Tremor Retrainer App
Shows promise in preliminary research
App Summary
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Detailed Description
Functionality & Mechanism
Developed by neurologists at the University of Virginia and University of Cincinnati, this app delivers an entrainment-based intervention for functional tremor. The system leverages internal smartphone accelerometers to analyze a patient's baseline tremor frequency. It then generates personalized, pulsed auditory cues at a lower frequency for the patient to match with prescribed wrist movements. A visual gauge on the interface provides continuous biofeedback on performance, facilitating motor retraining through a structured, bio-adaptive protocol.
Evidence & Research Context
- A preliminary pilot study (N=3) evaluated the usability and acceptability of a one-week protocol in pediatric patients with functional tremor.
- The intervention is grounded in the principle of entrainment, adapting a key diagnostic feature of functional tremor into a potential therapeutic strategy.
- All participants in the pilot evaluation reported the application was easy to use and could be effective, providing feedback that informed subsequent software development.
Intended Use & Scope
This application is designed exclusively for investigational use by researchers and participants within formal clinical trials. It functions as a potential adjunctive, biofeedback-based therapy for functional tremor. The system is not a validated standalone treatment for general clinical use and must be administered under the supervision of qualified research personnel.
Studies & Publications
Peer-reviewed research associated with this app.
Development and Pilot Testing of the Tremor Retrainer Smartphone Application for the Treatment of Functional Tremor
Garris et al. (2023) · Tremor and Other Hyperkinetic Movements
Feasibility confirmed — all three patients found the app easy to use and potentially effective.
App Information
Developer
University of VirginiaCategory
Evidence Profile
Shows promise in preliminary research
Platforms
Updated
Aug 2025
© 2025 University of Virginia
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