I consider assessments absolutely worthless unless they point DIRECTLY TO 100% RECOVERY PROTOCOLS!
Extended reality to assess post-stroke manual dexterity: contrasts between the classic box and block test, immersive virtual reality with controllers, with hand-tracking, and mixed-reality tests
Journal of NeuroEngineering and Rehabilitation volume 21, Article number: 36 (2024)
Abstract
Background
Recent technological advancements present promising opportunities to enhance the frequency and objectivity of functional assessments, aligning with recent stroke rehabilitation guidelines. Within this framework, we designed and adapted different manual dexterity tests in extended reality (XR), using immersive virtual reality (VR) with controllers (BBT-VR-C), immersive VR with hand-tracking (BBT-VR-HT), and mixed-reality (MD-MR).
Objective
This study primarily aimed to assess and compare the validity of the BBT-VR-C, BBT-VR-HT and MD-MR to assess post-stroke manual dexterity. Secondary objectives were to evaluate reliability, usability and to define arm kinematics measures.
Methods
A sample of 21 healthy control participants (HCP) and 21 stroke individuals with hemiparesis (IHP) completed three trials of the traditional BBT, the BBT-VR-C, BBT-VR-HT and MD-MR. Content validity of the different tests were evaluated by asking five healthcare professionals to rate the difficulty of performing each test in comparison to the traditional BBT. Convergent validity was evaluated through correlations between the scores of the traditional BBT and the XR tests. Test-retest reliability was assessed through correlations between the second and third trial and usability was assessed using the System Usability Scale (SUS). Lastly, upper limb movement smoothness (SPARC) was compared between IHP and HCP for both BBT-VR test versions.
Results
For content validity, healthcare professionals rated the BBT-VR-HT (0[0–1]) and BBT-MR (0[0–1]) as equally difficult to the traditional BBT, whereas they rated BBT-VR-C as more difficult than the traditional BBT (1[0–2]). For IHP convergent validity, the Pearson tests demonstrated larger correlations between the scores of BBT and BBT-VR-HT (r = 0.94;p < 0.001), and BBT and MD-MR (r = 0.95;p < 0.001) than BBT and BBT-VR-C (r = 0.65;p = 0.001). BBT-VR-HT and MD-MR usability were both rated as excellent, with median SUS scores of 83[57.5–91.3] and 83[53.8–92.5] respectively. Excellent reliability was found for the BBT-VR-C (ICC = 0.96;p < 0.001), BBT-VR-HT (ICC = 0.96;p < 0.001) and BBT-MR (ICC = 0.99;p < 0.001). The usability of the BBT-VR-C was rated as good with a median SUS of 70[43.8–83.8]. Upper limb movements of HCP were significantly smoother than for IHP when completing either the BBT-VR-C (t = 2.05;p = 0.043) and the BBT-VR-HT (t = 5.21;p < 0.001).
Conclusion
The different XR manual tests are valid, short-term reliable and usable tools to assess post-stroke manual dexterity.
Trial registration
https://clinicaltrials.gov/ct2/show/NCT04694833; Unique identifier: NCT04694833, Date of registration: 11/24/2020.
Background
Upper limb impairments are prevalent during both the acute [1, 2] and chronic phase [3] after a stroke. Such impairments result in activity limitations and participation restrictions, leading to a decline in the overall quality of life [4, 5]. In the field of neurorehabilitation, regular and time-bounded assessments of impairments and activity limitations are of utmost importance for establishing an effective rehabilitation plan [6, 7]. Moreover, functional assessments play a critical role in identifying prognostic factors that influence stroke recovery [8]. Recently, experts have formulated recommendations for the clinical evaluation of the upper limb in neurorehabilitation [9]. One such recommended assessment is the Box and Block Test (BBT) [10], which measures manual dexterity in the activity domain (according to the International Classification of Functioning, Disability and Health) [10]. Additionally, experts have highlighted the significance of kinematics in assessing body functions, through measures of movement quality and compensations during activity of daily living tasks [11].
In recent years, extended reality (XR) has emerged as an innovative and promising approach in rehabilitation. XR is a comprehensive concept that encompasses both present and forthcoming advancements in virtual reality (VR) and mixed reality (MR) [12]. VR technology allows for a computerized immersion of individuals in digitally created worlds, enabling them to experience multiple sensory stimuli and interact with the virtual environment through various modalities [13]. There are two primary types of VR experiences: non-immersive VR, where users remain aware of their physical surroundings and receive visual feedback through a 2D display, and immersive VR (iVR), which allows complete submersion in the virtual environment (using a Head Mounted Display (HMD) or a large curved screen with panoramic view) and provides a panoramic view [14]. More recently, MR systems have been developed [15] that offer individuals a hybrid experience by combining real objects and virtual environments to create a captivating midway point between these two realities [14]. MR can be classified as augmented reality and augmented virtuality systems. Augmented reality involves overlaying virtual information onto the physical environment whereas in augmented virtuality, real-world data is superimposed onto a virtual environment.
In the context of upper limb rehabilitation using XR, hand tracking and controllers are commonly employed as input devices to enable users to interact with the virtual environment [14, 16]. Hand-tracking technology measures hand position using HMDs equipped with infrared detectors or other specialized hardware (e.g., Leap Motion®), providing realistic visual feedback of hand and finger positions. However, current XR systems using hand-tracking technology do not allow for the provisioning of tactile feedback. On the other hand, controllers equipped with buttons and inertial measurement units enable the delivery of haptic feedback, but with limited visual feedback and positioning capabilities. Virtual representations of hand and fingers are not always available, and when they are, they do not always reflect natural hand positions. Most systems incorporating controllers tend to employ pre-determined hand poses that dynamically change based on the buttons pressed and the controller’s position, rather than accurately reflecting the real positions of hands and fingers. Both input methods (hand-tracking technology and controllers) have unique advantages and can be utilized based on the specific rehabilitation needs and goals of the individual.
Recently, VR has transcended its role as a therapeutic tool and has emerged as a valuable means of assessing upper limb body function [17], cognition [18, 19] and activities [20,21,22]. This assessment approach offers several advantages over traditional outcome measures. Firstly, VR allows for the implementation of computerized standardized protocols, effectively reducing the risk of inter and intra-rater bias. Secondly, it facilitates the measurement of multiple quantitative and objective variables, notably including reaction time, response time and kinematics, providing complementary performance measures that together build a more comprehensive understanding of the patient’s progress. Thirdly, once patients have been trained in VR assessment, they may gain the ability to conduct assessments independently, presenting the opportunity to increase the frequency of evaluations, even within the comfort of their homes.
Several iterations of the BBT have been developed in VR. Notably, two studies have demonstrated strong correlations between scores obtained in non-immersive VR versions and those of the traditional BBT [23, 24]. The first study was conducted among individuals with stroke [23] and the second among healthy participants and individuals with spinal cord injury [24]. Oña et al. took a step further by developing the first iVR BBT using an HMD and hand-tracking technology (Leap Motion®) to measure hand and finger movements [25]. Their study revealed a moderate correlation between the virtual BBT and traditional BBT scores among individuals with Parkinson Disease [25]. In a study by Dong et al., another immersive virtual BBT was designed, employing a specific haptic device [26]. The outcomes indicated moderate correlations between virtual and traditional versions of the test [26]. Similarly, we created an iVR BBT that employed controllers to manipulate and move the virtual blocks, while the HMD provided visual feedback [20]. Results demonstrated strong correlations between the number of blocks moved by individuals with stroke during the virtual and traditional BBT [20]. More recently, to further enhance the assessment process, a new manual dexterity test inspired by the BBT has been developed in MR using real blocks and an interactive non-immersive virtual environment display (REAtouch®, AXINESIS®, Belgium).
While several studies have explored the validity of VR-based BBT versions, a significant gap in the literature remains. To date, there have been no comprehensive investigations that directly compare different VR versions of BBT assessments, specifically contrasting responses made with hand-tracking vs. haptic devices. Hand-tracking technology may lead to improved sense of presence and more effective interaction when compared to haptic devices, but the accuracy and reliability of this technique remains debated [27]. Moreover, the validity of developing a manual dexterity test in MR remains under-explored. Yet, such developments could be of interest as, in contrast with hand-tracking and controller technologies, MR systems allow users to manipulate real word objects, therefore providing true haptic feedback. Addressing this research void is essential for gaining a comprehensive understanding of the relative advantages and limitations of these input modalities. Furthermore, to date, few studies have explored the potential of XR reality to assess upper limb kinematics. This study first aimed to bridge this gap by comparing the content and convergent validity of different XR BBT versions and manual dexterity tests using hand-tracking, controllers, and MR among healthy participants and individuals with stroke. We first hypothesized that scores from the iVR and MR tests versions would be strongly correlated to the traditional BBT. We also hypothesized that, on average, participants would displace more blocks in the traditional test and when using hand-tracking technology than when using controllers [27]. Secondary objectives were to assess and compare the reliability and usability of the different iVR and MR tests. Lastly, we aimed to compare upper limb kinematics that were acquired in iVR between individuals with stroke and healthy participants.
Martin Lotze
Påvel G. Lindberg