Quantifying Similarities Between MediaPipe and a Known Standard to Address Issues in Tracking 2D Upper Limb Trajectories: Proof of Concept Study.

ABSTRACT:

Background

Markerless motion tracking methods have promise for use in a range of domains, including clinical settings where traditional marker-based systems for human pose estimation are not feasible. Artificial intelligence (AI)-based systems can offer a markerless, lightweight approach to motion capture. However, the accuracy of such systems, such as MediaPipe, for tracking fine upper limb movements involving the hand has not been explored.

Objective

The aim of this study is to evaluate the 2D accuracy of MediaPipe against a known standard.

Methods

Participants (N=10) performed a touchscreen-based shape-tracing task requiring them to trace the trajectory of a moving cursor using their index finger. Cursor trajectories created a reoccurring or random shape at 5 diffe

SUBMITTER: Wagh V 

PROVIDER: S-EPMC11683656 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature