Body Mass Index LabView Program

2012-01-04T11:20:00.000-08:00

LABVIEW PROGRAM FOR BODY MASS INDEX

OLATUNDE G. A. AND HEHAR G. S.

SUBMITED TO

DR. Timothy McDonald

FUNDAMENTAL OF INSTRUMENTATION IN BIOSYSTEMS ENGINEERING

Auburn University

DECEMBER 2011

1.0 INTRODUCTION

Instrumentation is based on the principle and operation of measuring instruments that are used in design and configuration of automated systems. Instrumentation typically includes automated processes which are mainly focusing on the improving of system productivity, reliability, safety, optimization, and stability. To control the parameters in a process or in a particular system, devices such as microprocessors, various analog and digital sensors, programming but their ultimate aim is to control the parameters of a system.

Fundamentals of instrumentation and control engineering applied in biological and agricultural systems and processes include time-domain analysis and frequency response methods. Sensors and actuators in feedback control systems. The application in the biosystem engineering includes various sensors and equipment for precision agriculture, development of the automated gasifiers and pyrolysis systems in bioenergy, instruments to control the irrigation, food processing, food machinery, packaging, ingredient manufacturing and control.

The course exposed us to basic of instrumentation in the Biosystem Engineering and how they are used to develop basic theoretical programs and their practical application to various issues in design, signal conditioning, analog devices, data acquisition and sampling, and sensor applications. The laboratory provide hands on experience with instrumentation equipment such as oscilloscopes, data acquisition boards, bread boarding circuits, and other equipments for practical. Additionally the course introduced students to C++, LabVIEW, Electronic WorkBench, and Matlab applications in instrumentation. The practical sessions provided student with opportunity to explore and learn at one's own initiative and assistance from the coordinator

LabVIEW has been used for the basic concepts and practice of data acquisition, and more generally, instrumentation, to undergraduate, graduate, postgraduate engineering students for their projects. The number of students who are using LabVIEW has been gradually increased.

Currently, LabVIEW is focusing on the data acquisition systems: this includes simple chart recordings, through systems based on programs written in the C programming language, to recent systems built with LabVIEW. It is the intention that all engineering students should have a basic knowledge of modern data acquisition with experience on LabVIEW. The graphical programming environment of LabVIEW is suitable for students to understand basic concepts of loops, case structures, etc., in a short period and to generate working programs.

2.0 Problem statement

Body Mass Index (BMI) now appears to be a widely accepted index for classifying adiposity in children and adults, however, most medical practitioners still use old method which involves using a weighing machine and height measuring equipment especially meter rule and the index computations are manually done and presented to the patient. Measurement error and sometimes human error result in wrong computation with its attendant consequences. The precision and accuracy of the BMI index will assist the patient in proper classification of his body fat and assist the medical personnel in proper diagnosis and drug prescription. Therefore the need to develop automated equipment that will acquire the weight and the height and perform the computations that are needed and present the result to the patient in hard of soft copy and in very short time and with high degree of precision and accuracy.

2.1 Proposed solution

2.1.1 Sensors required

1. Distance analog ( QT50ULB U-Gage)

2. Weight sensor U3L Load cell, SER NO 222555, Capacity 10000

2.1.2 Calibration of sensor

The distance measurement sensor and the weight measurement sensor have their outputs in voltage thus the need to find the relationship between the voltage and the measured quantities. About four sample data each were used for the two sensors, regression analysis was carried out and the regression equations was estimated as shown in graph 1 and 2.

2.2 Flow chart for the proposed solution

Graph 1: regression analysis of voltage against height

Graph 1: regression analysis of voltage against weight

2.3 Program overview

The program was divided into three time frames as listed below (plate 1):

Time frame 1: the start button: the operator is expected to click on start button to tell the program to run

Time frame 2: the program acquired voltage measurement from the sensor (Weight and height measurement sensors). About 20 samples shall be acquired and send to the next phase

Time frame 3: the average of the voltages shall be estimated and converted to real mass (pound) and height (inches) through regression analysis equation. The body mass index is estimated through equation one. The result is presented on a scale visible to the operator.

2.4 Program from LabView

Plate 1: Block diagram showing the program equations and flow

Plate 2: Presentation of result output

Result and discussion

Six samples were taking from six different people. The result of the average BMI index from the program were compared with manual computations, the estimated error is presented. The error is 2.06 which is small/low which indicate a good prediction.

	BMI Reading 1	BMI Reading 2	BMI Average	Estimated BMI from formula	Error	Avg. Error
1	25.604	25.554	25.579	27.5	1.921	2.062875
2	23.8727	25.866	24.86935	27.5	2.63065
3	24.429	23.986	24.2075	26.5	2.2925
4	24.153	24.1256	24.1393	26.5	2.3607
5	26.1439	26.3863	26.2651	27.85	1.5849
6	26.243	26.282	26.2625	27.85	1.5875

BMI index using Labview program

Body Mass Index LabView Program