Evaluating upper limb movement smoothness metrics derived from markerless 3D motion tracking in children with neurological disorders

 If this doesn't get in your hospital in the next month to objectively determine your recovery protocol needs; THEN EVERYONE IS MASSIVELY INCOMPETENT!

You need to get them all fired and the hospital reconstituted! Obviously no one in your hospital has any brains at all if this doesn't immediately trigger; 'Let's get this for stroke rehab.'

Evaluating upper limb movement smoothness metrics derived from markerless 3D motion tracking in children with neurological disorders

• Nikolas Hesse,
• Jan Lieber &
• Hubertus J. A. van Hedel 

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Abstract

Background

Clinical assessment of movement smoothness during reaching in children is often based on subjective, ordinal-scaled therapist ratings. Markerless 3D motion tracking using an RGB-D camera offers a promising avenue for more objective and fine-grained smoothness evaluation. This study investigated the use of a new markerless RGB-D-based tracking method, SMPLify-KiDS, for the quantitative assessment of upper limb movement smoothness in a heterogeneous population of children with neurological impairments.

Methods

Thirty-eight children with neurological diagnoses performed three reaching tasks from the Melbourne Assessment 2 (MA2) MA2 with their more affected arm while being recorded with an RGB-D camera. Upper limb kinematics were extracted using SMPLify-KiDS, and two widely used smoothness metrics—the log dimensionless jerk (LDJ) and the modified spectral arc length (SPARC)—were computed. The same movement sequences were independently scored by two therapists according to MA2 guidelines. Correlations between quantitative smoothness metrics and therapist scores were evaluated using Spearman’s rank correlation coefficient, and smoothness metric differences between ordinal therapist score levels were analyzed using non-parametric statistical tests for individual items and averaged values.

Results

Quantitative smoothness metrics showed moderate to strong correlations with therapist scores per item (for LDJ:0.666 ≤ p ≤ 0.836; for SPARC:0.556 ≤ p ≤ 0.674  ), and very strong to excellent correlations for averaged values (for LDJ: p= 0.843, for SPARC:p= 0.755). Both metrics revealed statistically significant differences between ordinal therapist score levels, and LDJ strongly correlated with task duration.

Conclusions

Smoothness metrics derived from markerless RGB-D motion tracking are able to discriminate between clinically assigned smoothness levels in children with neurological impairments. LDJ showed closer alignment with therapist scores than SPARC, potentially due to its relationship with movement duration—a factor that also appears relevant to clinical perception of smoothness. These findings support the integration of markerless motion capture into clinical assessments to provide objective, quantitative, and fine-grained information on movement quality, complementing established therapist-based evaluations.