Designing%20A%20Patient%20Monitoring%20System%20Using%20Cloud%20And%20Semantic%20Web%20Technologies

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Designing A Patient Monitoring SystemUsing
Cloud And Semantic Web Technologies
Technical University of Crete
Chryssa Thermolia -Ekaterini S. Bei? Stelios
Sotiriadis? - Kostas Stravoskoufos? Euripides
G.M. Petrakis
17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Motivation Patient Monitoring Systems

• New era of healthcare requires new tools,
  devices and systems to improve health
• services?
• Advanced health care increases the need for
  constant monitoring of patient's condition?,
  especially in chronic diseases
• ?Solution
• Multi-source patient monitoring evolves into
  an important service in this domain?
• Patient monitoring systems offer advantages in?
•      - early-diagnosis      
• - optimal treatment strategies 
• - disease prevention?
• - analysis, management and
  communication of medical information?
• ?
• Key factors in this attempt ?
•   integration of medical information from various
  sources
• constant, on-time briefing of patients health
  state and behavior ?

17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Motivation Bipolar Disorder Domain

• Bipolar Disorder (BD) is a mental disorder,
  characterized by dramatic shifts in mood,
  thinking, behavior and energy that is seemed in
  up to 5 of primary health care patients
• Symptoms of bipolar disorder may have great
  effects in the daily activities and general
  behavior of a person preventing him from a normal
  life

• BD Management Must address different aspects
  of patients physical, emotional and social daily
  status
• Need for a patient monitoring system to
  support longitudinal follow-up of BD

17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Background Semantic Web

• Semantic Web Collection of standard technologies
  to realize a Web of Data
• - Ontology Heart of Semantic Web
• Formal representation of knowledge
  as a set of concepts.
• Describes the concepts (classes) of in a
  domain interest, their characteristics (data
  properties) and the relationships that hold
  between the concepts (object properties)
• Example
• OWL (Web Ontology Language) Language that
  describes the concepts and their relationships.
• SWRL (Semantic Web Rule Language) Implements
  deductive reasoning in OWL

17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Background Internet of Things (IoT)

• Internet of Things (IoT)
• Relates users and their smart devices
• along with sensors used in every day actions
• (e.g., Smart phones and wearable devices)
• Various devices could offer to sensor embedded
  healthcare new applications and services

• IoT is expected to greatly transform the
  healthcare industry by improving the
  clinician-patient relationship
• Clinicians using IoT could
• - monitor patients remotely
• - run a diagnosis in real-time
• - be notified for sudden and
• abnormal events and act
• immediately

17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Background Cloud Computing

• IoT growth leads to large amounts of data
• Need for big data storage, processing and
• accessing
• Cloud computing as a paradigm for big data
  storage and analytics

• Cloud Computing
• Provides a platform environment where hardware
  and software could be delivered on a bespoke
  manner to users and utilized accordingly to their
  requests.
• Allows the scaling of user resources on demand
  (elasticity)

• Combination of IoT and Cloud Computing is the
  real innovation

17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Core System

• The designed patient monitoring
• system is aimed to be able to support clinical
  professionals during the initial evaluation and
  diagnosis of adults with suspected BD, and during
  their treatment
• The system will be able to provide
• evidence-based treatment options for a
  personalized therapeutic approach
• notifications for early-warning signs and alerts
  for crucial mood swings

• Our design consists of three components
• 1) The implemented core system.
• 2) A proposal of the front-end system.
• 3) The vision of the back-end system.

17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Core System Guidelines

• The World Federation of Societies of Biological
  Psychiatry (WFSBP) Guidelines for the Biological
  Treatment of Bipolar Disorders (long-term
  treatment)
• Canadian Network for Mood and Anxiety Treatments
  (CANMAT) and International Society for Bipolar
  Disorders (ISBD) collaborative update of CANMAT
  guidelines for the management of patients with
  bipolar disorder (acute episodes of mania,
  depression)
• The CANMAT task force recommendations for the
  management of patients with mood disorders and
  comorbid medical conditions (diagnosis)
• Australian and New Zealand clinical practice
  guidelines for the treatment of bipolar disorder
  (breakthrough depression)
• Bipolar disorder algorithms The
  Psychopharmacology Algorithm Project at the
  Harvard South Shore Psychiatry Program , TEXAS
  Medication Algorithm Project (immediate urgent)
• Rating Scales
• Hamilton Depression Rating Scale (HDRS)
• Young Mania Rating Scale (YMRS)
• MontgomeryÅsberg
• Clinical Global Impression Bipolar Version
  Scale, CGI-BP
• Global Assessment of Functioning Scale, GAF
• The Quality of Life in Bipolar Disorder
  Questionnaire

17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Core System User Scenarios For BD

• Types of Bipolar Disorder
• DSM-IV-TR Classification
• Bipolar I Disorder (BDI) one or more episode of
  mania with or without major depressive episodes
• Bipolar II Disorder (BDII) one or more episode
  of hypomania as well as at least one major
  depressive episode with no psychotic features
• Cyclothymic disorder low grade cycling of mood
  with the presence or history of hypomanic
  episodes and periods of depression that do not
  meet criteria for major depressive episodes
• Bipolar disorder NOS Bipolar symptoms that do
  not meet the criteria for previous subtypes

• Diagnosis
• 1st Level (clinician studies the patients
  experience in regards of abnormal symptoms),
• 2nd Level (clinician estimates according
  to defined criteria taking also into account
  family history)
• Therapy pharmacotherapy (mood stabilizers,
  antidepressants, antipsychotics),
  psychoeducation,
• psychotherapy

17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Core System User Scenarios For BD
Possible phase transitions of Bipolar I Disorder
The scenarios are developed considering possible
phase transitions of BD that may occur during
the progress of the disease (mania to euthymia,
depression to euthymia, mania to depression, and
vice versa)
17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Core System User Scenarios

• The developed scenarios support clinician through
• Diagnosis
• Immediate Urgent Management Treatment
• Acute Manic Episode Treatment
• Acute Depressive Episode Treatment
• Breakthrough Depressive Episode (Li) Treatment
• Long-term Treatment

17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Core System Ontology

• Dynamic Entities
• PHR
• PatientState
• Symptom
• Function Tests
• Therapy
• Medicine
• Static entities
• Patient
• PatientHistory
• Episode
• InitialEvaluation
• History
• Questionnaire
• (MDQ, BSDS, CIDI)
• Clinical Evaluation

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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Core System SWRL Rules

• Clinical guidelines encoded as SWRL rules to
  issue alerts and recommendations
• Apply rules over patients information.

Example If there is a positive mood
questionnaire, there is a suspicion of BD and in
that case, if the clinical evaluation excludes
other medical causes from being responsible for
the patients symptoms then, the rule concludes
that the clinician needs to continue with
assiduous clinical examination PHR n
InitialEvaluation n (? Questionnaire.result
true) n (? ClinicalEvaluation.result normal)
? Recommendation
17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Overall Architecture

• High level expected functionalities of the
  monitoring system prototype
• Data collection
• Interoperability
• Notification services
• Data analysis and integration
• Secure data storage
• Legacy system adaptors
• Other services such as semantic analysis tools

17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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"Designing A Patient Monitoring System Using
Cloud And Semantic Web Technologies"?
Conclusions Future Work

• Conclusions
• Analyze patient records and filtering
• evidence-based guidelines to offer
• individualized notifications and
• recommendations for diagnosis
• and treatment.
• Propose a cloud deployment model
• as a perspective for an advanced
• environment that assists in
• monitoring of complex chronic
• pathologies, such as brain disorders
• including BD.

• Future Work
• Implement and test the cloud- based
• architecture on a real setting perfor-
• ming data acquisition from sensors
• and wearable devices

17th International Conference on Brain and Health
Informatics (ICBHI 2015)
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Thank you!(Questions ?)