1. Intelligent Technologies for Renal Dialysis and Diagnostics
iTREND
Intelligent Technologies for Renal Dialysis and Diagnostics

2. iTrend Project
Funded by Mel Morris via MStart Foundation and iTrend
Kicked off 1st March 2017
3 year duration
Collaborative research programme between the University of Derby and the University of Nottingham
University of Derby
Prof Paul Stewart – Project Principal Investigator
Senior Researcher to be appointed
Prof Kath Mitchell – UoD VC + Psych Academic
Prof James Elander – Psych Academic
Carol Stalker – PhD Student Researcher
University of Nottingham
Prof Maarten Taal - Professor in Medicine, University of Nottingham, Honorary Consultant Nephrologist,
Royal Derby Hospital
Dr Nick Selby - Associate Professor of Nephrology, University of Nottingham,
Honorary Consultant Nephrologist, Department of Renal Medicine, Royal Derby Hospital

3. UoD Dept Psychology Patient Study
UoN Patient Study at Derby Royal
Ethics Approval
Cloud Mobile Dashboard
Dialyser
Patient
3G/Ethernet Interface
Matlab
Local Data Storage
Local Data Analysis
Signal Conditioning
Bio Sensors
Dynamic Physiology Model
Internet of Things
Low Cost Smart Sensors

4. Cloud Mobile Dashboard
Dialyser
Patient
3G/Ethernet Interface
Local Data Storage
Local Data Analysis
Signal Conditioning
Bio Sensors
Internet of Things
Low Cost Smart Sensors

5. Low cost sensing
IoT
Web Dashboard

6. Patient Study
Data Acquisition

7. What will it look like?

8. Patient Study Conducted via £50k Finometer Units
Data collected locally
Anomised and encrypted
Sent to project repository
Cloud, analytics and dashboard via wifi and 4g

9. Patient Condition Monitoring
Patient monitoring
Finometer
O2 Saturation
Critline - Bloodline: volume/O2 Saturation
Bio-Impedance
Machine monitoring
Blood volume / rate
Clearance (Na + Urea)
Patient variables
Heart rate
Heart rate variability
Stroke volume
Cardiac output
Blood Pressure
Peripheral resistance
In Silico
dynamic model
Phenotype + Med History

10. In Silico Dynamic Model

11. Project flow plan