# From RGB-D to RGB-Only: Reliability and Clinical Relevance of Markerless Skeletal Tracking for Postural Assessment in Parkinson’s Disease

## TL;DR

This study compares RGB-D and RGB-only systems for tracking posture in Parkinson’s patients, finding that simpler RGB-only models can be reliable and clinically useful.

## Contribution

The study demonstrates that low- and medium-complexity RGB-only models can reliably replace RGB-D sensors for postural assessment in Parkinson’s Disease.

## Key findings

- Low-complexity RGB-only models showed high congruence with RGB-D systems for trunk and shoulder alignment.
- Sagittal angles tracked via lateral views correlated with motor complications and gait freezing severity.
- Both RGB-only and RGB-D systems effectively distinguished postural severity clusters in Parkinson’s patients.

## Abstract

Axial postural abnormalities in Parkinson’s Disease (PD) are traditionally assessed using clinical rating scales, although picture-based assessment is considered the gold standard. This study evaluates the reliability and clinical relevance of two markerless body-tracking frameworks, the RGB-D-based Microsoft Azure Kinect (providing the reference KIN_3D model) and the RGB-only Google MediaPipe Pose (MP), using a synchronous dual-camera setup. Forty PD patients performed a 60 s static standing task. We compared KIN_3D with three MP models (at different complexity levels) across horizontal, vertical, sagittal, and 3D joint angles. Results show that lower-complexity MP models achieved high congruence with KIN_3D for trunk and shoulder alignment (ρ > 0.75), while the lateral view significantly improved tracking of sagittal angles (ρ ≥ 0.72). Conversely, the high-complexity model introduced significant skeletal distortions. Clinically, several angular parameters emerged as robust metrics for postural assessment and global motor impairments, while sagittal angles correlated with motor complications. Unexpectedly, a more upright frontal alignment was associated with greater freezing of gait severity, suggesting that static postural metrics may serve as proxies for dynamic gait performance. In addition, both RGB-only and RGB-D frameworks effectively discriminated between postural severity clusters. While the higher-complexity MP model should be avoided due to inaccurate 3D reconstructions, our findings demonstrate that low- and medium-complexity MP models represent a reliable alternative to RGB-D sensors for objective postural assessment in PD, facilitating the widespread application of objective posture measurements in clinical contexts.