Literature DB >> 33567769

Hand Motion Capture from a 3D Leap Motion Controller for a Musculoskeletal Dynamic Simulation.

Robin Fonk1, Sean Schneeweiss1, Ulrich Simon1, Lucas Engelhardt1.   

Abstract

The AnyBody Modeling System™ (AMS) is a musculoskeletal software simulation solution using inverse dynamics analysis. It enables the determination of muscle and joint forces for a given bodily motion. The recording of the individual movement and the transfer into the AMS is a complex and protracted process. Researches indicated that the contactless, visual Leap Motion Controller (LMC) provides clinically meaningful motion data for hand tracking. Therefore, the aim of this study was to integrate the LMC hand motion data into the AMS in order to improve the process of recording a hand movement. A Python-based interface between the LMC and the AMS, termed ROSE Motion, was developed. This solution records and saves the data of the movement as Biovision Hierarchy (BVH) data and AnyScript vector files that are imported into the AMS simulation. Setting simulation parameters, initiating the calculation automatically, and fetching results is implemented by using the AnyPyTools library from AnyBody. The proposed tool offers a rapid and easy-to-use recording solution for elbow, hand, and finger movements. Features include animation, cutting/editing, exporting the motion, and remote controlling the AMS for the analysis and presentation of musculoskeletal simulation results. Comparing the motion tracking results with previous studies, covering problems when using the LMC limit the correctness of the motion data. However, fast experimental setup and intuitive and rapid motion data editing strengthen the use of marker less systems as the herein presented compared to marker based motion capturing.

Entities:  

Keywords:  AMS; anybody modeling system; bvh; hand motion; leap motion controller; motion capture; musculoskeletal hand model; range of motion

Mesh:

Year:  2021        PMID: 33567769     DOI: 10.3390/s21041199

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  3 in total

1.  Arm Movement Analysis Technology of Wushu Competition Image Based on Deep Learning.

Authors:  Xiaoou Zhang; Xingdong Wu; Ling Song
Journal:  Comput Intell Neurosci       Date:  2022-08-12

Review 2.  Leap Motion Controller Video Game-Based Therapy for Upper Extremity Motor Recovery in Patients with Central Nervous System Diseases. A Systematic Review with Meta-Analysis.

Authors:  Irene Cortés-Pérez; Noelia Zagalaz-Anula; Desirée Montoro-Cárdenas; Rafael Lomas-Vega; Esteban Obrero-Gaitán; María Catalina Osuna-Pérez
Journal:  Sensors (Basel)       Date:  2021-03-15       Impact factor: 3.576

3.  Hand Measurement System Based on Haptic and Vision Devices towards Post-Stroke Patients.

Authors:  Katarzyna Koter; Martyna Samowicz; Justyna Redlicka; Igor Zubrycki
Journal:  Sensors (Basel)       Date:  2022-03-07       Impact factor: 3.576

  3 in total

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