Virtual Peg Insertion Test Research Articles

Influence of virtual reality and task complexity on digital health metrics assessing upper limb function

BackgroundTechnology-based assessments using 2D virtual reality (VR) environments and goal-directed instrumented tasks can deliver digital health metrics describing upper limb sensorimotor function that are expected to provide sensitive endpoints for clinical studies. Open questions remain about the influence of the VR environment and task complexity on such metrics and their clinimetric properties.MethodsWe aim to investigate the influence of VR and task complexity on the clinimetric properties of digital health metrics describing upper limb function. We relied on the Virtual Peg Insertion Test (VPIT), a haptic VR-based assessment with a virtual manipulation task. To evaluate the influence of VR and task complexity, we designed two novel tasks derived from the VPIT, the VPIT-2H (VR environment with reduced task complexity) and the PPIT (physical task with reduced task complexity). These were administered in an observational longitudinal study with 27 able-bodied participants and 31 participants with multiple sclerosis (pwMS, VPIT and PPIT only) and the value of kinematic and kinetic metrics, their clinimetric properties, and the usability of the assessment tasks were compared.ResultsIntra-participant variability strongly increased with increasing task complexity (coefficient of variation + 56%) and was higher in the VR compared to the physical environment (+ 27%). Surprisingly, this did not translate into significant differences in the metrics’ measurement error and test–retest reliability across task conditions (p > 0.05). Responsiveness to longitudinal changes in pwMS was even significantly higher (effect size + 0.35, p < 0.05) for the VR task with high task complexity compared to the physical instrumented task with low task complexity. Increased inter-participant variability might have compensated for the increased intra-participant variability to maintain good clinimetric properties. No significant influence of task condition on concurrent validity was present in pwMS. Lastly, pwMS rated the PPIT with higher usability than the VPIT (System Usability Scale + 7.5, p < 0.05).ConclusionThe metrics of both the VR haptic- and physical task-based instrumented assessments showed adequate clinimetric properties. The VR haptic-based assessment may be superior when longitudinally assessing pwMS due to its increased responsiveness. The physical instrumented task may be advantageous for regular clinical use due to its higher usability. These findings highlight that both assessments should be further validated for their ideal use-cases.

Goal-directed upper limb movement patterns and hand grip forces in multiple sclerosis.

BackgroundUpper limb disability in persons with Multiple Sclerosis (pwMS) leads to increased dependence on caregivers. To better understand upper limb disability, observer-based or time-based clinical assessments have been applied. However, these only poorly capture the behavioural aspects underlying goal-directed task performance.ObjectiveWe aimed to document alterations in goal-directed upper limb movement patterns and hand grip forces in a cohort of pwMS (n = 123) with mild to moderate upper limb impairments.MethodsWe relied on the Virtual Peg Insertion Test (VPIT), a technology-aided assessment with a goal-directed pick-and-place task providing a set of validated digital health metrics.ResultsAll metrics indicated significant differences to an able-bodied reference sample (p < 0.001), with smoothness, speed, and grip force control during object manipulation being most affected in pwMS. Such abnormalities negatively influenced the time to complete the goal-directed task (p < 0.001, R2 = 0.77), thereby showing their functional relevance. Lastly, abnormalities in movement patterns and grip force control were consistently found even in pwMS with clinically normal gross dexterity and grip strength.ConclusionThis work provides a systematic documentation on goal-directed upper limb movement patterns and hand grip forces in pwMS, ultimately paving the way for an early detection of MS sign using digital health metrics.

Reliability and validity of digital health metrics for assessing arm and hand impairments in an ataxic disorder.

ObjectivesAutosomal recessive spastic ataxia of Charlevoix‐Saguenay (ARSACS) is the second most frequent recessive ataxia and commonly features reduced upper limb coordination. Sensitive outcome measures of upper limb coordination are essential to track disease progression and the effect of interventions. However, available clinical assessments are insufficient to capture behavioral variability and detailed aspects of motor control. While digital health metrics extracted from technology‐aided assessments promise more fine‐grained outcome measures, these have not been validated in ARSACS. Thus, the aim was to document the metrological properties of metrics from a technology‐aided assessment of arm and hand function in ARSACS.MethodsWe relied on the Virtual Peg Insertion Test (VPIT) and used a previously established core set of 10 digital health metrics describing upper limb movement and grip force patterns during a pick‐and‐place task. We evaluated reliability, measurement error, and learning effects in 23 participants with ARSACS performing three repeated assessment sessions. In addition, we documented concurrent validity in 57 participants with ARSACS performing one session.ResultsEight metrics had excellent test–retest reliability (intraclass correlation coefficient 0.89 ± 0.08), five low measurement error (smallest real difference % 25.4 ± 5.7), and none strong learning effects (systematic change η −0.11 ± 2.5). Significant correlations (ρ 0.39 ± 0.13) with clinical scales describing gross and fine dexterity and lower limb coordination were observed.InterpretationThis establishes eight digital health metrics as valid and robust endpoints for cross‐sectional studies and five metrics as potentially sensitive endpoints for longitudinal studies in ARSACS, thereby promising novel insights into upper limb sensorimotor control.

Technology-aided assessment of functionally relevant sensorimotor impairments in arm and hand of post-stroke individuals

BackgroundAssessing arm and hand sensorimotor impairments that are functionally relevant is essential to optimize the impact of neurorehabilitation interventions. Technology-aided assessments should provide a sensitive and objective characterization of upper limb impairments, but often provide arm weight support and neglect the importance of the hand, thereby questioning their functional relevance. The Virtual Peg Insertion Test (VPIT) addresses these limitations by quantifying arm and hand movements as well as grip forces during a goal-directed manipulation task requiring active lifting of the upper limb against gravity. The aim of this work was to evaluate the ability of the VPIT metrics to characterize arm and hand sensorimotor impairments that are relevant for performing functional tasks.MethodsArm and hand sensorimotor impairments were systematically characterized in 30 chronic stroke patients using conventional clinical scales and the VPIT. For the latter, ten previously established kinematic and kinetic core metrics were extracted. The validity and robustness of these metrics was investigated by analyzing their clinimetric properties (test-retest reliability, measurement error, learning effects, concurrent validity).ResultsTwenty-three of the participants, the ones with mild to moderate sensorimotor impairments and without strong cognitive deficits, were able to successfully complete the VPIT protocol (duration 16.6 min). The VPIT metrics detected impairments in arm and hand in 90.0% of the participants, and were sensitive to increased muscle tone and pathological joint coupling. Most importantly, significant moderate to high correlations between conventional scales of activity limitations and the VPIT metrics were found, thereby indicating their functional relevance when grasping and transporting objects, and when performing dexterous finger manipulations. Lastly, the robustness of three out of the ten VPIT core metrics in post-stroke individuals was confirmed.ConclusionsThis work provides evidence that technology-aided assessments requiring goal-directed manipulations without arm weight support can provide an objective, robust, and clinically feasible way to assess functionally relevant sensorimotor impairments in arm and hand in chronic post-stroke individuals with mild to moderate deficits. This allows for a better identification of impairments with high functional relevance and can contribute to optimizing the functional benefits of neurorehabilitation interventions.

A data-driven framework for selecting and validating digital health metrics: use-case in neurological sensorimotor impairments

Digital health metrics promise to advance the understanding of impaired body functions, for example in neurological disorders. However, their clinical integration is challenged by an insufficient validation of the many existing and often abstract metrics. Here, we propose a data-driven framework to select and validate a clinically relevant core set of digital health metrics extracted from a technology-aided assessment. As an exemplary use-case, the framework is applied to the Virtual Peg Insertion Test (VPIT), a technology-aided assessment of upper limb sensorimotor impairments. The framework builds on a use-case-specific pathophysiological motivation of metrics, models demographic confounds, and evaluates the most important clinimetric properties (discriminant validity, structural validity, reliability, measurement error, learning effects). Applied to 77 metrics of the VPIT collected from 120 neurologically intact and 89 affected individuals, the framework allowed selecting 10 clinically relevant core metrics. These assessed the severity of multiple sensorimotor impairments in a valid, reliable, and informative manner. These metrics provided added clinical value by detecting impairments in neurological subjects that did not show any deficits according to conventional scales, and by covering sensorimotor impairments of the arm and hand with a single assessment. The proposed framework provides a transparent, step-by-step selection procedure based on clinically relevant evidence. This creates an interesting alternative to established selection algorithms that optimize mathematical loss functions and are not always intuitive to retrace. This could help addressing the insufficient clinical integration of digital health metrics. For the VPIT, it allowed establishing validated core metrics, paving the way for their integration into neurorehabilitation trials.

Concurrent validity and test-retest reliability of the Virtual Peg Insertion Test to quantify upper limb function in patients with chronic stroke.

BackgroundMeasuring arm and hand function of the affected side is vital in stroke rehabilitation. Therefore, the Virtual Peg Insertion Test (VPIT), an assessment combining virtual reality and haptic feedback during a goal-oriented task derived from the Nine Hole Peg Test (NHPT), was developed. This study aimed to evaluate (1) the concurrent validity of key outcome measures of the VPIT, namely the execution time and the number of dropped pegs, with the NHPT and Box and Block Test (BBT), and (2) the test-retest-reliability of these parameters together with the VPIT’s additional kinetic and kinematic parameters in patients with chronic stroke.The three tests were administered on 31 chronic patients with stroke in one session (concurrent validity), and the VPIT was retested in a second session 3–7 days later (test-retest reliability). Spearman rank correlation coefficients (ρ) were calculated for assessing concurrent validity, and intraclass correlation coefficients (ICCs) were used to determine relative reliability. Bland-Altman plots were drawn and the smallest detectable difference (SDD) was calculated to examine absolute reliability.ResultsFor the 31 included patients, 11 were able to perform the VPIT solely via use of their affected arm, whereas 20 patients also had to utilize support from their unaffected arm. For n = 31, the VPIT showed low correlations with the NHPT (ρ = 0.31 for time (Tex[s]); ρ = 0.21 for number of dropped pegs (Ndp)) and BBT (ρ = −0.23 for number of transported cubes (Ntc); ρ = −0.12 for number of dropped cubes (Ndc)). The test-retest reliability for the parameters Tex[s], mean grasping force (Fggo[N]), number of zero-crossings (Nzc[1/sgo/return) and mean collision force (Fcmean[N]) were good to high, with ICCs ranging from 0.83 to 0.94. Fair reliability could be found for Fgreturn (ICC = 0.75) and trajectory error (Etrajgo[cm]) (0.70). Poor reliability was measured for Etrajreturn[cm] (0.67) and Ndp (0.58). The SDDs were: Tex = 70.2 s, Ndp = 0.4 pegs; Fggo/return = 3.5/1.2 Newton; Nzc[1/s]go/return = 0.2/1.8 zero-crossings; Etrajgo/return = 0.5/0.8 cm; Fcmean = 0.7 Newton.ConclusionsThe VPIT is a promising upper limb function assessment for patients with stroke requiring other components of upper limb motor performance than the NHPT and BBT. The high intra-subject variation indicated that it is a demanding test for this stroke sample, which necessitates a thorough introduction to this assessment. Once familiar, the VPIT provides more objective and comprehensive measurements of upper limb function than conventional, non-computerized hand assessments.

The Virtual Peg Insertion Test as an assessment of upper limb coordination in ARSACS patients: A pilot study

ObjectiveThis paper introduces a novel assessment tool to provide clinicians with quantitative and more objective measures of upper limb coordination in patients suffering from Autosomal Recessive Spastic Ataxia of Charlevoix–Saguenay (ARSACS). The Virtual Peg Insertion Test (VPIT) involves manipulating an instrumented handle in order to move nine pegs into nine holes displayed in a virtual environment. The main outcome measures were the number of zero-crossings of the hand acceleration vector, as a measure of movement coordination and the total time required to complete the insertion of the nine pegs, as a measure of overall upper limb performance. Results8\\9 patients with ARSACS were able to complete five repetitions with the VPIT. Patients were found to be significantly less coordinated and slower than age-matched healthy subjects (p<0.01). Performance of ARSACS patients was positively correlated with the Nine-Hole Peg Test (r=0.85, p<0.01) and with age (r=0.93, p<0.01), indicative of the degenerative nature of the disease. Conclusion(s)This study presents preliminary results on the use of a robotics and virtual reality assessment tool with ARSACS patients. Results highlight its potential to assess impaired coordination and monitor its progression over time.