RADAR Platform - Ecsel Ju · RADAR Platform Large scale, open source wearables data processing for...
Transcript of RADAR Platform - Ecsel Ju · RADAR Platform Large scale, open source wearables data processing for...
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RADAR Platform
Large scale, open source wearables data processing for disease and relapse assessment
Kees van Bochove, CEO The Hyve (@keesvanbochove)
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The Hyve
▶ Professional support for open source software for bioinformatics and translational
research software, such as tranSMART, cBioPortal, i2b2, Galaxy, ADAM and OHDSI
Mission Enable pre-competitive collaboration in life science R&D by leveraging open source software
Core values
Share Reuse Specialize
Office Locations Utrecht, Netherlands Cambridge, MA, United States Singapore
Services Software development Data science services Consultancy Hosting / SLAs
Fast-growing Started in 2012 43 people by now
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Interdisciplinary team @ The Hyve NL
• software engineers, data scientists, project managers & staff; expertise in bioinformatics, medical informatics, software engineering, biostatistics etc.
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3 Health Data Areas The Hyve is active in
▶ Translational Research Data
(‘Clinical & bioinformatics data’)
▶ Population Health Data
(‘Real world data’)
▶ Personal Health Data
(‘Wearable sensors data’)
Example project:
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RADAR-CNS
• IMI project
• Remote Assessment of
Disease And Relapse –
Central Nervous
System
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Problem statement
• Physicians only get a snapshot of their patients • How many times have you had a headache last months?
• Continuous monitoring
• Moving from treatment to prevention • Prediction of disease onset or relapse
• Huge amounts of data, uncertain quality of sensors • Big data solutions
• Understanding the environment
• Risk assessment
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RADAR-CNS Focus areas
from diagnose & treat to predict & prevent • Epilepsy
• Monitoring and predicting epileptic seizures
• Multiple Sclerosis
• Monitoring disease progression and state
• Depression
• Monitoring for possible relapses, plan timely interventions
• Predict bipolar state transitions
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Epilepsy Pilot Studies
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RADAR Platform Initial Requirements
pRMT
App
aRMT
App
Wearables
Questionnaires
Phone
sensors
Digital Assay
mobile apps
middleware
https://github.com/RADAR-CNS
3rd Party Data
Sources
3rd Party
Connector
RADAR Platform
Dashboard
Data
Access /
Storage
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Team of Developers Assembled from RADAR Partners
Sebastian
Boettcher
Mark Begale/
Vibrent Health
Nithin Thomas Hesam Sagha
Ward Weistra
Abhishek
Govindappa
Lakshminarayan
Paula Petcu
Nivethika Mahasivam
Herculano Campos
Joris Borgdorff
Carolyn Langen
Maxim Moinat
Maximilian Kerz
Amos Folarin
Francesco Nobilia
Denny Veerbeck/
Janssen Sjaak Peelen
Julia Kurps
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Architecture
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▶ Skin Temperature ▶ Heart rate/Heart rate variability
(PPG*, ECG**) ▶ Actigraphy (3-axis
accelerometer, gyroscope) ▶ Galvanic Skin Conductance
(EDA***)
▶ Location/Movement: GPS ▶ Mood: Voice recognition ▶ Social interaction: Call logs, Message logs ▶ App interaction/App usage ▶ Experience Sampling Methods: questionnaires
Data Sources - devices
Empatica E4, Pebble2, Biovotion
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13 aRMT App
Composable Questionnaire App
Requirements
● Dynamic questionnaires
● Scheduling
● Data feedback
● Engagement driver
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Iterative design cycles & focus groups
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Features
Setup &
Enrolment Planning Feedback Questions
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Recruitment: REDCap & RADAR
REDCap
• Personally identifiable information (PII)
• Protected Health information (PHI)
• Regimen management
RADAR-CNS Platform
• Pseudonymised data
• User management
• Device management
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in the RADAR-CNS Platform
Automatically Share unidentifiable identifiers across two systems
De-identified
Redcap API: Export / Import
Only access the RADAR Enrolment Form
Locking
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Management Portal: Subject Management
Subject creation in UMP triggered via RedCap
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Management Portal: Source Management Register devices (aka Sources) in the MP for given project and device-types
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Security • Token-based authentication and authorization
• Unique token for each application
• Fine granularity access control
READ
WRITE
WRITE
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pRMT app
App available in Google Play Store
https://goo.gl/ioopHq
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Measurements
Monitor upload to server
Android app config. tool
Connect patient with device
Devices (smartphone, wearable) with connection status to app with ID
pRMT app
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Live monitoring dashboards
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Live monitoring dashboards
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Make the research project data FAIR Findable • deposit into a public open access repository (unique identifiers, accompanied with
relevant metadata) Accessible • make sure appropriate data use agreements and procedures are set up with the
repository Interoperable • make sure that the data is in a standard format and has the appropriate metadata Re-useable • Re-usability of the data for research purposes is achieved by the above measures
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Data Access for Analysis
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Data Access for Analysis
Query data based on ● patient_ID ● sensor_ID ● time points (UTC)
key.userId key.sourceId value.time value.timeReceived value.x value.y value.z
radarTestTheHyve 00:07:80:1F:8D:A1 1492758973.86 1492758974.05 0.047 0.969 0.156
radarTestTheHyve 00:07:80:1F:8D:A1 1492758973.89 1492758974.05 0.047 0.969 0.156
radarTestTheHyve 00:07:80:1F:8D:A1 1492758973.92 1492758974.05 0.063 0.969 0.156
radarTestTheHyve 00:07:80:1F:8D:A1 1492758973.95 1492758974.94 0.047 0.969 0.156
radarTestTheHyve 00:07:80:1F:8D:A1 1492758973.98 1492758974.94 0.047 0.342 0.211
radarTestTheHyve 00:07:80:1F:8D:A1 1492758974.02 1492758974.94 0.047 0.342 0.211
radarTestTheHyve 00:07:80:1F:8D:A1 1492758974.06 1492758974.94 0.085 0.342 0.211
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RADAR Platform in Action: Epilepsy Study @ KCL
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On-site RADAR Platform deployment usecase @King's College Hospital, Telemetry Unit
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What makes the RADAR platform unique
• Open source • Apache 2 license
• No vendor lock-in
• Extensible • Plugin architecture: input, processing, output
• Live data analysis • Streaming data for direct feedback
• Standardized data • Schematized data storage