Identification of Object Dynamics Using Hand Worn Motion and Force Sensors

Area of Science:

• Biomedical Engineering
• Human-Computer Interaction
• Robotics

Background:

• Microelectromechanical system (MEMS)-based sensors are increasingly used for on-body measurements.
• Fingertip-sized tri-axial force sensors enable measurement of human hand-object interaction forces.

Purpose of the Study:

• To develop a novel prototype device for simultaneous 3D force and movement measurements at the finger and thumb tips.
• To investigate the potential of combining interaction forces and movement data for identifying object dynamical characteristics.
• To quantify human hand interactions with environmental objects.

Main Methods:

• Development of a new prototype device integrating 3D force and movement sensing at the fingertips.
• Experimental setup involving subjects manipulating mass and spring objects under varying conditions.
• Data analysis to identify and estimate object properties such as weight and spring constant.

Main Results:

• Successful estimation of the weight for two mass objects (0.44 kg with 29.3% ± 18.9% error and 0.28 kg with 19.7% ± 10.6% error).
• Accurate estimation of the spring constant for a physical spring object (16.3% ± 12.6% error).
• Demonstration of the system's capability to quantify hand-object interactions.

Conclusions:

• The developed system represents a significant advancement in quantifying hand-environment interactions.
• The device shows potential for applications in rehabilitation, ergonomics, and sports science.
• Simultaneous measurement of 3D forces and movements provides valuable insights into object manipulation and identification.