Armando Bellini, - phdindustrialengineering

Real time processing of biomedical and biomechanical signals

• Armando Bellini, Full Professor

• Vincenzo Bonaiuto, Associate Professor

• Fausto Sargeni, Associate Professor

• Stefano Bifaretti, Researcher

• Giuseppe Annino, Researcher

• Nicola De Simone, PostDoc Grant

• Luca Federici, PhD Student

• Luca Tarisciotti, PhD Student

People


The NA62 Experiment – High Energy Phisycs - CERN • Design of the Veto Trigger System for LKr Calorimeter

Artificial Neural Networks – Analogue VLSI Circuit implementation • Cellular Neural Networks • I&F Neuromorphic Neural Networks

Research Activities

Sport Engineering Technologies • Extraction of functional parameters for performance evaluation of

high-level athletes


Main Academic and Industry Partners

C.H.O.S.E

TELETECNICA

Apparecchiature elettriche,

elettroniche e per

teletrasmissioni


Data Acquisition

Data Transmission

Data Processing

ASIC (Analogue or Digital)

FPGA

Software on PC

Hardware Design for Signal Processing

EMG Sensor

IMU Sensor

Stereo Vision Camera

Time Constrain Problem


Hardware vs Software Solution

Real time?

Wired or Wireless?

Battery powered? Low Power

System Dimensions?

Algorithm Complexity

Costs

Engineering problem to solve

Time Constrain


Computational Power

Pro

cess

ing

Tim

e R

equ

irem

en

ts DSP Processors

ASIC (Analogue or Digital)

FPGA

ARM Microcontroller

16bit Microcontroller


Hardware vs Software Solution

Software on PC


Hardware design

Design of mixed-signal electronic boards based on microcontroller (C2000, MSP430, TMS320, STM, Cortex-M3, Arduino, PIC, ecc.)

Design of mixed-signal electronic boards based on programmable electronic devices (FPGA) and/or Digital Signal Processor (DSP)

Design of analogue or mixed-signal ASIC

Software design

Software application design using object-oriented languages on Android,

Linux as well as Windows platforms (Delphi, Visual C++, Visual C#)

Main skills


Cellular Neural Networks Applications: Stereovision System for Autonomous Robotics

Disparity Map Extraction

16x64 Stereo

Vision CNN Chip

Dual ADSP-TS201S

TigerSHARC®

Processors 6x24 Stereo Vision DPCNN Board

DSP Processors ASIC (Analogue)

Real time Image Processing Problem


Multi-chip I&F Neuromorphic Architecture

Specific Algorithm

ASIC (Analogue)


Cellular Neural Networks Applications: Support Systems to the Clinical Diagnosis of the Eye Diseases

Morphometry Analysis of the Corneal Endothelium

Salerno, M. ; Sargeni, F. ; Bonaiuto, V. ; Amerini, P. ; Cerulli, L. ; Ricci, F.: A new CNN based tool for an automated morphometry analysis of the

corneal endothelium - Proceedings of Fifth IEEE International Workshop on Cellular Neural Networks and Their Applications, 1998

Image Processing Problem

Software on PC

•Density of cells

•Morphometry analysis

NO Real Time requirement


Retinal Images Registration and Clinical Parameter Extraction (PRIN 2004)

Cellular Neural Networks Applications: Support Systems to the Clinical Diagnosis of the Eye Diseases

Image Processing Problem

FAST Processing Time requirement

Software on PC


Design of electronic systems by using new materials and new technologies to acquire and study the physiological and biomechanical parameters of human movement

Sport Engineering

Easy to use in Athletic as well as soccer field (outdoor)

or basketball and volleyball court (indoor)

Smallest system, Minimally invasive, Wireless (short or long distance),

MUST NOT MODIFY THE ATHLETE’S PERFORMANCE

Analysis of Athlete’s Performances

The data of the performance have to be easy to

understand

Support to the trainer in fully recovery of the athlete in

the post rehabilitation phase


Training and performance evaluation of swimmers

Ben Hur: Electrical machine for training swimmers and measuring their force and speed

Goldeneye: Underwater motion capture and evaluation

Kz: A system to measure the thrust of a swimmer Speed RT: a system to measure the

displacement and speed of a swimmer


Bottoni, A., Lanotte, N., Bifaretti, S., Gatta, G., Bonifazi, M., Boatto, P. : “Direct measurement of stroke propulsion in real swimming by means of a non

invasive gauge” - Biomechanics in Swimming – Oslo June 16th -19th 2010

KZ: a system for measure the thrust of a swimmer

The athlete can swim freely and

the data are stored in the system.

They can be acquired by a PC via

a Bluetooth radio link

It is based on two differential pressure sensors

receiving the input from two special mini paddles on

the hands of the swimmer.

These sensors measure the pressure difference

between palm and back of the hand, which determines

the thrust.



• Quantitative analysis (maximum thrust, avg. thrust, frequency,…)

• Qualitative analysis (shape of the curve, faults, symmetry…)

• Study of efficiency

• Effects of training

• Effects of fatigue

• Integration with other sensors (accelerometers, gyroscopes, GPS,..)

• Real time data transmission

“Technical skill differences in stroke propulsion between high level athletes in triathlon and top level swimmers“: A. Bottoni, N. Lanotte, P.

Boatto, S. Bifaretti, M. Bonifazi - JOURNAL OF HUMAN SPORT & EXERCISE - VOLUME 6 | ISSUE 2 - 2011

KZ: a system for measure the thrust of a swimmer

Software on PC


TriodeTM

Electrodes sEMG

MCU and Wireless TX Unit

MP430 Texas Instr

IMU MPU6050

Wireless IMU-sEMG System

EMG Accelerometer




Software on PC


Counter Movement Jump (CMJ)

countermovement ( squat) 390 ms

Rise Time 350ms

FLy Time 490 ms Contact

Time

Acceleration VT

Peak Concentric Phase

Peak Eccentric Phase

Flight

Contact

EMG

Accelerometer


Corsa

Run Parameters evaluated

from acquired data

•4

Steps

•19,54

Rhythm (steps/min)

•2,5

Average Step Lenght (m)

•2,71

Speed (m/s)

•0,34

Contact Time (s)

•0,66

Fly Time (s)

Walking 1st Step

EMG


Documents

Armando Bellini, - phdindustrialengineering