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

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1199
Author(s):  
Robin Fonk ◽  
Sean Schneeweiss ◽  
Ulrich Simon ◽  
Lucas Engelhardt

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.

2015 ◽  
Vol 27 (1) ◽  
pp. 103-104
Author(s):  
Jörg Güttler ◽  
◽  
Dany Bassily ◽  
Christos Georgoulas ◽  
Thomas Linner ◽  
...  

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270001/12.jpg"" width=""300"" />Gesture based validation</div> A light weight robotic arm (Jaco) has been interfaced with a novel gesture detection sensor (Leap Motion Controller), substituting complicated conventional input devices, i.e., joysticks and pads. Due to the enhanced precision and high throughput capabilities of the Leap Motion Controller, the unobtrusive measurement of physiological tremor can be extracted. An algorithm was developed to constantly detect and indicate potential user hand tremor patterns in real-time. Additionally a calibration algorithm was developed to allow an optimum mapping between the user hand movement, tracked by the Leap Motion Controller, and the Jaco arm, by filtering unwanted oscillations, allowing for a more natural human-computer interaction. </span>


Sign in / Sign up

Export Citation Format

Share Document