Measurement Systems and Applications Mariolino De Cecco Antonio Selmo Michele Confalonieri

M. De Cecco - Lucidi del corso di Measurement Systems and Applications

Measurement Systems and Applications

Mariolino De CeccoAntonio Selmo

Michele Confalonieri


Force Panel

The instrument employed


How its electronics work?[Antonio Selmo]

How its electronics work?[Antonio Selmo]

Design and purpose of the FP

[a couple of frontal lessons]

Design and purpose of the FP

[a couple of frontal lessons]

Measurements for Diagnostics

[study and identification of the HTF]

Measurements for Diagnostics

[study and identification of the HTF]

Principles of human diagnosis and rehabilitation

[doct Guandalini and Tomasi]

Principles of human diagnosis and rehabilitation

[doct Guandalini and Tomasi]

Achronims:Fprce Panel – FPHuman Transfer Function - HTF

Logic of the Course

Rehabilitation and its quantification (measure of indexes of performance)

[development of serious games with processing]


Application: identification of human transfer function for

dexterity assessment and serious games for

rehabilitation

Method: - study of touch technology

- study of signal analog elaboration and conversion- acquisition of human data

- signal processing

Course:- frontal lessons (few)

- exercitation with matlab- building of the application

with Processing- visit to a clinic

Exam:- oral discussion

- homework

Material of the course can be found at http://www.miro.ing.unitn.it

Organization and final examination


VERITAS Project

• Project number: 247765• Project acronym: VERITAS• Project full title: Virtual and Augmented Environments

and Realistic User Interactions To achieve Embedded Accessibility DesignS

• Site: http://www.veritas-project.eu/• Starting date: 1 January 2010• Duration: 48 Months

VERITAS is an Integrated Project (IP) within the 7th Framework Programme, Theme FP7-ICT-2009.7.2, Accessible and Assistive ICT


Design and purpose of the FP - VERITAS Project

Virtual and Augmented Environments and Realistic User Interactions To achieve Embedded Accessibility DesignS

Method

SP1: development of virtual users

SP2: development of the simulation platform

SP3: validation

OBJECTIVE develop virtual humans for accessibility design in virtual simulation of ICT and non ICT products

UNITN activities

Modeling

Measurement


• Systems developed:– Garment based Motion

Capture: Ga-MoCap

– Multi-axis load cell

– Force Panel

VERITAS Project - measurement systems developed


• Diagnostics by human dexterity estimation• Requirements:

– Measure position of the touch– Measure the applied force– Store the above for path and trajectories– Accuracy and sampling frequency able to reveal

human dexterity– Visual feedback

Idea: “Force Panel”– Display LCD– Touch panel– Force transducers

Design and purpose of the FP - requirements


Stato dell’arteTouch screen

LCD and cameras

Graph tablets

Design and purpose of the FP - state of the art


Stato dell’artejoystick Aptics devices and virtual

reality

Design and purpose of the FP - state of the art


Force Panel

Design and purpose of the FP - Design


Schema della struttura(disposizione dei vincoli)

Horizontal use Vertical use

= perpendicular to LCD= parallel to LCD

3 load cells



Tipologie di vincolo considerate– Spherical joints– wires

– wires

2 solutions !





Variante con teste a snodo

mechanical design: spherical joint


mechanical design: wires


mechanical design: wires constraints


mechanical design: wires constraints


Requirements:• No buckling• No finger force through the blues• Diameter 1 mm

Wires with load cell– Length 10 mm (due to physical constraints)

wires– Length 30 mm (FEM analysis → finger force < 0.3 %)

F

mechanical design: wires length


Lunghezza dei filihorizontal Vertical

Worst case for buckling Worst case for force leakage



• Critical length ≈ 65 mm• Force lost:

• Moments ≈ 10-3 – 10-6 Nm

Caso Errore lettura forza [%]

Worst case horizontal, l = 10 mm 2.41

Worst case vertical, l = 10 mm 2.50

Worst case for buckling, l = 10 mm 5.32



Worst case for buckling, l = 30 mm, e = 0.5 mm 0.23

Worst case for buckling, l = 30 mm, e = 1 mm 0.27



VGA

Force Conditio

ning

Force Conditio

ning

3 x ANALOG IN

USB

2 x DIGITAL OUT

Touch panel

Force sensors

µController

PC

2 x ANALOG IN

LCD

System design: overall layout


Touch position measurement circuit

A touch screen is a 2-dimensional sensing device constructed of 2 sheets of material separated slightly by spacers

A common construction is a sheet of glass providing a stable bottom layer and a sheet of Polyethylene (PET) as a flexible top layer

The 2 sheets are coated with a resistive substrate, usually a metal compound called Indium Tin Oxide (ITO). The ITO is thinly and uniformly sputtered onto both the glass and the PET layer

Tiny spacers are placed between the 2 sheets in order to prevent false touch

When the PET film is pressed the two resistive surfaces meet. This position can be read as illustrated in next slides


Indium tin oxide (ITO, or tin-doped indium oxide) is a solid solution of indium(III) oxide (In2O3) and tin(IV) oxide (SnO2), typically 90% In2O3, 10% SnO2 by weight. It is transparent and colorless in thin layers while in bulk form it is yellowish to grey. In the infrared region of the spectrum it is a metal-like mirror.

Indium tin oxide is one of the most widely used transparent conducting oxides because of its two chief properties:- its electrical conductivity - optical transparency



5 V

GND

VS - sense

€

R0

y

L€

R0

L − y

L

€

R0

x

L+ RT

€

VS = 5R0

yL

R0

yL

+ R0

L − yL

=5

Ly

Ly+

R0 is the total resistance of the substrateRT is the touch resistance



Reading the x coordinate is similar

Note that in the equivalent circuit there are capacitive effects that lead to a certain delay that usually is less than 10 ms



Electronics scheme


Alim. cella

Output cella

Alim. condiz. (± 15 V DC)

Circuito di condizionamento

Pre-Amplificazione e Filtro analogico

passa bassoBessel V ordine

Pre-Amplificazione e Filtro analogico

passa bassoBessel V ordine

DC / DCDC / DC

Alimentazione(12 V DC)

Cella di carico

Cella di carico

μCμCShift del segnale

(μC legge solotensioni positive)

Shift del segnale(μC legge solo

tensioni positive)AmplificazioneAmplificazione

Conditioning unit


Conditioning unit


Bessel lowpass 5° order

Gain and offset adjustment: Arduino reads only positive voltages (0 – 5 V)

Full Wheatstone bridge

Conditioning unit


RISPOSTA TEMPORALE AL GRADINO DEL FILTRO PASSA BASSO DEL 5° ORDINE (Risposta di Bessel con frequenza di taglio 1 kHz)

20s

50s

Tempo di assestamento

No sovraelongation

500 s

Conditioning unit


• Arduino UNO

X

Y

F1

F2

F3

Alimentazione lungo XAlimentazione lungo X

Attesa assestamento circuito RCAttesa assestamento circuito RC

Lettura valore XLettura valore X

Alimentazione lungo YAlimentazione lungo Y

Attesa assestamento circuito RCAttesa assestamento circuito RC

Lettura valore YLettura valore Y

Lettura valore F1Lettura valore F1



PCPC

Inizializzazioni(costanti, variabili e pin μC)

Inizializzazioni(costanti, variabili e pin μC)

sw design: embedded system


PIN per lettura XPIN per lettura X

TASK 2 – PC TASK 3 – PC

Ricezione dati ed applicazione modello di

taratura

Ricezione dati ed applicazione modello di

taratura

Gestione delle immagini in

relazione alle risposte di chi sta di fronte al

pannello

Gestione delle immagini in

relazione alle risposte di chi sta di fronte al

pannello

TASK 1 – Arduino

t assest. RCt assest. RC

Read XRead X

PIN per lettura YPIN per lettura Y

Read F1, F2, F3 nel t assest. RCRead F1, F2, F3 nel t assest. RC

Read YRead YInvio dati via RS-232Invio dati via RS-232

0

5

5.1

t [ms]

10.110.2

15.2

25.2

8

2 task paralleli su PC:- uno segue l’Arduino, - uno è indipendente

sw design: task analysis


Acquisition

• Inizializzazioni• Lettura RS-232• Riconoscimento stringa• Distinzione segnali• Eventuali operazioni di

filtraggio• Operazioni di taratura

Elaboration and graphical output

• Inizializzazioni• Attesa inizio

acquisizione• Calcolo della tara del

sistema• Elaborazione (gestione

delle immagini in relazione all’interazione con l’utente)

sw design: two independent tasks on the PC


1. Touch position (resistive touch)

2. Force (load cell)

3. Touch position (load cell)

Calibration


Force Panel - calibration


Measurement model:• Linear behaviour on both directions• No interactions

uncoupled modelling

yaym

xaxm

qymy

qxmx

+=+=xm [pixel]

ym [pixel]xm = f (xa)ym = f (ya)xm = f (xa)ym = f (ya)

xa [bit]

ya [bit]

calibration: position


• Non-linear behaviour for:– Touch position– Force

€

FT = Fii=1

3

∑

FT [bit]

Fm [N]Fm[N] = f (Fa , xm , ym)Fm[N] = f (Fa , xm , ym)

xm [pixel]

ym [pixel]

€

Fm = a+bxm + cym +dxm2 + exmym + fym

2 + gFT +hFT xm + iFT ym + jFT xmym

calibration: force


€



€

1 xm1 ym1 xm12 ... ... ... ... ... FT1xm1ym1

... ... ... ... ... ... ... ... ... ...

1 xmN ymN xmN2 ... ... ... ... ... FTN xmN ymN

⎡

⎣

⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥⋅

a

b

c

d

e

f

g

h

i

l

⎡

⎣

⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥

=

Fm1

...

FmN

⎡

⎣

⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥

For N measurements made in different positions and with different forces it is possible to build the following linear relation

Than, with a pseudoinverse computation, the 10 coefficients of the polynomial model are estimated

WORK IN CLASS Force Panel - calibration: force


€



€

1 xm1 ym1 xm12 ... ... ... ... ... FT1xm1ym1

... ... ... ... ... ... ... ... ... ...


⎡

⎣

⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥⋅

a

b

c

d

e

f

g

h

i

l

⎡

⎣

⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥

=

Fm1

...

FmN

⎡

⎣

⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥

The pseudoinverse computation gives the 10 coefficients of the polynomial model:

€

A ⋅x = b

€

x = AT ⋅A( )−1AT ⋅b

€

ATA ⋅x = ATb

€

ATA( )−1ATA ⋅x = ATA( )

−1ATb

NOTE: ATA is generally a square and full rank matrix



€




Files given:- read_float.m

How to use read_float :

jj = 1 ; % numero filefile = ['dati_celle_armon_', num2str(jj), '.txt'] ; dati = read_float(file, ',', ':') ;clc

Dati = cell2mat(dati);

% grammi -> NewtonDati(:,1) = Dati(:,1)*(9.81/1000) ;


% Data are saved on 9 files “dati_celle_armon_1…9.txt”As follows on columns:% 1 -> calibration load [g]% 2 -> x position [pixel]% 3 -> y position [pixel]% 4 -> load cell 1 (in alto) [N]% 5 -> load cell 2 (in basso a sx) [N]% 6 -> load cell 1 (in basso a dx) [N]% 7 -> load cell sum [N]



€



€

1 xm1 ym1 xm12 ... ... ... ... ... FT1xm1ym1

... ... ... ... ... ... ... ... ... ...


⎡

⎣

⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥⋅

a

b

c

d

e

f

g

h

i

l

⎡

⎣

⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥

−

Fm1

...

FmN

⎡

⎣

⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥=

ε1

...

ε N

⎡

⎣

⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥

chi2gof Chi-square goodness-of-fit test on the vector Performs a chi-square goodness-of-fit test for discrete or continuous distributions. The test is performed by grouping the data into bins, calculating the observed and expected counts for those bins, and computing the chi-square test statistic SUM((O-E).^2./E), where O is the observed counts and E is the expected counts. This test statistic has an approximate chi-square distribution when the counts are large.




Procedure:

1.With the pseudoinverse computation estimate the 10 coefficients of the proposed polynomial model taking one data file at your choice

2.Apply the estimated coefficients to the model to predict (validate) the model behaviour using a different data file

3.Analyse the residuals and the validation behaviour

4.Apply the chi2gof test to verify the randomness of the residuals

5.Try to choose different mathematical models and see how the chi2gof test performs


∑=

=3

1iiT FF

{ }

⎥⎥⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢⎢⎢

⎣

⎡

⎭⎬⎫

⎩⎨⎧

=

yx

yx

yx

yx

yx

Tm

m

Tm

m

Tm

m

Tm

m

Tm

m

Tm

m

Tm

mss

ee

dd

cc

bb

aa

F

F

F

F

F

F

F

F

F

F

F

F

F

Fyx 3121321

1

2 3

F1a [bit]

xm = f (F1a , F2a , F3a)ym = f (F1a , F2a , F3a)xm = f (F1a , F2a , F3a)ym = f (F1a , F2a , F3a)

F2a [bit]

F3a [bit]

xm [pixel]

ym [pixel]

Force Panel – calibration position


Resolution Accuracy

Position X [mm] < 0.40 ± 1.80 (al 95%)

Position Y [mm] < 0.30 ± 1.80 (al 95%)

Force [N] < 0.05 ± 0.10 (al 95%)

Time [ms] 10 ± 5

Nail Finger finger horizontal

Yellow: resistive touchBlue: load cell reconstruction

Force Panel – calibration position


Documents

Measurement Systems and Applications Mariolino De Cecco Antonio Selmo Michele Confalonieri