Information about technology selection, acquisition, and troubleshooting for remote research studies, including mobile technologies.
This article summarizes the tools available for collaboration, file storage and file sharing at University of Michigan and Michigan Medicine.
A compilation of software and cloud services for creating forms, surveys, polls, questionnaires, etc. A compilation of software and cloud services for electronic data capture, forms, surveys, polls, questionnaires, etc. Find the right survey tool for business, clinical or research use.
This article describes how to move a Google Analytics property between accounts, without loosing existing analytics data.
Microsoft Power Automate is a flexible, low-code automation tool available to all Michigan Medicine faculty and staff. Each automation, or flow, consists of "triggers" that kick off the automation, "actions" that are performed on data through interconnected logical steps, and "connectors" to other applications, databases, and systems. This article presents a brief summary of the connectors that are currently available in the MM environment.
Selecting technology to manage a study remotely is a big decision. This article includes considerations for selecting technology and information on vendors that are (at the time of writing) approved for use in research at U-M.
This article will help researchers plan for and overcome technology access challenges in the planning phase of their study.
Understanding the technology elements for a study utilizing wearable and mobile technologies will assist researchers during the study planning process in several ways.
- Build a more accurate study budget.
- Develop a Data Management & Sharing Plan, which can be a requirement for funders and journal submissions.
- Prepare for regulatory and compliance processes, like an Information Assurance (IA) review, if needed
The University of Michigan and Michigan Medicine offer generative AI tools including UMGPT, Microsoft Copilot, Google Gemini and Gemini Notebook. This guide explains how to choose tools and models, get started, and use AI for research, clinical, teaching and administrative work.
A compilation of software tools used by MDEN mobile tech researchers for working with mobile data, including: wearable programming, mobile app development, data extraction, data analysis, data presentation and visualizations, and data pipelines.
Active Tasks in ResearchKit allow researchers to collect data directly from study participants through physical performance activities. These tasks use sensors and other features on iOS and Android devices to provide reliable and precise measurements of various physical and cognitive functions.
MTC focuses on consumer-grade, over-the-counter wearable and nearable devices with potential clinical applications. We concentrate on study management platforms from vetted vendors, although we can refer researchers to other resources when necessary.