Professor Ian Craddock
B.Eng., Ph.D.(Bristol), C.Eng
Current positions
Contact
Press and media
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Research interests
- Director of the EPSRC funded SPHERE IRC (£12M, ~30 postdocs and 10 PhD students).
- Pervasive health.
- Technology for self-management of long term health conditions.
- Ultra low power wireless communications.
- Data fusion and clinical decision support.
- Antennas.
- Electromagenetics, radar and inverse scattering.
Projects and supervisions
Research projects
LEAP (Leadership Engagement Acceleration & Partnership) - an EPSRC Digital Health Hub
Principal Investigator
Managing organisational unit
Bristol Veterinary SchoolDates
01/10/2023 to 30/09/2026
LEAP (Leadership Engagement Acceleration & Partnership) - an EPSRC Digital Health Hub
Principal Investigator
Managing organisational unit
Department of Electrical & Electronic EngineeringDates
01/10/2023 to 30/09/2026
LEAP (Leadership Engagement Acceleration & Partnership) - an EPSRC Digital Health Hub
Principal Investigator
Managing organisational unit
Department of Electrical & Electronic EngineeringDates
01/10/2023 to 30/09/2026
LEAP (Leadership Engagement Acceleration & Partnership) - an EPSRC Digital Health Hub
Principal Investigator
Managing organisational unit
School of Engineering Mathematics and TechnologyDates
01/10/2023 to 30/09/2026
Transforming the Objective Real-world measUrement of Symptoms (TORUS)
Principal Investigator
Managing organisational unit
Department of Electrical & Electronic EngineeringDates
01/10/2023 to 30/09/2028
Thesis supervisions
Publications
Recent publications
25/03/2024Real World Parkinson’s Disease Tremor and Score Prediction using Wearable IMU Sensors
2023 IEEE International Conference on E-health Networking, Application & Services (Healthcom)
Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting
KDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations
A multi-sensor dataset with annotated activities of daily living recorded in a residential setting
Scientific Data
Automated Real-World Video Analysis of Sit-to-Stand Transitions Predicts Parkinson’s Disease Severity
Digital Biomarkers
Thesis
Enhanced numerical techniques for time domain electromagnetic analysis
Supervisors
Award date
01/01/1995