Electronic biomedical dynamometer developed with metalon structure for measurement, analysis and recording of gripping force information
International Journal of Development Research
Electronic biomedical dynamometer developed with metalon structure for measurement, analysis and recording of gripping force information
Received 03rd February, 2019; Received in revised form 19th March, 2019; Accepted 03rd April, 2019; Published online 29th May, 2019
Copyright © 2019, Josivaldo G. Silva et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The developed electronic biomedical dynamometer was able to measure palmar grip strengths and varying forces over time produced by grip forces ranging from 5 N to 1000 N. This dynamometer has a very affordable mechanical structure, compact signal conditioning circuit and microcomputer. The mechanical structure consists of a dynamic support developed in Metalon and a static support also developed in Metalon. In addition, there is a support attached to the dynamic structure that was developed in Acrylic to accommodate the fingers of the hand and other support that was fixed to the static structure that developed in Acrylic to accommodate the palm of the hand. Between the dynamic structure and the static structure was installed a dynamometric ring containing extensometers (Kyowa) that were connected in Wheatstone Bridge and produce electric voltage proportional to the grip force applied between the supports. The electrical voltage produced by the Wheatstone Bridge is subjected to the signal conditioning circuit which amplifies, filters and produces an electrical voltage of the receiver, which is connected to a data acquisition board which converts that analog signal into a digital signal which is sent to the microcomputer to perform the processing by means of an interface developed with the Labview software to plot the behavior. graphs and generate analysis of forces applied over time and obtain fast and slow components of muscle strength, produces information that aid in medical diagnosis and can be stored in a database.