Journal of neuroengineering and rehabilitation · 2026
Evaluating upper limb movement smoothness metrics derived from markerless 3D motion tracking in children with neurological disorders.
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Hesse Nikolas, Lieber Jan, van Hedel Hubertus J A
Аннотация
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: [Formula: see text]; for SPARC: [Formula: see text]), and very strong to excellent correlations for averaged values (for LDJ: [Formula: see text], for SPARC: [Formula: see text]). 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.
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: [Formula: see text]; for SPARC: [Formula: see text]), and very strong to excellent correlations for averaged values (for LDJ: [Formula: see text], for SPARC: [Formula: see text]). 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.