitation games among children in this age group. In total, 10 healthy children aged 9-16 participated in the workshop. Six different design student groups (4-6 students in each group) created paper prototypes of potential rehabilitation games. The children were asked to evaluate these early concepts and provide open feedback. During the sessions, the research team conducted observations and took notes on the children’s excitement and reactions to the different design concepts. These observations served as a baseline for selecting 3 initial design concepts for further discussion with the clinical team.

The next step in the research process was to conduct a focus group discussion with clinicians working with children with ABI to better understand the rehabilitation status and needs of this population, as well as to gather feedback on their preferences regarding the preliminary design ideas and generate initial concepts for the XR solution. However, only 4 of the 6 clinicians who participated in the focus group discussion and 2 of the 3 clinicians who participated in the individual interviews provided consent for data usage. Consequently, only the consented data were included in the formal analysis. Data from the remaining 4 clinicians were used as background input to inform the development of the initial XR design concepts, but were not included in the analyzed dataset.

The next phase of the study (4 workshops) included 4 children with ABI (3 participated with their parents and 1 with an assistant), aged 9-16, and clinicians (including occupational and physical therapists) with rehabilitation experience. The focused objective of the workshops was to explore stakeholder perceptions (specifically concerns and opportunities related to XR-based rehabilitation), understand how fatigue and engagement were experienced during and after XR sessions, and identify how the XR solution should be adapted to preserve engagement while accounting for fatigue. In this study, fatigue-related cues referred to clinician-observed, naturally occurring behavioral changes during interaction, such as reduced responsiveness, slowed reaction time, reduced movement amplitude, changes in posture, gaze disengagement, or an increased need for prompts. These cues were used to inform interpretation of engagement and to guide fatigue-aware design decisions (eg, session length, breaks, and sensory load). Observations were documented through field notes, workshop video review, and clinician reflections. Fatigue was not induced; sessions were kept short and supervised by the clinical team, and activities were paused if clinicians or caregivers determined that the child needed a break. No specialized technical training was required to identify these cues; however, clinicians’ familiarity with pediatric ABI strengthened the contextual interpretation.

The solution was intended to be engaging while supporting motor rehabilitation and facilitating responses to fatigue-related symptoms in children with brain injuries. After the fourth workshop, 3 additional individual interviews were conducted with the same clinical team members who had participated in all workshops. The purpose of these interviews was to gain a deeper understanding of their perspectives on opportunities and concerns, fatigue and engagement during XR sessions, and XR design elements needed to preserve treatment goals while accounting for fatigue.

The study prioritized the collection of actionable insights to guide iterative refinement of XR prototypes rather than aiming for exhaustive thematic saturation. Accordingly, a small, purposefully selected sample was considered methodologically appropriate. Clinicians were selected based on their direct practical experience in pediatric ABI rehabilitation, including occupational and physical therapists and a pediatric neurologist involved in home- and outpatient-based care. Children with ABI were purposively selected to reflect diversity in age (8-16 years), type and cause of injury (eg, stroke, traumatic brain injury), functional abilities, and observed fatigue characteristics, while still being able to safely participate in XR-supported motor activities. Parents were included, when appropriate, to provide complementary perspectives on fatigue and engagement in the home rehabilitation context. In the early ideation phase, healthy children were intentionally recruited as proxy users to explore general gameplay preferences and interaction concepts before involving children with ABI, thereby reducing participant burden and informing initial design decisions. This sampling strategy supported the study’s iterative co-design process and the development of fatigue-sensitive XR design insights.

The approach aligns with rapid prototyping methodologies, which emphasize the value of targeted feedback to inform design decisions rather than comprehensive theme development [30]. The study also adhered to participatory research principles by engaging a representative sample of end users, including clinicians whose perspectives are critical to the intervention’s relevance and usability. Furthermore, the total sample size (10 healthy children, 4 children with ABI, 4 parents, and 7 clinicians, comprising a total of 25 participants) falls within the range recommended by Creswell and Miller [31] for phenomenological inquiry, which suggests between 5 and 25 participants. Data collection involved workshops, interviews, observations, and surveys to support triangulation and ensure rich, contextual insight into the design, use, and evaluation of the XR rehabilitation prototype, as shown in Table 1.

Semistructured interviews were conducted with 5 clinicians—physical therapists, occupational therapists, and a pediatric neurologist—experienced in pediatric brain injury rehabilitation. These clinicians provided insights into the behavioral presentation of fatigue, motivational challenges, and design features to enhance engagement and outcomes. The interviews (guide in Multimedia Appendix 3), lasting 45-90 minutes, followed a structured protocol covering rehabilitation practices, XR technology, and digital tools. Audio recordings were transcribed and thematically analyzed to inform XR prototype design. Co-design workshops were conducted with 2 key user groups: health care professionals and children with ABIs (or, in the first workshop, healthy children as proxies), as shown in Table 2, which summarizes their profiles, including age, diagnosis, and session involvement. “Quality” indicates the research team’s perceived utility of each data source for answering the research questions (+++ high; ++ moderate), based on triangulation potential and richness of the data.

The workshops had dual purposes: to collaboratively generate design ideas (early phase) and to collect feedback on different versions of the XR prototype. Co-design principles guided the development of the XR prototype through iterative workshops with children, parents, and therapists (see Table 3). Their contributions informed key design decisions, such as the inclusion of adaptive challenge mechanics, consideration of fatigue situations, natural rest prompts, and personalized rewards based on user interests.

Each workshop session lasted approximately 120-180 minutes and included guided playtesting with the prototype, participant feedback through discussions and questionnaires, and follow-up discussions with the clinical team. The sessions were audio- and video-recorded, and postsession feedback was also documented through informal discussions and field notes. These workshops enabled iterative integration of feedback and supported the co-creation of features addressing user fatigue, safety, and engagement. Four children with varying types of ABIs participated across different workshops. Observations captured user interaction, task navigation, responses to feedback, and fatigue-related behaviors (eg, posture changes, slowed reaction time, disengagement). A structured protocol guided interviews conducted with the children after each session, supporting triangulation with other data sources. Participants who took part in the interviews and provided consent are shown in Table 4. To assess engagement and fatigue, 2 instruments were used: a simplified User Engagement Scale (UES) [32] and an adapted VMRFS [33]. The UES measured attention, usability, aesthetics, and reward, adjusted for pediatric cognitive levels (see Multimedia Appendix 1 for the scales used). The VMRFS assessed visual discomfort, cognitive strain, and physical fatigue. Both instruments were used qualitatively: each child with ABI was narratively guided through rating the prototype using the UES and VMRFS immediately after the session. These discussions were audio-recorded, transcribed, and analyzed alongside other qualitative data to identify patterns in motivation, usability, and fatigue. The instruments were administered in a simplified, interview-supported format appropriate for children. Items were used to prompt reflection on comfort, strain, and engagement and were analyzed qualitatively alongside interviews and observations, rather than as standalone quantitative outcome measures.

Data analysis followed Braun and Clarke’s [34] 6-phase thematic analysis framework. The process began with familiarization through transcription and repeated readings of the data. Initial codes were generated to capture key features related to fatigue, motivation, and engagement. These codes were then organized into broader themes, which were reviewed and refined to ensure coherence and accuracy. The final phase involved producing the report, supported by illustrative quotes and linked to relevant theoretical frameworks, including the UES [32] and Cognitive Load Theory [35]. Analysis was conducted first for the individual interviews and then iteratively extended to the workshop data. Given the small sample size and the risk of deductive identification, quotes are attributed by stakeholder group only.

This study ensured methodological integrity by drawing on diverse data sources—including interviews, co-design workshops, observations, interaction videos, and postsession engagement and fatigue scales—that captured the perspectives of children with ABI, parents, clinicians, and healthy children relevant to the study aims. Researcher influence was managed through reflexive practices such as memo writing, field notes, and supervisory discussions, and interviews were conducted using open-ended prompts to minimize bias. Reflective thematic analysis grounded the findings in the data, supported by direct quotes, behavioral descriptions, and triangulation across sources. Apparent contradictions—such as low self-reported fatigue despite observable fatigue cues—were integrated into the analysis rather than treated as inconsistencies. Contextual details about participants and settings enhanced transparency, and iterative prototype refinement functioned as a form of member validation, demonstrating the practical utility of the findings. Analytic consistency was maintained through collaborative coding and discussion, supported by reflexive notes and repeated engagement with the data. This approach ensured that the claims are well-supported, meaningful, and relevant to the design of fatigue-sensitive XR rehabilitation tools for pediatric ABI.

Approval from the Regional Committee for Medical and Health Research Ethics in Norway was deemed unnecessary because the study focused on health service research and therefore did not fall under the Health Research Act § 2. Instead, approval was obtained from the Norwegian Agency for Shared Services in Education and Research (SIKT; reference number 871403) to ensure data protection and privacy compliance. Participants received both oral and written information about the study, and informed consent was obtained before conducting the workshops and individual interviews. To protect participant privacy, all data were deidentified through the use of pseudonyms. Given the vulnerability of the study population, fatigue was not deliberately induced. Observation of fatigue cues was limited to naturally occurring behaviors during short, supervised XR sessions conducted in collaboration with the experienced clinical rehabilitation team.

All participants—children, parents/guardians, clinicians, and healthy children involved in the early ideation phase—received written and oral information about the study, and parents/guardians provided informed consent before participation. Participants received gift cards as compensation for their efforts. Study data were deidentified using pseudonyms, and all audio files, transcripts, and workshop materials were securely stored on OsloMet’s research server with access restricted to the research team, ensuring confidentiality and compliance with GDPR (General Data Protection Regulation). No identifiable images or videos of participants are included in the manuscript or its multimedia appendices.

The data analysis revealed 4 main themes: fatigue detection challenges; engagement and motivation; adaptive therapy design; and clinical utility, therapist needs, and child-centered co-design. These themes were further divided into 16 subcategories (Multimedia Appendix 4).

When examined across workshops, children’s self-reported responses reveal a converging pattern of increasing engagement alongside consistently low fatigue, supporting the qualitative observations described above and illustrated in summary Figures 3 and 4. Mean engagement scores steadily increased from workshop 2 through workshop 4, reflecting improvements in perceived immersion, control, enjoyment, and motivation as iterative design changes introduced interactive mechanics, simplified visual environments, and gamified feedback. At the same time, mean fatigue-related scores remained low and showed a slight downward trend, indicating that rising engagement was not accompanied by increased physical or cognitive strain. Importantly, children’s responses to the session-length question contextualize these findings: in workshops 2 and 3, children indicated that XR sessions should not exceed 5-10 minutes, while in workshop 4, preferences shifted toward even shorter, clearly bounded sessions of approximately 3-5 minutes. This convergence suggests that short, modular exposure durations played a critical role in maintaining comfort while supporting engagement. Together, these findings demonstrate that engagement and fatigue can be decoupled through careful XR design: interactive and emotionally supportive gamification elements can enhance motivation when combined with visually grounded AR environments, simplified interfaces, adaptive pacing, and deliberately short session lengths. The alignment between children’s self-reported responses, therapist observations, and iterative design decisions underscores the importance of fatigue-sensitive session structuring as a core principle for pediatric XR-based neurorehabilitation.

This study demonstrates that XR-based rehabilitation, when co-designed with children and therapists, can support engagement and fatigue-aware use by enabling short sessions, visual grounding, and clinician observation of fatigue-related cues during interaction in pediatric brain injury contexts.

Iterative co-design with children, parents, and clinicians led to critical design adaptations that improved usability, personalized challenge levels, and alignment with therapeutic goals. In our study, fatigue was consistently identified as a central barrier to therapy, often expressed behaviorally rather than verbally. Fatigue emerged as the most pervasive barrier to rehabilitation, typically expressed through subtle behavioral changes rather than direct verbal reporting by children. High engagement enhanced participation but also increased the risk of overstimulation, revealing a delicate balance in which engagement must be continuously regulated to prevent fatigue-related disengagement. Therapist observations and behavioral data revealed fatigue-related changes in movement, gaze, and responsiveness that were not consistently captured through children’s self-reported fatigue ratings.

Clinicians emphasized the need for short, adaptive sessions tailored to fluctuating energy levels. Minimal gamification elements, such as scoring and visual feedback, increased motivation and replay desire when designed to support mastery rather than cognitive or sensory stimulation. Children showed noticeably higher engagement with prototypes that included interactive game mechanics (eg, target shooting) and environments that preserved visibility of their own bodies and surroundings. These features improved usability and reduced disorientation. Short, modular sessions (3-10 minutes) supported fatigue management, allowing children to complete sessions without signs of visual or physical fatigue, while therapists observed increased focus and participation. Gamification was effective when purposeful and balanced. Simple scoring systems, visual effects, and immediate feedback increased motivation without overstimulation. Customization and adaptability were also crucial; engagement improved when children could influence the experience (eg, selecting target heights). Therapists suggested further personalization to align with individual abilities and interests. Fatigue could be inferred through behavioral cues. While subjective fatigue scores were low, therapist observations and Cognitive3D tracking data revealed changes in movement, visual focus, and responsiveness as indicators of cognitive strain. Finally, AR-based designs that preserved visibility of the child’s body and surroundings reduced disorientation and supported both engagement and fatigue management, compared with immersive VR environments. Together, these findings highlight the importance of simplicity, interactivity, visual grounding, and short bursts of gameplay in XR design for pediatric neurorehabilitation.

Early case-based research using VR for pediatric ABI rehabilitation has revealed both the potential and concerns related to immersive game-based rehabilitation solutions. One of the main concerns is that, while systems such as the Xbox Kinect could improve balance performance, their cognitive, sensory, and motor demands were often poorly matched to children early in rehabilitation, leading to overstimulation, fluctuating performance, and variable motivation [36]. Our findings build directly on these observations by showing how fatigue becomes visible through behavioral changes during XR interaction and by demonstrating how simplified, visually grounded, and adaptive XR designs can preserve both engagement and safety. Our results suggest that effective XR rehabilitation for children with brain injury requires not only motivating content but also fatigue-sensitive system design that aligns with the child’s moment-to-moment capacity.

Previous research has demonstrated that fatigue is strongly associated with reduced participation and diminished quality of life in adolescents and young adults with ABI [37,38]. In particular, it has been shown that higher fatigue corresponds to greater participation restrictions, highlighting fatigue as a critical therapeutic target [38]. Building on this work, our study extends the field by examining how fatigue manifests during rehabilitation activities themselves, revealing that fatigue emerges through moment-to-moment behavioral changes rather than solely through retrospective self-report. This study advances the design of XR-based rehabilitation tools for children with ABIs by foregrounding fatigue as a central design constraint—an area often underemphasized in prior work.

Consistent with Rohrer-Baumgartner et al [3] and Mazzone et al [21], our findings confirm that fatigue in pediatric brain injury is multifaceted—cognitive, physical, emotional, and sensory—and often behaviorally expressed rather than verbally reported. Our results show that XR-based interaction enables real-time observation of fatigue-related behaviors during task engagement, offering a concrete way to surface these otherwise hidden indicators. In line with Mazzone et al [21], whose findings indicate that clinicians depend heavily on behavioral cues rather than child self-report to detect fatigue, our results suggest that XR-based behavioral markers, such as gaze, posture, and response latency, can support this observational process in a structured manner.

In line with Mazzone et al [21], whose findings indicate that clinicians often rely on behavioral cues rather than child self-report to identify fatigue following pediatric brain injury, this study demonstrates how XR-based rehabilitation can support this observational process in a structured yet clinically aligned manner. By capturing changes in gaze, posture, movement, and responsiveness during short, adaptive XR sessions, the system allowed fatigue to become visible without requiring children to articulate their internal state. Importantly, these behavioral indicators did not replace clinical judgment but supported shared understanding and collaborative decision-making among therapists, children, and families. Together, these findings position XR not as a fatigue-reducing technology per se, but as a fatigue-sensitive design approach that operationalizes existing clinical practices while preserving engagement and emotional safety. Clinicians also need to continually adjust rehabilitation demands to manage fatigue [21]. Our findings extend this work by illustrating how adaptive XR session length and task difficulty can embed this clinical reasoning directly into the intervention design.

While Wender et al [20] emphasize the need for adaptive systems to prevent disengagement, few studies operationalize this need through concrete design strategies. Our work builds on this by implementing modular, short-duration sessions (3-10 minutes) and adaptive difficulty scaling, which allowed children to complete tasks without signs of visual or cognitive overload. While Proschowsky et al [37] describe gradual changes in fatigue across the rehabilitation period using standardized measures, our results suggest that clinically relevant fatigue fluctuations occur within sessions and are primarily observable through changes in interaction behavior, underscoring the need for complementary real-time monitoring approaches. Our approach also aligns with Sweller’s [35] Cognitive Load Theory, which advocates minimizing extraneous load to preserve mental resources—particularly critical in pediatric neurorehabilitation.

Proschowsky et al [37] also demonstrated a consistent discrepancy between child and parent fatigue ratings, particularly for cognitive fatigue, suggesting that children may lack insight into their own fatigue experience. Our findings extend this work by showing that XR-based behavioral indicators—such as gaze disengagement, postural changes, and response latency—can provide an additional, nonverbal layer of information that aligns with clinicians’ observational fatigue assessments. In contrast to XR systems with fixed difficulty levels (eg, [11]), our prototype dynamically adjusted the challenge based on fatigue cues, supporting the “just-right challenge” principle from occupational therapy [39]. This approach not only sustained engagement but also improved therapeutic focus, as observed by clinicians. The use of AR over VR—supported by Rebenitsch and Owen [40]—further reduced disorientation and preserved environmental awareness, which is especially important for children with balance or visual sensitivities. Gamification was another key differentiator. While Deterding et al [41] and O’Brien et al [32] highlight the motivational benefits of game elements, our study extends this by emphasizing adaptive gamification. Rather than static rewards or competitive mechanics [42], we prioritized emotionally supportive feedback, autonomy, and visual grounding. Children responded positively to features such as target selection, score feedback, and interactive animations, confirming that gamification enhances motivation when developmentally appropriate and cognitively balanced [43].

As a qualitative case study, this research is context-specific and not intended for statistical generalization [27,29]. The small participant sample, drawn from a single clinical setting, limits transferability. While including healthy children in early prototyping aligns with child-centered design practices [44,45], it may have introduced discrepancies between early feedback and the needs of children with ABIs. This study used Design Thinking [46] within a qualitative case study to guide XR development for children with brain injuries. Its 5 phases—empathize, define, ideate, prototype [47,48], and test—structured co-design workshops and ensured stakeholder insights shaped solutions focused on fatigue detection, adaptive engagement, and emotional safety. In the empathize phase [49], interviews, observations, and shadowing sessions with clinicians, parents, and children were conducted to understand clinical routines, fatigue triggers, and children’s emotional responses to therapy. In the define phase [47], these insights were synthesized into problem statements, such as the need for understanding fatigue and safeguarding mechanisms to prevent overstimulation. During the ideate phase [50], multidisciplinary workshops with clinicians, designers, and children generated concepts ranging from environmental cues for fatigue to customizable levels of XR immersion. In the prototyping phase [47], low- and mid-fidelity XR mockups were created and iteratively refined based on stakeholder feedback, focusing on interaction patterns, visual clarity, and observational insights. Finally, in the test phase [51], preliminary XR prototypes were trialed in simulated therapy sessions, where children and clinicians evaluated usability, comfort, and safety, directly informing adjustments such as simplified interfaces and adaptive pacing.

This approach was seen as particularly valuable in pediatric rehabilitation, where the wide variation in children’s physical, emotional, and cognitive abilities calls for personalized and context-sensitive design [52]. Co-design is a participatory design approach that involves end users and stakeholders as active contributors in the design process, rather than passive recipients of a finished product. According to Sanders and Stappers [53], co-design centers on collaboration, mutual learning, and shared ownership, enabling users to bring their experiences, needs, and creativity into the creation of meaningful solutions. In our study, Design Thinking was used as an organizing framework to structure the co-design and iterative prototyping process, ensuring that stakeholder insights were translated into concrete, testable design changes [54]. Across empathize, define, ideate, prototype, and test, the focus was to reduce participant burden, capture fatigue-aware requirements, and iteratively refine engagement-related mechanics in short XR sessions. The choice of a case study combined with co-design is justified by the exploratory nature of the research. Together, design thinking, co-design, and case study provide a robust methodology for integrating multiple stakeholder perspectives while iteratively shaping and evaluating the prototype within its intended context of use. From a process perspective, the Design Thinking structure strengthened traceability between stakeholder needs and design outcomes [55]: the empathize and define phases foregrounded fatigue-aware constraints (session duration, sensory load, safety), ideation clarified interaction preferences, and prototype/test cycles enabled rapid validation of engagement mechanics (eg, interactive shooting and scoring) while maintaining visual grounding through AR. This helped balance engagement with the risk of overstimulation, which clinicians described as a central tension in pediatric ABI rehabilitation. Design Thinking supported rapid iteration and stakeholder alignment; however, the iterative nature also meant that not all clinician suggestions could be implemented and retested within the study time frame. Future work should evaluate the refined design elements across more sites and over longer home-use periods. Feedback from the clinical team, though rich, was collected after the final prototype iteration and therefore could not be integrated, tested, or clinically validated. Future work should also explore personalization options (eg, themes, interaction styles) and multilevel interaction design to support both fine and gross motor skills. Prior research emphasizes the importance of individualized therapy content for sustaining motivation and improving outcomes [11,26]. Although the initial prototype dashboard was intended to visualize behavioral fatigue indicators over the long term (eg, gaze, posture), this was not implemented in the present design phase, and the system also lacked physiological data integration. Future systems could integrate XR-compatible wearables to capture biometric signals, such as heart rate variability or pupil dilation, enhancing fatigue detection [56,57]. The dashboard could be further developed as a fatigue detection tool or as a clinical decision-support tool with customizable visualizations, engagement tracking, and real-time alerts [25]. While this study focused on behavioral indicators of fatigue observable during XR interaction, future research may explore the potential role of additional physiological signals, such as heart rate variability or pupil dilation, as complementary sources of information.

Although fatigue detection was not conducted in this study, it is important to note that evidence supporting the validity and reliability of these biometric measures for fatigue detection in pediatric ABI populations is currently limited [37]. Our study revealed a need for objective fatigue detection methods that could support safe personalization of XR solutions. Existing research on biometric fatigue markers, however, stems largely from adult neurological populations or from studies of cognitive load and fatigue in other clinical or nonclinical contexts [58]. As such, any integration of physiological signals into pediatric XR rehabilitation systems should be considered exploratory and would require careful validation, ethical consideration, and age-appropriate interpretation before clinical use. To improve generalizability, future studies should include more diverse participants, test across multiple sites, and assess long-term therapeutic impact. Integration with clinical data systems may also be necessary for sustainable implementation in routine care.