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Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation

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Federated web-accessible clinical data management within an extensible neuroimaging database.

I Burak Ozyurt¹, David B Keator, Dingying Wei

¹Department of Psychiatry, University of California at San Diego, San Diego, CA, USA. iozyurt@ucsd.edu

Neuroinformatics

|June 23, 2010

Summary

A new data management system, the Human Clinical Imaging Database (HID) and Toolkit, simplifies handling diverse clinical neuroimaging data. It offers flexible storage, integrated data entry, and distributed querying for research communities.

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Area of Science:

Neuroimaging
Data Science
Clinical Research Informatics

Background:

Managing large, diverse clinical neuroimaging datasets is challenging due to evolving protocols and data types.
Existing data management systems struggle to incorporate new research data and experimental advances.

Purpose of the Study:

Introduce an extensible data management system, the Human Clinical Imaging Database (HID) and Toolkit, for clinical neuroimaging studies.
Design a flexible schema to accommodate new data types without modification.
Enhance data consistency and streamline data entry through integrated tools.

Main Methods:

Developed a database schema to support diverse data types, including experimental parameters and subject-specific information.
Integrated clinical data entry tools (Clinical Assessment Layout Manager - CALM) and a management engine (GAME) for consistent data reporting.
Implemented a service-oriented architecture for distributed access and a parallel query builder for cross-database querying.

Main Results:

The Human Clinical Imaging Database (HID) and Toolkit allows flexible storage of various neuroimaging data types.
Embedded tools improve data consistency and automate entry.
The system supports distributed operation and web-accessible queries across federated databases.

Conclusions:

The Human Clinical Imaging Database (HID) and Toolkit provides a robust, extensible solution for managing complex clinical neuroimaging data.
Its open-source nature and flexible design facilitate adoption and integration within research communities.
The system enhances data management efficiency, consistency, and accessibility for multi-site neuroimaging studies.