1 Introduction

Upper-limb motor skills, such as handwriting and drawing, play a fundamental role in the development of children and adolescents because these skills are essential for school performance and the activities of daily living (Accardo et al. 2013). Assessment of these skills is essential to ensure that children receive the optimal support throughout childhood and into adolescence, and is important for developing and implementing appropriate therapies for clinical population, e.g., cerebral palsy (CP) (Elvrum et al. 2016). Circle drawing is a simple task that can provide insight into children’s ability to develop upper-limb motor skills and fine motor control (Cohen et al. 2021; Gatouillat et al. 2017). In addition, circle drawing has been used to examine the interaction of sensory-motor, perceptual and cognitive abilities (Georgopoulos 2000; Smits-Engelsman and Van Galen 1997). However, it has been reported that circle drawing in children can vary with development, with younger children tending to require more time and muscular effort (shoulder and elbow involvement) to draw circles compared with older children and young adults (Ringenbach and Amazeen 2005). For example, Rueckriegel et al. (2008) examined circle drawing in a group of children and adolescents and reported that, across a number of metrics, older children drew better circles than younger children. Furthermore, it has been reported that age is likely to be a critical factor in the assessment of children’s fine motor development, such as circle drawing, because older children have been shown to perform this task better than younger children (Lin et al. 2015; Pacilli et al. 2014; Robertson Ringenbach and Amazeen 2005). Indeed, these studies explicitly highlight the potential value of circle drawing in quantifying juvenile motor performance and discussed potential variations in the performance due to age-related differences.

The potential use of virtual reality (VR) in the rehabilitation of children and adolescents in pediatric physiotherapy has gained much attention in recent years. Reid (2002a, b) was one of the first to examine the viability of VR with children. In these earlier applications, the author reported that VR play-based intervention was promising in the rehabilitation programme of children with CP. Several subsequent papers have since highlighted the ability of VR to provide an enriching and motivational environment to conduct goal-oriented tasks with different outcomes, useful feedback and a flexible number of repetitions (Bryanton et al. 2006; El-Shamy and Alsharif 2017; Kott et al. 2009; Levac et al. 2012; Liu et al. 2022; Reid 2004). Each of these factors aim to capitalize on neuroplasticity and improve rehabilitation outcomes (Corbetta et al. 2015).

A growing body of published work has provided evidence of the usefulness of integrating VR into the rehabilitation programme of children and adolescents with CP (Amirthalingam et al. 2021; Arnoni et al. 2021). However, a recent review reported that much of the published research on VR and upper-limb rehabilitation in children with CP has focused only on non-immersive VR, e.g., Nintendo Wii/Wii Fit video games (Alrashidi et al. 2022). This type of VR does not, however, fully reflect the capabilities of this technology, such as immersion. Immersive VR (iVR) is typically provided through a Head-Mounted Display attached over the user’s eyes. iVR provides stereoscopic depth cues and tracking of head position to allow the user to feel more present in the virtual environment. Furthermore, it has been shown that iVR has the potential to improve performance (Xu et al. 2021) and bring a better positive experience (Xu et al. 2020) compared with non-immersive VR.

iVR is becoming more portable and affordable with commercially available headsets, such as the HTC Vive and Meta Quest systems. These systems feature built-in motion capture functions and, as such, individualized therapeutic tasks can be developed through specific iVR software assisting physiotherapy and rehabilitation (Voigt-Antons et al. 2020). These systems have been shown to be feasible diagnostic tool for motor rehabilitation of adult stroke survivors (Fregna et al. 2022), and provide patients with a more engaging and sustainable environment compared with conventional interventions (Laver et al. 2017). The findings from the review of Laver and colleagues may well be generalized to children, given that these factors are particularly crucial in administering pediatric physiotherapy.

While iVR has been used successfully in the context of diagnosis for upper-limb stroke survivors (Mekbib et al. 2021; Song and Lee 2021), only a few studies have explored the feasibility of iVR headsets for children and adolescents. The few studies to do so have placed their focus on non-upper-limb physiotherapy and rehabilitation, such as walking activities in children with neurological conditions (Ammann-Reiffer et al. 2022) and motor proficiency in youths with autism spectrum disorders (Hocking et al. 2022), or focused on upper limb injuries in pediatric patients (Phelan et al. 2023). These studies reported that iVR could be a promising tool for children but did not evaluate the degree to which these headsets can quantify children’s upper-limb motor performance. To try and quantify children’s upper-limb motor performance in an iVR environment, we developed a protocol where neurotypical children were asked to trace circles in a virtual environment using a Meta Quest 2 headset.

Therefore, the aims of the study were threefold. Firstly, to assess the acceptability and feasibility of using iVR headsets in typically developing children and adolescents in the context of measuring upper-limb movement. Secondly, to identify any adverse effects of using headsets with children and adolescents, and thirdly to assess the strength of the relationships between age, performance and usability score, and circle drawing metrics in iVR.

2 Methods

2.1 Participants

Thirty-six children and adolescents (12 females, 24 males), and at least one of their parents were recruited and completed this study. The mean age was 12 ± 2.1 years (range 8–16 y). Five participants reported that they preferred to use their left hand for most tasks, and three participants had VR experience. All participants were self-reported to be healthy, with no neurological impairments, musculoskeletal injuries of the upper limbs and the trunk, and no known impairment to function.

2.2 Measures and experimental procedures

All experimental procedures for this study were conducted in one laboratory visit. A participant information sheet was provided to all participants and their parents at least 48 h prior to arriving at the laboratory. On arrival at the laboratory, all participants and their parents were asked to complete written assent and informed consent forms respectively and had the opportunity to ask any questions. Following this, participants completed the iVR task, which was developed using the Unity game engine (Unity Technologies, San Francisco, USA). The iVR task used in this study was a circle tracing task delivered through a Meta Quest-2 headset (Meta Platforms, Inc., California, USA), in which participants were asked to trace the outline of a horizontal holographic circle shown in their display, as quickly and accurately as possible. The virtual environment consisted of a monitor screen to present instructions on how to complete the task and a holographic virtual circle (Fig. 1), which was approximately 1.4 m above the floor. The circle had a small start point indicating where to start and end the movement. To draw a circle, participants placed the controller over the start point, pressed the trigger down, and traced the circle until they reached the start point again; during that time, the movement was recorded as one trial (Fig. 1). If the participants release the trigger during the drawing, the trial automatically restarted.

Fig. 1
figure 1

Circle drawing task in iVR environment

Full size image

The participants first watched a short video illustrating how to complete the experiment (see Supplementary Video 1), before completing six practice trials (three with each hand) to familiarize themselves with the task. Afterward, they proceeded to the actual experiment. This protocol consisted of 32 trials (16 with each hand in a randomized order). Although circle drawing task is a unimanual task, the participants were asked to draw circles in both clockwise (using the right hand) and counterclockwise (using the left hand) directions to avoid any issues arising from asynchrony between the two hands (Carson et al. 1997). The participants were able to rest between trials as long as they wanted. The participants received visual and audio feedback whilst tracing the circle. A humming sound was played, and a cyan-colored line appeared at the participants’ hand position to indicate the drawing. After the trigger was released, the humming sound stopped, and the cyan line disappeared to indicate the trial completion. To avoid collisions with obstacles, participants were asked to complete the task while standing, and were supervised by the researcher throughout the experiment.

After participants completed the iVR part of the experiment, they were asked to complete an adapted version of the System Usability Scale (SUS), a simple and reliable ten-item tool that measures whether a device or system is usable and learnable (Brooke 1996). The SUS is a five-point Likert scale comprising ten statements, where even-numbered statements are structured in a negative form, and odd-numbered statements are structured in a positive form (Bangor et al. 2008; Brooke 1996). SUS statements evaluate the learnability (statements 4 & 10), ease of use (statement 3), confidence (statement 9), and remaining statements appraise the usability (Lewis and Sauro 2009). Each statement is rated between zero and four (zero = strongly disagree and four = strongly agree). Then the total score for each participant is multiplied by 2.5 to attain a total score of 100. The total SUS score can be interpreted as follows: (a) zero–64 = not acceptable, (b) 65–84 = acceptable, and (c) 85–100 = highly acceptable (Bangor et al. 2008). The SUS questionnaire was adapted by adding terms related to iVR headsets with children. To consider the risk of iVR to provoke motion sickness symptoms, a short, self-reported questionnaire was used to investigate whether the participants experienced any negative symptoms during the experiment, e.g., nausea, dizziness, headache.

While these tasks were being completed, the parent was asked to complete the Developmental Coordination Disorder-Questionnaire (DCD-Q) to quantify their child’s motor performance. The DCD-Q is a parent-reported outcome measure that evaluates the fine motor control of children aged five to 15 years. This questionnaire comprises 15 Likert-scale questions with a total score of 75 (Wilson et al. 2007), designed to identify problems in control of movement, fine motor skills, and general coordination (Matta et al., 2021). While this questionnaire was developed as a screening tool for DCD, it is widely used to quantify movement skills in typically-developing control groups in these studies (e.g., (Allen et al. 2023; Ferreira et al. 2020)). To this end, we used the DCD-Q in the current study to obtain a rapid metric of the children’s motor performance to compare with our newly-derived iVR measures.

2.3 Data analysis

Positional data from the iVR task were captured at a frequency of approximately 72 Hz using a custom C# script carried out in Unity, and this script recorded the XYZ positions and rotations of the controllers of each hand using the built-in tracking function of the headset. Data processing was performed in MATLAB (version R2022a, The MathWorks, Inc., Massachusetts, USA). Data were filtered using a dual-pass, zero phase shift Butterworth filter at 10 Hz (Franks et al. 1990), and were then resampled at 90 Hz to maintain a consistent sampling rate across all the trials, as in (Arthur et al. 2021).

2.4 Circle drawing metrics

Movement time and velocity are features of fine motor development (Lin et al. 2015). Therefore, movement time and mean velocity were averaged across trials for each participant using a custom script written in MATLAB. Before averaging took place, 1% of the total frames captured for each trial were cropped from the movement’s start and end to eliminate any artefacts caused by resampling. In addition, in case of any participants had pressed the trigger but had not yet started moving, movement onset was defined as the point at which velocity in the x-axis first exceeded 50 mm per second for three sequential frames (Arthur et al. 2021; Eastough and Edwards 2007).

To calculate circle roundness, an ellipse was fitted to the children’s hand path on each trial. Ellipses were generated and fitted using Principal Component Analysis (Tuta et al. 2019). Circle roundness was defined as the ratio between the major and minor axes of the fitted ellipse (Krabben et al. 2011; Oliveira et al. 1996), and was averaged across trials for each participant. The values for roundness range between zero and one, where values closer to one indicate a more perfect circle.

2.5 Statistical analyses

Descriptive statistics (mean, standard deviation, and frequencies) were compiled to present the data from the SUS. The normality of data was visually checked using a normal probability plot and tested using Shapiro-Wilk test. Relationships between age, motor performance (DCD-Q) and usability score were examined via Pearson’s correlation. As the data derived from the circle drawing metrics were not normally distributed (p < 0.001), a Spearman’s correlation test was performed to assess the strength of the relationships between age, SUS scores, DCD-Q scores, and the kinematic measures. The strength of the correlation was divided into weak, moderate and strong based on Cohen (1988) guidelines. The adverse effects questions were narratively reported. The statistical analyses for this study were performed using SPSS version 28 (IBM, Chicago, IL, USA).

3 Results

No adverse effects or discomfort associated with VR use were reported for any participants.

3.1 System usability scale

The mean score for the SUS was 74 ± 11, indicating a good level of usability, which is above the standard mean score of 68 for the SUS scale. Female and male participants showed similar scores (76 ± 10 vs. 73 ± 11) respectively. The mean score for the DCD-Q was 68 ± 6 (range 49–75). A frequency table of the SUS responses is shown below in Table 1.

Table 1 Frequencies and percents of SUS responses
Full size table

A Pearson’s correlation test revealed a weak but significant relationship between age and SUS scores (r = 0.35, p = 0.04; Fig. 2a). No significant relationship was observed between the DCD-Q scores and SUS scores (r = 0.14, p = 0.43; Fig. 2b).

Fig. 2
figure 2

Scatterplots of relationships between SUS scores & age (a) and SUS scores & DCD-Q scores (b)

Full size image

3.2 Circle drawing metrics

The mean of movement time was 4.8 ± 3.1 s, mean velocity was 23.7 ± 11.8 mm/s and mean of roundness ratio was 0.9 ± 0.1.

3.3 Relationship with SUS scores

As the data were not normally distributed, Spearman’s correlation analysis was used to test the relationships between the SUS scores and the circle drawing metrics. The analysis showed a weak and non-significant correlation between SUS scores and movement time (rho = 0.24, p = 0.1; Fig. 3a) or the mean velocity (rho = -0.19, p = 0.2; Fig. 3b). However, there was a significant and moderate correlation between SUS scores and roundness (rho = 0.5, p = 0.003; Fig. 3c).

Fig. 3
figure 3

Scatterplots of relationships between SUS scores & movement time (a), mean velocity (b) and roundness ratio (c). The circled point indicates potential outliers, which was included in the analysis - the results unchanged without the outlier removed

Full size image

3.4 Relationship with DCD-Q scores

No significant correlations were observed between DCD-Q scores and movement time (rho = -0.05, p = 0.7 – Fig. 4a), mean velocity (rho = 0.1, p = 0.6 – Fig. 4b), or roundness (rho = 0.07, p = 0.7 – Fig. 4c).

Fig. 4
figure 4

Scatterplots of relationships between DCD-Q scores & movement time (a), mean velocity (b) and roundness ratio (c) The circled point indicated potential outlier, which was included in the analysis - the results unchanged without the outlier removed

Full size image

3.5 Relationship with age

Non-significant and weak correlations were found between age and movement time (rho = -0.05, p = 0.8; Fig. 5a), mean velocity (rho = 0.08, p = 0.6; Fig. 5b), or roundness (rho = 0.29, p = 0.08; Fig. 5c).

Fig. 5
figure 5

Scatterplots of relationships between age & movement time (a), mean velocity (b) and roundness ratio (c). The circled point indicates potential outlier, which was included in the analysis - the results unchanged without the outlier removed

Full size image

4 Discussion

This study aimed to assess the acceptability and feasibility of using iVR to measure motor performance in children and adolescents. The findings of this study indicated that an iVR headset is technically feasible and has good level of usability. Another finding was that age is positively (but weakly) associated with the SUS scores of headsets, indicating that older children might find the iVR circle drawing task easier to use than younger children did. No significant association was found between the DCD-Q and SUS scores. None of the circle drawing metrics were related to motor performance as assessed by the DCD-Q in the neurotypical sample group, and these metrics did not appear to be affected by participant age. Our data showed, however, that the children who found the iVR headset most usable drew the rounded circles.

The data from the SUS (Table 1) show that Meta Quest 2 headsets are technically feasible and have good acceptance levels for usability to deliver circle drawing tasks across the observed age range. This finding is consistent with the recent results of Ammann-Reiffer et al. (2022), who noted that the iVR headset is a usable tool to engage and encourage children and adolescents in walking activities. Together, these findings indicate that iVR could be a promising tool in pediatric rehabilitation in both upper-limb and lower limb protocols. The high SUS scores in this study could be explained because the task was not performed under time pressure and with few constraints so did not feel challenging, which reflects the simple nature of the task. Another factor to explain this result is that the nature of the virtual environment contributes to positively engaging the participants with headsets and the task. Indeed, virtual environments have been shown to have a crucial contribution in boosting children’s levels of motivation and engagement (Porras et al. 2018; Shen et al. 2020), and concentration (Jha et al. 2021).

In this study, the age of children was found to be positively but weakly associated with SUS score. This relationship is consistent with other research showing that fine motor skills (e.g., circle drawing) during childhood and adolescence are still being developed and refined; therefore, variations in these skills are to be expected (Cohen et al. 2021; Rueckriegel et al. 2008). However, more research in this area needs to be undertaken before the strength of the association between age and SUS scores is more clearly understood. For example, an obvious avenue for future research could be the potential associations between palm/hand size and the usability of the VR task/application. By contrast, no significant relationship was observed between the DCD-Q and SUS scores. Although the DCD-Q has good validity and reliability (Civetta and Hillier 2008; Wilson et al. 2007), the parents’ responses relating to DCD-Q were subjective and, therefore, susceptible to response bias. Furthermore, it must be acknowledged that the DCD-Q was developed explicitly as a screening tool for children with DCD, and thus is not typically used as a method to quantify individual differences in children without DCD (although it is often used to quantify movement performance in typically-developing control groups). This factor may have limited our ability to detect any associations between the DCD-Q and the circle drawing metrics or SUS. Indeed, this result raises an interesting question regarding the suitability of the DCD-Q as an objective measure of motor performance in typically-developing children.

The results of the study also show no significant relationships between SUS scores, DCD-Q scores, and age with circle drawing metrics, except for the correlation between circle roundness and SUS scores. To the best of our knowledge, no previous work has examined the association between SUS scores, DCD-Q, and circle drawing metrics. However, Rueckriegel et al. (2008) reported that the age of children and adolescents significantly correlates with the velocity of drawing circles. This finding differs from the outcome presented in this study, where no significant relationship was observed between the age and velocity variables. This discrepancy could be attributed to the differences in the measurements employed in these studies, as Rueckriegel and colleagues used digitizing graphic tablets to deliver the tasks to the participants. It is possible that differences in the level of haptic feedback and precision afforded by tablets and styli as compared to iVR controllers and headsets may account for some aspects of this discrepancy (Zhao et al. 2020). It can also be argued that drawing movement on a tablet is supported against gravity, which can be easier than unsupported drawing movement as is the case in this study. Furthermore, this unsupported circle drawing task in iVR might have recruited more proximal musculature than would have been used in an equivalent supported (i.e., tabletop) task. Indeed, a potential limitation of this study is that the participants completed the iVR tasks while standing, and it is unclear how circle drawing performance might change if the participants completed the tasks while sitting. In addition, the study did not control for the possible confounding effects of the variations in the height of the virtual circle and participants’ heights. Finally, it is worth speculating on how participants’ motivation to engage with iVR headsets might affect their performance in this task, which is a fruitful area for future research.

The recent guidelines on upper-limb rehabilitation in CP show that the traditional clinical assessment scales and measures have a number of drawbacks (Veruggio 2022). The current main scales, including but not limited to, the Quality of Upper Extremity Skills Test, Box and Block Test, Assisting Hand Assessment, ABILHAND-Kids, are fundamental in setting therapeutic plans and evaluating progress over the planned therapies (Veruggio 2022). While these tasks/scales are easy to use, they can be onerous to administer and subject to variations in scoring due to their subjective nature and potential influence of the assessor. Therefore, the recommendation from the recent guidelines is to apply, where possible, ‘computational technology’ during the assessment process. The findings from this paper highlight the potential role of iVR more broadly in future pediatric physiotherapy practice. Recently, there has been a rapidly growing interest in the role of immersive technologies in the healthcare system. The National Health Service (NHS) in the United Kingdom launched a key national project called Extended Reality Technologies, including iVR and augmented reality (NHS-England 2022) - a project dedicated to supporting healthcare providers to adopt evidence-based technological tools in their practice to improve the quality of healthcare provided, reduce costs, and increase patient and healthcare provider satisfaction. Other national networks also support the use of iVR for children, such as the National Institute for Health and Care Research (NIHR - children and young people MedTech co-operative), and the Technology Innovation Transforming Child Health (TITCH) networks. The successful transition of VR from research into clinical practice is however dependent on the quality of current evidence, the accessibility of resources and the versatility of VR as a tool to meet patients’ demands and goals (Rathinam 2021). The findings in this study are a first step to translating research into clinical practice.

The iVR circle drawing task used in this study provides an objective assessment method assessing upper-limb performance in children, which could be adapted for pediatric physiotherapists to quantify upper-limb movement in clinical populations in a repeatable and engaging way. This technology is comparable in cost with traditional clinical assessment tools, portable, and demonstrably feasible to implement in a pediatric sample. As such, our task - and others like it, may provide useful insights into the spatiotemporal dimensions of movement quality pre and post-interventions or therapeutic exercises (Choi et al. 2021). Reduced costs, wider access, patient interests, and increased portability of iVR (Elor et al. 2018) mean that these technologies have the capability to play a greater role in physiotherapy for diagnosis, monitoring, and rehabilitation purposes. Together, these points support the growing interest from the NHS and other UK national networks in technology applications and clinical practice.

In conclusion, this study provides the first feasibility assessment of iVR headsets to deliver a simple and portable circle tracing task for children and adolescents. The findings of this study indicate that the method offers good levels of acceptability, ease of use, learnability, and confidence. No adverse effects associated with iVR use were reported from any participants. This study showed that age plays a minor role in the usability of this iVR task for the observed age range and all the participants were able to cope with the task proficiently. However, more research should be undertaken to understand the association between age, motor performance, and the usability of iVR. Further research in the pediatric clinical population is an essential next step in confirming the feasibility of iVR headsets with rigorous, objective clinical outcome measures. Also, future research should usefully explore the perceived barriers and challenges to the implementation of iVR headsets in pediatric physiotherapy practice.