Disease Detection Using Bio robotics


About

In order to measure quantitatively the neuro-psychomotor conditions of an individual with a view to subsequently detecting his/her state of health, it is necessary to obtain a set of parameters such as reaction time, speed, strength and tremor. By processing these parameters through the use of fuzzy logic it is possible to monitor an individual's state of health, .i.e. whether he/she is healthy or affected by a particular pathology such as Parkinson's disease, dementia, etc. The DDX control system consists of a small board with an internal fuzzy microcontroller that acquires, through the action on a button on the joystick, some important parameters:  reaction time, motion speed, force of the finger on the button, and tremor and analyses them by fuzzy rules in order to detect the patient’s disease class. Moreover this new device also includes a system to detect vocal reaction. The resulting output can be visualized through a display or transmitted by a communication interface.

Background

Reaction time, speed, force, and tremor are parameters that are used to obtain a quantitative instrumental determination of a patient’s neuro-psychophysical health. These parameters have been used in the study of the progression of Parkinson’s disease, a particularly degenerative neural process, but these parameters can also be useful in detecting the wellness of a healthy person. As a matter of fact, these measurements turn out to be an excellent method of finding reactive parameters alteration due not only to a pathology, but also, for example, to the use of drugs, alcohol, drugs used in the treatment of mental conditions, or other substances that could affect a person’s reactive and coordination capabilities.

Moreover, for a healthy person, a continuous health monitoring turn out to be an excellent prevention system of some pathology and is an excellent method to acquire consciousness of how lifestyle and behavior have repercussions on one’s psychophysical well-being.


The New Experimental System (Ddx)

DDX is the new experimental bio-robotic system for the acquisition and restitution of human finger movement data. It is a bio-robotic system designed and constructed with medical and clinical data for the analysis of Parkinson’s disease. It was originally used for the analysis of neural disturbances with quantitative evaluation of both the response times and the dynamic action of the subject.

Software

By pressing the button, three beacons are sent, signifying, respectively, beginning pressure, race end, and force. First, the processor sends an impulse (like a warning) to the buzzer, and the timer starts. It begins the sampling and, after a random interval, sends another impulse to the buzzer (in order to obtain the starting signal). The value of the timer is stored in to tj. When the patient has pressed the push button, a beginning pressure beacon is sent, and the value of the timer is assigned to ti  This time is what we call the “Reaction Time”. At the end of the movement stroke, an end-of-race beacon is sent, and the value of the timer is assigned to tf. The speed of patient motion can be calculated from these times. When the stroke ends, the pressure is calculated using a simple circuit based on a strain gauge, a filter, an amplifier and an analog to digital (A/D) converter. Tremor is measured by a routine that reads data from the switching accelerometer on an input/output (I/O) pin.

Abstract

This seminar deals with the design and the development of a bio-robotic system based on fuzzy logic to diagnose and monitor the neuro-psychophysical conditions of an individual. The system, called DDX, is portable without losing efficiency and accuracy in diagnosis and also provides the ability to transfer diagnosis through a remote communication interface, in order to monitor the daily health of a patient.

Conclusions


In this article, an innovative bio-robotic system for neuro-psychophysical health-condition detection is presented. Today, systems of detection are very reliable but not portable and do not generally allow diagnoses to be sent via the internet.


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