scholarly journals Data Acquisition System and Pattern Image Generations for Hand Grip Device

Author(s):  
Ming-Horng Wong ◽  
Boon-Chin Yeo ◽  
Poh-Kiat Ng ◽  
Wei-Jun Choong

Grip pattern is essential to understand how an object being held in hand. One of the solutions is to use the pressure sensing glove to capture the gripping pressure distributed on the surface of the palm. The objective of this project is to develop a data acquisition system for a gripping device that can capture the grip patterns when a person is gripping an object. The design comprises of Velostat sheet, rows, and columns of conductive threads, that are sandwiched and layered to form a glove with pressure sensor grids. Arduino is used to generate the signals for data acquisition and interface with the MATLAB program through serial communication. On the MATLAB, the sensor data are organized and represented in hand pattern color image. Voltage Divider Rule (VDR) was used in an experiment with different resistor values and the effect of the image patterns were observed. Another experiment has been designed to find out the grip consistency. The results show that resistor values 330ohm can cause the image pattern create noises. Meanwhile, 4.7kohm resistance value is sufficient to eliminate most of the noises made in the pattern images. In this paper, different grip images can be obtained from different grip activities, such as holding toothbrush, lifting dumbbell, and pressing syringe. Future works can be done in resolution improvement and grip pattern recognition.

Author(s):  
Yucheng Liu ◽  
Andrew Le Clair ◽  
Matthew Doude ◽  
V. Reuben F. Burch

A data acquisition system along with a sensor package was designed and installed on an existing mechanically-controlled system to gather more data on their usage patterns. The data collected through the developed system include GPS route, vehicle speed and acceleration, engine state, transmission state, seat occupancy, fuel level, and video recording. The sensor package was designed and integrated in a way that does not interfere with the driver’s operation of the system. Cellular network connectivity was employed to retrieve sensor data so as to minimize human effort and maintain typical usage patterns of the outfitted systems. Testing and validation results showed that the developed system can correctly and effectively record data necessary for further analysis and optimization. The collected data will significantly promote system activity simulations in order to facilitate optimizing work flow at large industrial facilities and improving energy efficiency.


Sign in / Sign up

Export Citation Format

Share Document