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, 9 (1), 19972

First Validation of a Novel Assessgame Quantifying Selective Voluntary Motor Control in Children With Upper Motor Neuron Lesions

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First Validation of a Novel Assessgame Quantifying Selective Voluntary Motor Control in Children With Upper Motor Neuron Lesions

Jeffrey W Keller et al. Sci Rep.

Abstract

The question whether novel rehabilitation interventions can exploit restorative rather than compensatory mechanisms has gained momentum in recent years. Assessments measuring selective voluntary motor control could answer this question. However, while current clinical assessments are ordinal-scaled, which could affect their sensitivity, lab-based assessments are costly and time-consuming. We propose a novel, interval-scaled, computer-based assessment game using low-cost accelerometers to evaluate selective voluntary motor control. Participants steer an avatar owl on a star-studded path by moving the targeted joint of the upper or lower extremities. We calculate a target joint accuracy metric, and an outcome score for the frequency and amplitude of involuntary movements of adjacent and contralateral joints as well as the trunk. We detail the methods and, as a first proof of concept, relate the results of select children with upper motor neuron lesions (n = 48) to reference groups of neurologically intact children (n = 62) and adults (n = 64). Linear mixed models indicated that the cumulative therapist score, rating the degree of selectivity, was a good predictor of the involuntary movements outcome score. This highlights the validity of this assessgame approach to quantify selective voluntary motor control and warrants a more thorough exploration to quantify changes induced by restorative interventions.

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Assessgame elements and sensor placement. (A) Start screen; participant chooses avatar owl. (B) Participant tries to steer avatar on the star-studded path by appropriate movements of the target joint, while being instructed not to move the other joints or trunk. (C) An accommodation phase during which the participant was made familiar with steering the owl preceded the 30 s of measurement. The path was calibrated for each individual participant. Movements were performed within 90% of the active range of motion of each joint. The last 5 s were implemented to ensure that the participants continued playing until the end but were not analyzed. (D) Placement of sensors for the lower and upper extremities with indication of coordinate system. Sensors were attached with Velcro straps. To avoid that participants could steer the avatar with compensatory movements of the more proximal joints, we used master-slave sensor pairs for each joint to ensure that appropriate movements were used to steer the owl. The participants were seated on a pedestal or an adjustable chair for the lower and upper extremity testing, respectively.
Figure 2
Figure 2
Summary of data analysis steps and visualization of outcome scores. The assessgame splits selective voluntary motor control (SVMC) into target joint accuracy and involuntary movements. We visualized the algorithm analyzing the raw accelerometer data resulting in standardized error scores for both outcome metrics. For the target joint, the numbers between 0 and 100 reflect the percentage joint position relative to the calibrated active range of motion. The involuntary movements were analyzed by first calculating the actual joint angle and then the derivative to quantify changes in position. This was done so that patients who were unable to maintain the starting position were not penalized. Finally, the standardized error expresses how many adult standard deviations the player was away from either the target path or the adult mean (involuntary movements) on average. The exact procedure is described in the supplementary material section. The scatterplot (described in more detail in Fig. 3) displays the accuracy metric on the y-axis and the averaged standardized errors of up to 11 other joints, accounting for the involuntary movement score on the x-axis. Abbreviations: aROM = active range of motion; SD = standard deviation; NIA = neurologically intact adults; NIC = neurologically intact children; P = pediatric patients.
Figure 3
Figure 3
Examples of individual composition of outcome scores. More affected/non-dominant ankle flexion/extension as an example plot. The individual coordinates on the accuracy and involuntary movement plot are broken down into joint angle derivatives for every joint monitored during the assessgame play through. Therapist opinions are also provided. Age-normalizing was performed via z-transformation by creating peer groups ranging ± 1 year around the integer age of the current participant when looking at neurologically intact children and patients. The neurologically intact adults were not subjected to subgrouping. The resulting z-scores for each participant are presented in the age-normalized plot. Z-scores were constructed such that a positive value corresponds to a worse than average score and negative scores conversely indicate a better than average score, analogous to the non-age-normalized plot (larger values indicate worse scores). Abbreviations: aROM = active range of motion; TJP = target joint position; JAD = joint angle derivative; NIA = neurologically intact adults; NIC = neurologically intact children; P = pediatric patients; CP = cerebral palsy; GMFCS = Gross Motor Function Classification System.
Figure 4
Figure 4
Linear mixed model results of the lower extremities. Linear mixed models and violin plots combined with box plots displaying the accuracy and involuntary movement outcomes of all lower extremity joints individually. Marginal R2 describes how much variance is accounted for by the fixed effects and conditional R2 by the total model. R2 change indicates how much the marginal R2 increased when adding the predictor to the model. An example of how to read the table (from left to right): Looking at therapist opinion, a change of predictor level from 0 to 3 yields a log-transformed outcome score increase of 0.32 (level 3 minus level 1), the standard error is 0.14 resulting in a t-value of 2.26 (this would be for a t-distribution). Since, however, for linear mixed models the underlying distribution is not known, we also added the bootstrapped confidence interval to better assess if a significance for a certain predictor could be established. Abbreviations: SE = standard error, CI = confidence interval, SCALE = Selective Control Assessment of the Lower Extremity, GMFCS = Gross Motor Function Classification System.
Figure 5
Figure 5
Linear mixed model results of the upper extremities. Linear mixed models and violin plots combined with box plots displaying the accuracy and involuntary movement outcomes of all upper extremity joints individually. Marginal R2 describes how much variance is accounted for by the fixed effects and conditional R2 by the total model. R2 change indicates how much the marginal R2 increased when adding the predictor to the model. Abbreviations: SE = standard error, CI = confidence interval, SCUES = Selective Control of the Upper Extremity, MACS = Manual Ability Classification System.

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