Development and Implementation of Model-based Systems for Professional Football Teams, Aimed at Optimizing Health and Performance
Conditions: Electrocardiogram, Arrhythmias, Cardiac
Sponsor: RCD Mallorca SAD

 RESEARCH PROJECT.
30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
NTC number: 1573N19 Document Date: 05/15/2023

3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
1.
Analysis  of  data............................................... ................................................................ .........7
3.2
Index
2.
3.3
Discussion................................................. ................................................................ ......................8
7.
2.1
4.
9.
 ANNEX  I:  Informed  Consent.................................................. .............................11
Ethical-legal  and  biosafety  aspects. ................................................................ ...................8
Description ................................................. ................................................................ .................5
Sample/Participants................................................... ................................................................  .6
3.4
Methodology .................................................. ................................................................ ................5
Bibliographic  references................................................ ....................................................9
8.
LIST  OF  PLANNED  ORIGINAL  PUBLICATIONS...................................................3
Intervention................................................. ................................................................ ..............6
Results................................................. ................................................................ ...................8
5.
Introduction ................................................. ................................................................ ................3
3.
General  objectives ................................................ ................................................................ ..5
Procedure................................................. ................................................................ ...........7
Practical  application ................................................ ................................................................ ......9
6.
3.1  Experimental  Design................................................ ................................................................ ..5
3.5
Page  2  of  12

30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
Page  3  of  12
LIST  OF  PLANNED  ORIGINAL  PUBLICATIONS
1.  Introduction
3.  Machine  learning  applied  to  sports  geolocation  systems  for  the  prevention  of
professional  soccer  players  (T  wave  inversion  detection  with  machine  learning  to  prevent
1.  Detection  of  T-wave  inversion  with  machine  learning  to  prevent  sudden  death  in
of  health,  specifically  one  of  them  is  a  resting  12-lead  electrocardiogram.  Function
for  injury  prevention  in  professional  football  players.)
Players  undergo  various  pre-competitive  screening  tests  to  assess  their  status
2.  Machine  learning  applied  to  biological  parameters  for  control  and  advice  in
health  and  performance  in  professional  soccer  players.  In  professional  sport,  efforts  are  required
a  professional  athlete  and  the  need  for  more  complementary  tests  (Drezner  et  al.,
2017).  Our  proposal  is  to  reanalyze  these  tests  and  submit  them  to  a  mathematical  model  of
sudden  death  in  professional  football  players.)
The  approach  of  this  project  arises  from  the  concern  to  use  intelligence  systems
artificial  intelligence  and  machine  learning  in  professional  sports  as  assistance  for  the  optimization  of  the
In  this  regard,  the  proposal  of  several  publications  within  the  project  has  been  raised:
advisory  in  professional  football  players.)
From  the  waveform  findings  in  this  complementary  test,  the  risk  of
present  the  results  and  recommendations  according  to  international  study  criteria
professional  footballers  (Machine  learning  applied  to  biological  parameters  for  control  and
increasing  physical,  biological  and  physiological  conditions  and  we  need  help  tools.
machine  learning  that  is  capable  of  detecting  inversions  of  the  T  wave  in  said  leads  and
injuries  in  professional  soccer  players  (Machine  learning  applied  to  sport  geolocation  systems
1.  Detection  of  T-wave  inversion  with  machine  learning  to  prevent  sudden  death  in
professional  soccer  players.
electrocardiography  in  athletes.
Machine Translated by Google

30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
generate  pathologies.
During  the  season,  routine  analyzes  are  carried  out  to  control  biochemical  parameters.
professional  footballers.
The  data  obtained  during  training  sessions  and  matches  regarding  physical  data  such  as
(FIFA,  2006),  which  is  also  extrapolated  to  Spain  (Consejo  Superior  de  Deportes,  2015).
injuries  in  professional  soccer  players.
2.  Machine  learning  applied  to  biological  parameters  for  control  and  advice  in
vitamin  D,  vitamin  B12,  vitamin  B9,  ferritin,  etc  (Galan  et  al.,  2012).  These  data  will  be  submitted
and  performance  of  each  player.  Obtaining  the  performance  profile  of  the  player  standardized  according  to
In  recent  years,  soccer  competitions  have  experienced  a  great  boom  worldwide
carrying  out  different  studies,  on  the  one  hand  oriented  to  health  and  sudden  death  prevention
(Drezner,  Harmon,  Asif,  &  Marek,  2016)  and  on  the  other  hand  performance-oriented  and  that  relate  the
related  to  health  and  performance  and  fluctuating  or  changing  throughout  the  season:
duration,  distance,  distance  at  different  speeds,  training  density,  etc.  What  are  provided
by  sports  geolocation  systems,  are  of  great  importance  when  studying  the  effort  profile
habitual  of  the  players  and  that  can  cause  alterations  in  performance,  even  reaching
physical  condition.  Warning  and  alarm  systems  can  be  designed  aimed  at  the  prevention  of
With  regard  to  health  and  performance  in  football,  multiple  initiatives  are  emerging  and
to  a  machine  learning  procedure  that  can  notify  us  of  alterations  in  the  pattern
On  training  day  we  can  detect  adverse  situations  such  as:  over-training  or  lack  of
injury  incidence  (Hägglund,  Waldén,  &  Ekstrand,  2005),  injury  load  (Ekstrand,  Waldén,  &
3.  Machine  learning  applied  to  sports  geolocation  systems  for  the  prevention  of
injuries.  (Rossi,  Pappalardo,  Marcello,  Javier,  &  May,  2017).
To  better  understand  the  theoretical  framework  of  the  study  and  its  background,  we  can  highlight  how  in
Page  4  of  12
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2.  Description
3.  Methodology
Page  5  of  12
oriented  to  the  complexity  of  the  causality  of  injuries.  (Bittencourt  et  al.,  2016)(Quatman,
Therefore,  this  project  is  of  great  interest  to  show  a  strategy  that  helps  to  improve  these  aspects.
as  possible  factors  that  affect  the  final  result  of  the  teams,  (Hägglund  et  al.,  2013).  For  all
-  Develop  advisory/advisor  systems  in  the  area  of  health  and  performance  based  on
carried  out  by  other  authors.  (López-Valenciano  et  al.,  2017)
Hägglund,  2016),  player  availability  (Bahr,  Clarsen,  &  Ekstrand,  2017)  and  other  parameters
study  it  is  interesting  to  reflect  that  integrating  predictive  systems  with  preventive  orientation  is  not
Players.
To  end  this  introduction  and  prior  to  explaining  the  description  and  objectives  of  the
tried  to  develop  models  that,  from  the  current  point  of  view,  tend  towards  an  approximation
the  profiles.
in  professional  soccer  players
exempt  from  limitations  (Bahr,  2016).  Because  of  this  and  other  factors  that  have  been  considered,  it  has  been
The   studies  will  be  carried  out  implementing  artificial  intelligence  and  machine learning  
systems machine  on  the  physical,  biological  and  physiological  data  collected  during  routine  
activity sports  and  health  in  professional  football  teams  in  the  2019-20  to 2023-24.
1.  Detection  of  T-wave  inversion  with  Machine  Learning  to  prevent  sudden  death
Quatman,  &  Hewett,  2009),  and  make  a  correct  scale  of  the  statistical  weights  as  have  been
-  Evaluate  the  implementation  of  artificial  intelligence  systems  such  as  machine  learning  to
obtain  models  and  results  in  the  interpretation  of  physical,  biomedical  and  physiological  parameters  of
3.1  Experimental  Design
2.1  General  Objectives
3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
Machine Translated by Google

3.2  Intervention
3.3  Sample/Participants
3.  Machine  learning  applied  to  sports  geolocation  systems  for  prevention
of  the  morphology  of  the  T  wave  in  electrocardiography.
qualified  professionals  and  a  machine  learning  system  based  on  detection  algorithm
multiparameters  in  the  physical  data  profiles  of  the  players  during  routine  activity.
Healthy,  young  players  and  professionals  of  legal  age  who  perform  their  role  in  teams
Development  of  machine  learning  for  the  detection  of  abnormal  deviations
Comparison  study  between  results  obtained  in  the  electrocardiographic  interpretation  of
professional  footballers
of  the  routine  tests  carried  out  on  players  during  their  usual  work  practice:
Inclusion  criteria:
2.  Machine  learning  applied  to  biological  parameters  for  control  and  advice  in
The  procedure  is  based  on  the  generation  of  mathematical  models  from  the  data  obtained
soccer  professionals.
multiparametric  variables  in  the  biochemical  profiles  of  the  players.
Blood  and  urine  tests  (monthly)
Development  of  a  machine  learning  system  for  the  detection  of  abnormal  deviations
EKGs  (monthly)
of  injuries  in  soccer  players
Sports  geolocation  systems  (daily)
Page  6  of  12
30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
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3.5  Data  analysis
3.4  Procedure
research  and  development  of  the  same  (periods  of  realization,  measures  to  be  carried  out,  benefits  and
Players  with  known  pathology.
Players  who  are  not  a  regular  part  of  these  professional  teams.
study,  statistical  power,  effect  size,  and  alpha  significance  level.
informed  (ANNEX  I)  so  that  there  is  a  record  of  their  acceptance  to  participate  in  the  project.
Exclusion  criteria:
The  participating  professional  soccer  players  will  be  selected  from  the  database  of  the
interference  in  the  daily  operation  of  the  equipment.
determine  the  minimum  sample  for  the  study  taking  into  account  different  parameters  such  as  the  type
pre-experimental  tests  in  which  we  can  have  control  groups  or  control  databases  to  generate
Confusion  tables  between  actual  and  expected  values.  Normality  criteria  will  be  checked
Participant  selection  method  and  informed  consent
To  carry  out  the  project,  a  procedure  of  low  impact  of  presence  has  been  followed,  of
so  that  the  data  could  be  obtained  and  the  calculations  carried  out  with  the  minimum  presence  and/or
according  to  the  inclusion  and  exclusion  criteria,  they  will  be  contacted  to  explain  the  objective  of  the
Within  the  methodology,  depending  on  the  article,  an  a  priori  study  will  be  carried  out  to  adjust
The  studies  that  are  going  to  be  developed  belong  to  experimental  studies  of  the  type
systems  for  generating  algorithms  and  programming  systems  are  based  on  the  language  of
Villareal  Club  de  Fútbol,  from  among  teams  A,  B,  C  and  Juvenil  A.  Once  the  participants  have  been  selected
of  the  sample  and  the  data  will  be  processed  through  different  statistical  systems  such  as  SPSS24.  The
risks  of  the  study).  To  finalize  the  selection  process,  participants  will  sign  the  consent
the  statistical  parameters  and  the  necessary  sample  with  the  statistical  software  GPower  3  (Faul,
Erdfelder,  Lang,  &  Buchner,  2007)(Erdfelder,  Faul,  Buchner,  &  Lang,  2009).  This  system  allows
Page  7  of  12
3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
Machine Translated by Google

6.  Ethical-legal  and  biosafety  aspects.
4.  Results
5.  Discussion.
presentations  at  congresses  or  presentations  at  scientific  meetings.  The  data  will  be  presented
sports  science  like  Pandas,  Numpy,  Matplotlib,  Spider  among  others.
Andalusia  for  its  approval  and  correct  comparison.
results  of  the  study  by  sending  the  links  corresponding  to  the  publications  obtained.
Python  programming  and  assistance  software  such  as  Anaconda  Navigator  and  libraries  of
significant  for  generating  translational  scientific  results  with  a  disruptive  component.  is  anticipated
In  this  section,  the  debate  between  the  scientific  articles  published  in this  area  and  the  results  of  
this  project.  It  will  also  try  to  argue  and  question the  study  in  the  face  of  possible  limitations  or  
improvements.
ethical  and  respectful  research,  it  is  sent  to  the  biomedical  research  ethics  portal  of
moment  with  the  ethical  principles  established  in  the  Declaration  of  Helsinki  for  research
medical.  All  the  information  will  be  processed  in  a  manner  disassociated  from  the  identity  of  the  sources  of  information.
In  this  project  we  will  try  to  obtain  statistically  representative  results  and
in  indicators  such  as  scientific  publications  in  widely  distributed  and  recognized  worth  journals,
The  project  is  based  on  the  exploitation  of  data  on  physical,  biological  and  physiological  tests  of
The  use  of  this  material  will  comply  with  current  international  standards  and  will  be  complied  with  at  all
Personal  Character  and  its  updated  supplement  to  the  European  Data  Protection  Regulation  (EU)
that  the  results  of  the  project  have  a  relevant  scientific-technical  impact  that  can  be  reflected
data,  in  accordance  with  the  provisions  of  Organic  Law  15/1999,  of  December  13,  on  Data  Protection  of
disassociated  from  the  identity  of  the  participants.  In  addition,  the  participants  will  be  informed  of  the
routine  developed  in  the  sports  field  that  could  generate  an  exemption  from  passing  through  a  committee
of  ethics  (Winter  &  Maughan,  2009),  even  so,  based  on  our  concern  to  generate
2016/679,  of  April  27.  In  the  procedures  for  collecting  and  transporting  samples  and  analysis  of
Page  8  of  12
3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
Machine Translated by Google

7.  Practical  application
8.  Bibliographic  references
The  project  has  great  potential  for  practical  applicability  and  could  generate  a  change  of
The  project  is  of  high  interest  due  to  its  translational  scope  and  it  would  not  be  possible  to  carry  it  out
WHO  biohazard  2.
professional  soccer  players.  A  notable  aspect  is  the  possible  improvement  of  the  calculation  of  the
Drezner,  JA,  Sharma,  S.,  Baggish,  A.,  Papadakis,  M.,  Wilson,  MG,  Prutkin,  JM,  …  Corrado,  D.
They  will  help  in  the  health  controls  and  in  the  sports  load  controls  that  apply  to
laboratory,  biosafety  and  personal  protection  standards  will  be  applied,  related  to  the  level  of
of  the  research  project  can  contribute  to  the  improvement  in  the  health  and  performance  of  the
Bahr,  R.  (2016).  Why  screening  tests  to  predict  injury  do  not  work-and  probably  never  will.:  A  critical  
review.  British  Journal  of  Sports  Medicine.  https://doi.org/10.1136/bjsports-2016-096256
Drezner,  JA,  Harmon,  KG,  Asif,  IM,  &  Marek,  JC  (2016).  Why  cardiovascular  screening  in  young  athletes  
can  save  lives:  A  critical  review.  British  Journal  of  Sports  Medicine,  50(22),  1376–1378.  https://
doi.org/10.1136/bjsports-2016-096606
without  data  derived  from  the  use  of  human  samples.  In  addition,  it  is  expected  that  the  results
probabilistic  weights  of  risk  factors  on  health  and  performance.
(2017).  International  criteria  for  electrocardiographic  interpretation  in  athletes:  Consensus  
statement.  British  Journal  of  Sports  Medicine,  51(9),  704–731.  
https://doi.org/10.1136/bjsports-2016-097331
Bittencourt,  NFN,  Meeuwisse,  WH,  Mendonça,  LD,  Nettel-Aguirre,  A.,  Ocarino,  JM,  &
Professional  sportsmen.
Bahr,  R.,  Clarsen,  B.,  &  Ekstrand,  J.  (2017).  Why  we  should  focus  on  the  burden  of  injuries  and  
illnesses,  not  just  their  incidence.  British  Journal  of  Sports  Medicine,  0(0),  
bjsports-2017-098160.  https://doi.org/10.1136/bjsports-2017-098160
paradigm,  since  it  is  based  on  the  generation  of  mathematical  and/or  programming  models  that
Fonseca,  ST  (2016).  Complex  systems  approach  for  sports  injuries:  moving  from  risk  factor  
identification  to  injury  pattern  recognition—narrative  review  and  new  concept.  British  Journal  of  
Sports  Medicine,  50(21),  1309–1314.  https://doi.org/10.1136/bjsports-2015-095850
Superior  Sports  Council.  (2015).  Report  2015  Licenses  and  Clubs.  Retrieved  from  Http://
Www.Csd.Gob.Es/ Csd/ Estaticos/ Asoc-Fed/ LicenciasyClubes2015.Pdf,  446(1).
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3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
Machine Translated by Google

30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
Ekstrand,  J.,  Waldén,  M.,  &  Hägglund,  M.  (2016).  Hamstring  injuries  have  increased  by  4%  annually  in  
men's  professional  football,  since  2001:  a  13-year  longitudinal  analysis  of  the  UEFA  Elite  Club  
injury  study.  British  Journal  of  Sports  Medicine,  50(12),  731–737.  
https://doi.org/10.1136/bjsports-2015-095359
Hägglund,  M.,  Waldén,  M.,  &  Ekstrand,  J.  (2005).  Injury  incidence  and  distribution  in  elite  football  -  A
López-Valenciano,  A.,  Ayala,  F.,  Puerta,  JM,  De  Ste  Croix,  M.,  Vera-García,  F.,  Hernández-Sánchez,  
S.,  …  Myer,  G.  (2017).  A  Preventive  Model  for  Muscle  Injuries.  Medicine  &  Science  in  Sports  &  
Exercise.  https://doi.org/10.1249/MSS.00000000000001535
Quatman,  CE,  Quatman,  CC,  &  Hewett,  TE  (2009).  Prediction  and  prevention  of  musculoskeletal  injury:  
A  paradigm  shift  in  methodology.  British  Journal  of  Sports  Medicine,  43(14),  1100–1107.  https://
doi.org/10.1136/bjsm.2009.065482
Galan,  F.,  Ribas,  J.,  Sánchez-Martinez,  PM,  Calero,  T.,  Sánchez,  AB,  &  Muñoz,  A.  (2012).  Serum  25-
hydroxyvitamin  D  in  early  autumn  to  ensure  vitamin  D  sufficiency  in  mid-winter  in  professional  
football  players.  Clinical  Nutrition,  31(1),  132–136.  https://doi.org/10.1016/j.clnu.2011.07.008
Timpka,  T.,  Jacobsson,  J.,  Bickenbach,  J.,  Finch,  CF,  Ekberg,  J.,  &  Nordenfelt,  L.  (2014).  What  is  a  
Sports  Injury?  Sports  Medicine,  44(4),  423–428.  https://doi.org/10.1007/s40279-014-0143-4
Injuries  affect  team  performance  negatively  in  professional  football:  An  11-year  follow-up  of  the  
UEFA  Champions  League  injury  study.  British  Journal  of  Sports  Medicine,  47(12),  738–742.  
https://doi.org/10.1136/bjsports-2013-092215
Retrieved  from  https://arxiv.org/pdf/1705.08079.pdf%0Ahttps://arxiv.org/abs/1705.08079
Gabbett,  T.J.  (2016).  The  training-injury  prevention  paradox:  should  athletes  be  training  smarter  and  
harder?  British  Journal  of  Sports  Medicine,  1–9.  https://doi.org/10.1136/bjsports-2015-095788
Hägglund,  M.,  Waldén,  M.,  Magnusson,  H.,  Kristenson,  K.,  Bengtsson,  H.,  &  Ekstrand,  J.  (2013).
FIFA.  (2006).  FIFA  Big  Count  2006:  270  million  people  active  in  football.
Rossi,  A.,  Pappalardo,  L.,  Marcello,  CF,  Javier,  I.,  &  May,  ML  (2017).  Effective  injury  prediction  in  
professional  soccer  with  GPS  data  and  machine  learning.  Cornwell  University  Library,  (June).
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j.1600-0838.2004.00395.x
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Name
The  treatment  that  will  be  made  of  them  will  be  carried  out  in  accordance  with  the  general  data  protection  regulation  (RGPD)  and  
its  sole  purpose  being  to  generate  algorithms  or  mathematical  models  aimed  at  optimizing  health  and  performance.  The  
data  will  remain  anonymous,  not  being  able  to  identify  the  experimental  subject.  You  may  deny  or  revoke  permission  to  use  the  data  by  
contacting  the  Principal  Investigator  by  any  written  means.
You  are  hereby  informed  that  you  are  going  to  be  included  in  the  aforementioned  research  project.  This  implies  that  your  biomedical  
and  physiological  data  collected  during  your  routine  practice  as  a  professional  footballer  will  be  processed  for  research  purposes  during  
the  2019-20  and  2020-21  seasons.
4.  Detection  of  T-wave  inversion  with  Machine  Learning  to  prevent  sudden  death  in  soccer  players
I  declare  that  I  have  been  informed  by  the  Principal  Investigator,  and  I  am  aware  that,  at  any  time,  I  can  revoke  my  consent.
I  am  satisfied  with  the  information  received,  I  have  been  able  to  ask  all  kinds  of  questions  that  I  have  deemed  appropriate  and  
all  the  doubts  raised  have  been  clarified.
Signature
ID
Principal  Investigator: 
mail: 
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  soccer  teams,  aimed  at  
optimizing  health  and  performance.
LIST  OF  PLANNED  PUBLICATIONS:
5.  Machine  learning  applied  to  biological  parameters  for  control  and  advice  in  professional  soccer  players.
3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011).  University  of  Seville  30210003  
-  Computer  Technology:  Medical  and  Industrial  Applications 
The  data  on  which  the  engineering  analysis  will  be  made  primarily  will  be:  electrocardiograms,  blood  tests,  urine  tests,  sports  geolocation  
data  (GPSs),  complementary  imaging  tests:  DEXA,  MRI,  rx,  CT  scans  and  functional  assessments.
Signature  of  the  experimental  subject
Project  description.
professional.
Accordingly,  I  consent  to  the  use  of  my  biomedical  data.
Signature
6.  Machine  learning  applied  to  sports  geolocation  systems  for  the  prevention  of  injuries  in  soccer  players
professionals.
Signature  of  Principal  Investigator.
9.  ANNEX  I:  Informed  Consent
Page  11  of  12
3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
INFORMED  CONSENT  FOR  RESEARCH  WITH  BIOMEDICAL  DATA.
30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
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Date  of  Birth       
Date of  Information

Page  12  of  12
30210003  -  Computer  Technology:  Medical  and  Industrial  Applications
Title:  Development  and  implementation  of  expert  systems  based  on  models  for  professional  
soccer  teams,  aimed  at  optimizing  health  and  performance.
3021  -  Doctoral  Program  in  Computer  Engineering  (RD.  99/2011)
REVOCATION  OF  INFORMED  CONSENT
Patient's  signature
Signature  of  the  research  manager
On  date .................................  I  revoke  the  consent  given  for  the  use  of  my  biomedical  data  for  research.
Date:
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