Journal of Neuroscience Methods, 1 (1979) 201--204 © Elsevier/North-Holland Biomedical Press

201

A VERSATILE PHYSIOLOGICAL DATA ANALYSIS SYSTEM USING AN I N T E L 8080 MICROPROCESSOR

D. Hyde, E.G. Nice, P.J. Oakley Faculty of Science, Science Laboratories, South Road, Durham DHI 3LE, U.K. ABSTRACT A microprocessor based physiological data processor has been realised. The system controls the data flow from physiological experiments and performs on-line mean and variance calculations with an output in graphical form. The analyser accepts one data point every 0.5 ms and has a capacity of 128 records each containing 800 data points.

Post stimulus histogram and inter-

val histogram analysis programs have also been written and implemented. 1. Introduction Many physiological experiments require data averaging in order to obtain either an acceptable signal to noise ratio or the average response to an external stimulus.

At present two distinct but expensive solutions to this

problem are favoured.

On-line data processing has been performed with a

central computer in a time sharing mode.

Alternatively some research work-

ers have preferred to use dedicated on-line mini computers to undertake the tasks of data gathering and reduction.

A third possibility has emerged

with the availability of microprocessors and their ancillary components. This strategy allows, we believe, a cheap but flexible solution to the problem of signal averaging in the physiological domain.

A versatile data

processing system using an Intel 8080 microprocessor will now be described in which system storage is kept to a minimum. 2. Theoretical basis The normal expressions for the mean and the variance are shown in equaN (I) and (2) ~ xi(t ) (~) x(t) i=1

tion

L

and

o2t

(xlt i=!

x t)2 N

where N is the number of records and x(t) is the mean and a2(t) is the variance.

202

The second equation makes it necessary to calculate the m e a n before any calculation of the variance can be attempted.

This is an unacceptable

approach for a small system as it requires complete storage of the input data.

However,

alternative

for machine implementation.

forms of equation

(2) are much more suitable

Thus expanding and collecting terms e q u a t i o n

(3) emerges:

2 2 O

(t) .

~ .~.W. i= 1

x I (t) . . N

This e x p r e s s i o n o n l y r e q u i r e s the storage of

--2 x(t)

'running'

(3)

totals and is there-

fore ideal for'a low cost data p r o c e s s i n g system. 3. S y s t e m Structure and l]rogramminq Signal to noise p r o b l e m s are common in the p h y s i o l o g i c a l data p r o c e s s i n g field where small

(~V size)

signals are e n c o u n t e r e d in extra c e l l u l a r re-

cordings or, high noise levels are seen in i n t r a - c e l l u l a r records signals)

(mY size

made through high resistance microelectronics.

The input signal is p a s s e d through a p r e - f i l t e r to remove excess noise and then d i g i t i z e d to an accuracy of 0.4% of F.S.

(8 bits).

The input is

sampled regularly and 800 data points are taken on each record.

Internally

the p r o g r a m stores the running totals using 5 bytes per data point.

Thus

4000 b y t e s of read-write memory are required for data storage and the a d d i t i o n a l 96 bytes are available for temporary storage

(see Figure

I).

Y1

o Y2 P

cess

X

/]_ Start o

4 K byte Figure I

203

The program copes with DC drift by a digital level shift calculated from the first point on each record.

High frequency noise was reduced by pre-

filtering and is further reduced by the averaging process. The microprocessor program was written in 8080 assembler code using structured programming techniques where all major components of the program are written as separate modules

(see Figure 2).

The speed of the program

is predominantly determined by the time taken to calculate the "running" sum of squares as this proved to be the most complex operation. START

Zx

÷

¢

Zx 2 ÷

R÷

R + i I

t÷~

t÷¢

READ : N

i READ : DC Levell

Calc:

t

x(t)

i

2 (t)

÷ (7"x t)--2

x(t)

N

Correct : Drift t Calc. : ~- x(t) i :

~x(t) N

i

x(t) 2

NO

t : ~- x(t) 2 1

I I t÷t÷l

J

I Display

]

x(t), (~2(t) vs t

Figure 2

R:= No.of Records taken N:= No. to be taken

204

It was r e a l i s e d

that a r e l a t i v e l y

effort would greatly histogram

and interval

read o n l y memory. loscope

extend

analysis

In a d d i t i o n

and an X-Y p l o t t e r

routine.

Correlation

small

the useful

programs an o u t p u t

was d e v e l o p e d

and F o u r i e r

amount of a d d i t i o n a l

range of the system. were written display

and loaded

routine

into the

for b o t h an oscil-

and i n c o r p o r a t e d

analysis

programming

Post stimulus

are c o n s i d e r e d

as a common feasible

but are

n o t yet implemented. 4. S y s t e m p e r f o r m a n c e The o v e r a l l physiological

and a c c u r a c y

s y s t e m was

found to be very r e l i a b l e

data a v e r a g i n g

system was r e a l i s e d

in m a n y d i f f e r e n t

on a d e v e l o p m e n t

system

and p r o v i d e d

useful

types of experiment.

for d e b u g g i n g

The

and data valida-

tion purposes. The

system performance

and the m a x i m u m modifications maximum

to e a c h p r o g r a m

data rates w e r e

averaging

and

using

to remove

The a c c u r a c y

quite

used.

adequate

I data p o i n t

square wave

techniques

syncronisation.

in 0.55 ms for the

to function

is g o v e r n e d

hence

system will provide

were

functions,

at the p r e d i c t e d

by the input d a t a a n d the

is 8 b i t s or 0.4% w h i c h

for m o s t p h y s i o l o g i c a l

facilities

simple The

s y s t e m structure.

The input a c c u r a c y

128 records,

The d i s p l a y

but a d e d i c a t e d

external

p r o g r a m was not able

of the c a l c u l a t i o n s

is able to cope w i t h 11.3 times.

simple

in 152 ~s for b o t h the h i s t o g r a m

in 0.5 ms due to the d e v e l o p m e n t

n u m b e r of records believed

tested

found to be

I data p o i n t

the m e a n and v a r i a n c e i point

was

data rates of e a c h p r o g r a m w e r e m e a s u r e d by m a k i n g

applications.

decreasing

is

The p r o g r a m

the e r r o r by

~

or

limited b y the d e v e l o p m e n t

12 b i t a c c u r a c y

(0.025%)

system

on all o u t p u t s

5. C o n c l u s i o n It has b e e n shown physiological tent results cost pares

signals

that low cost m i c r o p r o c e s s o r s under a w i d e

of a h i g h q u a l i t y

(of components) favourably

of the p r o g r a m s

with

with

of a d e d i c a t e d

can a d e q u a t e l y

range of conditions, little

effort.

The c u r r e n t

s y s t e m is £1500

(Jan 1979)

the cost of other p h y s i o l o g i c a l

are a v a i l a b l e

producing

process consis-

estimated which

equipment.

com-

Copies

from the authors.

( Received November

9th,

( Accepted

13th,

February

1978 1977

) )