multisensor systems & ambient assisted living (aal) · •indoor localization ......

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a

Università Degli Studi di Catania

Multisensor Systems & Ambient Assisted Living (AAL)

DIEEI

Department of Electrical, Electronic and Information Engineering University of Catania – Italy

14-01-2015

Cristian Orazio Lombardo [email protected]

Technologies

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Progressive increase in the average age of the population. Over the last 50 years, the number of older persons worldwide has tripled - and will more than triple again over the next 50-year period as the annual growth of the older population (1.9%) is significantly higher than that of the total population (1.02%). The European Commission has predicted that between 1995 and 2025 the UK alone will see a 44% rise in people over 60.

THIS SITUATION ASKS FOR NEW SOLUTIONS TOWARDS IMPROVING THE INDEPENDENCE, THE QUALITY OF LIFE, AND THE ACTIVE AGEING OF OLDER CITIZENS.

Need to find new models of intervention involving a plurality of actors according to the logic interdisciplinary

New advanced, reliable and socially acceptable ICT services to cope the additional costs of the welfare state that we will face in the years to come

Why?

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


OBJECTIVES:

• Extend the period in which people can live in their preferred environment by

increasing their autonomy, self-sufficiency and mobility;

• Keep health and functional capacity of the elderly;

• Increase safety, prevent social exclusion

• Support workers, family members and organizations of care;

AAL is not just technology, it requires collaboration and effective communication between stakeholders:

RESEARCHERS, PLANNERS, INDUSTRY, USERS, ADMINISTRATORS, SOCIAL WORKERS AND HEALTH CARE

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


What we want to be preserved and guaranted!!!

Smart&Authonomous Sensing Systems @SensorLab

DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

WSN & Multi-sensor systems

• IMU • Indoor localization • Haptic assistive systems • Weak people monitoring (ADL) • Cognitive Sensor network • Hazards monitoring

•Sensor data fusion PCA, Rock Curves, Neuro-Fuzzy,

Kalman Filter, Dythering, Wavelet

•Sensor Networks

•Advanced readout

Methodologies

Ambient Assisted Living@SensorLab

Resima

•Multisensor platforms

•Customized Solutions

•Customized WSN

•Smart Phone

•Embedded Systems

•Microcontroller Systems

•Microprocessor Systems

Technologies


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

Systems for the Active Ageing and Visually Impaired People

Smartphone based solutions

Customized architectures


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

System specifications

Sensitivity to a large set of colours

Clustering features of similar tone of colours

Light Green Dark Green Green

GOAL: To identify color of the different materials to provide blind user with

an improved informations about environment.


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

GOAL: A Smart multi sensor strategy to assist blind people in navigation


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

GOAL: User tracking in indoor and outdoor structured environment

RFID Receiver Floor with passive tags


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

GOAL: To reproduce the real feeling provided by a traditional white cane.

ADVANTAGES : Natural codification, no physical interaction.

Methodology and solutions • Vibration motors positioned on the handle reproduce the “bump” feelings. • An inclinometer is used to measure the cane tilt • A ultrasound sensor measures the distance from the obstacles


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

Improving the perception of weak signals by added noise


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

The effect of background noise


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

The effect of contour noise


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

[kg]

Goal: Development of a low cost, low power, minimally invasive sistem for fall detection, posture and activity rate monitoring

Sensor: Accelerometer

ACTIVITY / INACTIVITY

Each phase of the Fall Dynamic Behaviour has to be checked in time and amplitude


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

Systems for the Active Ageing and Visually Impaired People

Smartphone based solutions

Customized architectures


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

Methodology • Multisensory datafusion • Multi-feedback approach • Fall Detection • Fall typology Identification • Feedback evaluation • Skill monitoring • Smart processing • Activity rate monitoring • Scheduled Monitoring • Event Triggered Monitoring • Autonomous • Caregivers alerting

Goal: Development of a platform for fall detection, cognitive capability monitoring and activity rate

Technology • Low cost custom module • Customized App • Inertial Sensors • Bluetooth Communication

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


Regione Siciliana ASSESSORATO REGIONALE DELLE ATTIVITA’ PRODUTTIVE

AVVISO PUBBLICO PER LA CONCESSIONE DELLE AGEVOLAZIONI IN FAVORE DELLA RICERCA, SVILUPPO ED INNOVAZIONE PREVISTE DALL’ART 5 DELLA LEGGE REGIONALE 16.12.2008, N. 23

Linea di intervento 4.1.1.1 - POR FESR Sicilia 2007-2013

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Env . quantities Compass, a x , a y , a z

d i

Pre-processing&Elaboration algorithms

User Inertial Trilateration Env . status

User - Environment Interaction

User - Environment Contextualization

Environment Info

Decision Support System

User skill

Message Center

Supervisor GUI

User

x

z

y

RESIMA: a new WSN based paradigm to assist weak people in indoor environment

GOAL: Provide the user with a smart form of indoor assistance (safety and efficient site exploration/exploitation) by: •awareness of User-Environment Contextualization …the user status related to the environment status •awareness of User-Environment Interaction …physical interaction between user and environment

Target Users • Visually Impaired • Weak users (e.g. elderly)

Advantages • To provide high level form of information to users and caregivers • Spatial and temporal continuous form of assistance • Low costs, easy installation & maintenance • Low impact on the pre-existing environment

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Env . quantities User: , di, a x , a y , a z

Pre-processing&Elaboration algorithms

User Inertial Trilateration Env . status

User - Environment Interaction

User - Environment Contextualization

Environment Info

Decision Support System

User skill

Message Center

Supervisor GUI

User

x

z y

•Multisensor nodes •Inertial Unit •Coupled US distance sensors

•User position •Environment safety •User behaviour

•Candidates messagges for the User •User/env representation for the supervisor •Messagges for the User

•Suggested actions for the supervisor

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


IRIS Features

Frequency band: 2405 MHz to 2480 MHz ISM band

Transmit (TX) data rate: 250 kbps

RF power: 3 dBm (typ)

Receive Sensitivity: -101 dBm (typ)

Outdoor Range: > 300 m

Indoor Range: > 50 m

Current Draw: 16 mA (Receive mode)

IEEE 802.15.4 compliant RF transceiver

Battery 2X AA batteries Attached pack

External Power 2.7 V - 3.3 V Molex connector provided

User Interface 3 LEDs Red, green and yellow

Wireless Sensor Network

USER NODE

ENVIRONMENTAL NODE

SERVER NODE

Star Net Topology

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


User Node Sensors

Wireless Module

Ultrasonic Sensor

9DoF Inertial Module

Digital Compass

40 kHz

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


USER MODULE

9 Degrees of Freedom - Sensor Stick

Accelerometer (ADXL345) Gyroscope (ITG-3200) Magnetometer (HMC5883L)

Accelorometer

Compensated Compass

SENSORS ALGORITHMS

User Posture

User Heading

Dead Reckoning

User Heading

Magnetic Field Meas.

http://www.robot-domestici.it/joomla/component/virtuemart/robotica-domotica/sensori/sensori-di-posizione/9-degrees-of-freedom-sensor-stick




Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


Environmental Node Sensors

Wireless Module

Temperature Sensor

Ultrasonic Sensor

Smoke Sensor

Gas Sensor

40 kHz

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


MODULO UTENTE

AURICOLARE

CUFFIA

Environmental Node

REAL VIEW OF THE HARDWARE IMPLEMENTATION Headset

User Module

Earphone

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


HW IMPLEMENTATION OF THE ULTRASOUND MODULE (US TX – User Node)


40 kHz – Oscillator Stadium

Driver Stadium

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


HW IMPLEMENTATION OF THE ULTRASOUND MODULE (US RX – Environmental Node)


Selective Amplifier Gain Stadium Comparator

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Reconstruction of the single step is performed by the combination of

the Heading θi and the StepSize ΔSi .

The absolute position is obtained by cumulating step by step the

relative positions

ΔS1

ΔS2

ΔS3 ΔS4

x

y

ΔSi

θi

X’

Y’ = ΔS *cos(θ)

X’ = ΔS *sinθ)

Y’

N

E

Dead Reckoning Techniques Walking Path Reconstruction

• The position error increases step by step. • It needs periodic correction throught

absolute measurement of position. • Usefull to evaluate short distance path • Useful to estimate physical capability of

the user


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

USER LOCALIZATION - Ultrasound Trilateration


Time of Flight (TOF) of the Ultrasound Wave is converted in Distance

TX – User Module RX – Environmental Module TX

RX

RX

RX

RX

RX

RX

RX

RX

RX

TX

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


ʃ

Algorithms for

Step Size (S)

Estimation

Dynamic Sdin

Static Sstat

ΘK

SK

S

θ

XY

Compass

Gyroscope

Accelerometer ΘComp

ΘGyro Processing

Processing Kalman

Filter

Kalman Filter

HEADING ESTIMATION

STEP SIZE ESTIMATION

WALKING PATH ESTIMATION

Dead Reckoning Techniques Schematization

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Multisensor Systems & Ambient Assisted Living (AAL)

DIEEI

Department of Electrical, Electronic and Information Engineering University of Catania – Italy

15-01-2015

Cristian Orazio Lombardo [email protected]

Algorithms and Signal Processing


DIE

EI –

Un

ive

rsit

y o

f C

atan

ia, I

taly

USER LOCALIZATION - Ultrasound Trilateration


Time of Flight (TOF) of the Ultrasound Wave is converted in Distance

TX – User Module RX – Environmental Module TX

RX

RX

RX

RX

RX

RX

RX

RX

RX

TX

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


Master send Acki

Envir. Nodej

User Nodek

Start Timer (usec)

Generate US Pulse (10ms)

US Signal

Received

TOF=0

TOF<>0

ArrayTOF

TOF received from all Envir.

nodes

TOFi

Send Serial Information

of TOF to Labview

NACK - Repetitions

Filter TOF Min!=0

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


Characterization of the Distance Measurement

• Range of the measured distance: 0 cm – 700 cm

• Step measurement: 10 cm

• Refresh time: 1 s

• Sampling frequency: 20 sample/s

• Number of acquired samples: 20 for each distance (1 s)

• Variable influence measured: Environmental Temperature

US-TX Circuit Master Node

Experimental Setup

US-RX Circuit


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


Uncertainty about 2cm

Characterization of the Distance Measurement

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


24,5 °C

25,0 °C

25,5 °C

26,0 °C

26,5 °C

27,0 °C

27,5 °C

28,0 °C

0 cm 100 cm 200 cm 300 cm 400 cm 500 cm

TEMPERATURE DRIFT DURING CHARACTERIZATION

Current Distance

Tem

pe

ratu

re

v(T)=331,4 + 0,62 T [m/s] where T is temperature in °C

Velocity of sound waves:

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e d

ei S

iste

mi


0

2

4

6

8

10

12

0 cm 100 cm 200 cm 300 cm 400 cm 500 cm

Distance

Measurement Error without Temperature Compensation

Erro

r [c

m]

v(T)=331,4 + 0,62 T [m/s] where T is temperature in °C

Velocity of sound waves:

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a

Università Degli Studi di Catania Università Degli Studi di Catania

2

3

2

3

2

3

2

2

2

2

2

2

2

1

2

1

2

1

dYyXx

dYyXx

dYyXx

d1

d2

d3

3131

2121

31

2

3

2

1

2

3

2

1

2

1

2

3

21

2

2

2

1

2

2

2

1

2

1

2

2

2YYXX

YYXX

YYYYXXdd

YYYYXXdd

x

3131

2121

2

3

2

1

2

3

2

1

2

1

2

331

2

2

2

1

2

2

2

1

2

1

2

221

2YYXX

YYXX

YYXXddXX

YYXXddXX

y

2

3

2

1

2

3

2

1

2

1

2

33131

2

2

2

1

2

2

2

1

2

1

2

22121

22

22

YYXXddyYYxXX

YYXXddyYYxXX

System of nonlinear

polynomial equations

Final linear system

Let us consider only 3 sensors; assume that we can

measure the distance with no errors

(X3,Y3)

(X1,Y1)

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a

(X2,Y2)

2D-Trilateration: Operating principle A Sensor Network for US-based indoor localization

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a

Università Degli Studi di Catania Università Degli Studi di Catania

Eng. Salvatore La Malfa

2D-Trilateration: uncertainty sources

List of uncertainty sources that could affect the accuracy

and the precision of the measurement of the distance:

Uncertainty Sources Affecting the accuracy

Xi, Yi coordinates are given with finite accuracy

Actual speed of acoustic waves

Operator errors

…

Affecting the precision

Acoustic noise in the US frequency range

Electric noise in the HW equipment

Fluctuation of the microcontroller oscillator

Quantization noise due to the finite resolution of the

microcontroller timer

…

?

1 1 1

2 2 2

3 3 3

ˆ ( )

ˆ ( )

ˆ ( )

d d u d

d d u d

d d u d

ˆ ( )

ˆ ( )

u u

u u

x x u x

y y u y

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a

A Sensor Network for US-based indoor localization

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


NiYX ii ,...,2,1,

Nidi ,...,2,1

!

1,2,..., ( ,3)3 !3!

Nj M M C N

N

Sensor nodes coordinates

Distance between user node and

the i-th sensor node

(X1,Y1) (X2,Y2) (X3,Y3)

(X4,Y4)

(X5,Y5)

(X6,Y6)

(X7,Y7) (X8,Y8) (X9,Y9)

(X10,Y10)

(X12,Y12)

(X11,Y11)

d1 d2

d3

d4

d5

d6

d7

d8 d9

d10

d11

d12

1

T Tx x

A B A A A By y

We have 2M equations and 2 unknowns

M = number of 3-combinations from a set of N elements

(Xij,Yij) the i-th corner of the j-th triad

dij the user distance from the i-th corner of the j-th triad

Let us denote by:

1 2

1

2

1

2

2

1 2

122 2

( , ,..., )

( , ,..., )

1

x x xN x

y y yN y

N

N

N

d

dd d d

d

c c c c fx

c c c c gy d dd

We simply solve a least squares problem

Constant elements matrix, we calculate this

2N+2 numbers only once, as their values

depend only on Xi, Yi The symbolic form for the C matrix is nontrivial!


STA (Single Trilateration Algorithm)

IF YOU HAVE N>3 measured distances

LEAST MEAN SQUARE ALGORITHM

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


NiYX ii ,...,2,1,

1,2,...,id i N

!

1,2,..., ( ,3)3 !3!

Nj M M C N

N

Sensor nodes coordinates

Distance between user node and

the i-th sensor node

(X1,Y1) (X2,Y2) (X3,Y3)

(X4,Y4)

(X5,Y5)

(X6,Y6)

(X7,Y7) (X8,Y8) (X9,Y9)

(X10,Y10)

(X12,Y12)

(X11,Y11)

d1 d2

d3

d4

d5

d6

d7

d8 d9

d10

d11

d12

We have 2M equations and 2 unknowns

M = number of 3-combinations from a set of N elements

(Xij,Yij) the i-th corner of the j-th triad

dij the user distance from the i-th corner of the j-th triad

Let us denote by:

2 2 2 21

2 2 2 2

2 2

2 2

1 2 1 21 2 1 2

1 3 1 3 1 3 13 1 3

2 1j j j j j jj j j j j

j j j j jj j jj j j

X X Y Yx X X Y Y

y X X Y Y X

d d

d Xd Y Y

We solve this system M

times obtaining M different

solutions for user position.

Finally, we apply some kind

of filtering.

MTA Filter

d1

d2

dN

(x1,y1)

(x2,y2)

(xM,yM)

(x,y)

…

…

Under certain conditions, this

approach can improve the

robustness and the precision

of the localization system

ENHANCED TRILATERATION ALGORITHM


MTA (Multiple Trilateration Algorithm)

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


The system was characterized in a real environment, by a non uniform grid [100, 50, 10] cm

Room area: 43 m2. N=7 sensor nodes

Characterization of the trilateration Algorithm

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


2 2.5 3 3.5 4 4.5 5 5.52.5

3

3.5

4

4.5

5

5.5

6

6.5Results MTA Algorithm

X axis(m)

Y a

xis

(m)

measured position

expected position

standard deviation

DISTRIBUTION OF RESIDUALS – MTA

m

Map Rappresentation of the Results of the Static Characterization of the MTA trilateration Algorithm


Measurement Grid = 108 points

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


0 20 40 60 80 100 120-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

Measurement Points

ST

A-M

TA

(m)

Differences Between STA-MTA Results

Mean value

-0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.10

5

10

15

20

25

STA-MTA(m)

Distribution of the Differences Between STA-MTA Results

histfit

STA – MTA COMPARISON

Difference between Residuals of STA Algorithm and MTA Algorithm


Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


1 2 3 4 5 6 7 80

1

2

3

4

5

6

7

8

9Results of MTA

X [m]

Y [

m]

Measured Path

Nominal Path

Sensor Position

1 2 3 4 5 6 7 80

1

2

3

4

5

6

7

8

9Results of STA

X [m]

Y [

m]

Measured Path

Nominal Path

Sensor Position

Walking Path: Rectangular Path 11 m long; Number of Repetition of the Walking Path: 10

Dynamic Evaluation of the Trilateration Algorithms


Results of MTA

100%

Nom

EstimNom

wdWD

WDWDJ

STA MTA

JWD% 12,7 3,5

Results of STA

Env. node

WD=Walking Distance

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


User Posture Estimation

The user posture can be estimated merging roll and pitch estimation:

𝑟𝑜𝑙𝑙 = tan−1𝐴𝑧

𝐴𝑦2+𝐴𝑥

2

𝑝𝑖𝑡𝑐ℎ = tan2−1𝐴𝑥

𝐴𝑦2 + 𝐴𝑧

2

z

y

x

Ax , Ay , Az = Signals of Accelerometer

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


θ = Roll; ϕ = Pitch

-15°<φ<15°

NO

ERECT

BOWED

-45°<θ<-90° or

45°< θ <90°

LIE DOWN LATERAL

YES

20°<φ<60°

-70°<φ<-60°

-20°<φ<-15°

ERECT/BOWED 15°<φ<20°

ERECT/SITTING

SITTING -60°<φ<-20°

SITTING/LIE DOWN

60°<φ<70° BOWED/LIE DOWN

φ>70° LIE DOWN PRONE

LIE DOWN SUPINE

YES

YES

YES

YES YES

YES

YES

YES

NO

NO

NO NO

NO

NO

NO

NO

POSTURE RECOGNITION ALGORITHM

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


𝜶 𝜽

𝒓𝑼𝑺

𝒓𝑶𝑩

Actual Implementation of Interaction with the Environment

Intersection between Safety range of the User

and of the Objects

Comparison between attitude of the user and direction of the distance between user position

and drawing point

- Object contour is drawed by connecting drawing point having distances each other of about 50-60cm

1° Step

2° Step

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


TEST 1: Obstacles Avoidance

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0,10,25

0,50,75

User safety range[m]

FN

TP

Test Constrains: User is free of moving inside the environment. Each collision is considered a failure, each avoidance of the object is considered a positive result

Dip

arti

men

to d

i In

gegn

eria

Ele

ttri

ca, E

lett

ron

ica

e In

form

atic

a


TEST 2: Fruition of Services

0%

20%

40%

60%

80%

100%

0,1 0,25 0,5 0,75 11,25

User safety range[m]

FN

TP

Test Constrains: User moves toward a service, a positive result was considered when user stops walking near the service at less than 50cm

multisensor systems & ambient assisted living (aal) · •indoor localization ......

Documents