The Development of a System for the Measurement of Tremor

Tremor Clinical Trial

Official title: The Development of a System for the Measurement of Tremor

Status Recruiting

Clinical Trial Summary

The goal of this clinical trial is to develop a system which can be used to measure movements in people with Essential Tremor (with or without dystonia). The main questions it aims to answer are: - Can individuals with Essential Tremor be distingushed from individuals without tremor using Virtual Reality (VR) - Can the current Essential Tremor Assessment Scale (the TETRAS) be reproduced in VR - Can Essential Tremor be quantified using a measurement system - Can Dystonia be quantified using a measurement system. Participants will don the equipment used to measure their tremor and replicate a series of standardised movements to measure their tremor, in and out of the VR platform. The assessment will take no longer than an hour.

Clinical Trial Description

This study aims to develop a way of objectively measuring the neurological disorders, Essential Tremor (ET) and dystonia. These conditions can affect the upper and lower limbs, head, voice, face and trunk. ET and dystonia can be difficult to assess and treat, particularly if severe, and therapies are limited. Currently the severity of these conditions is formally assessed by clinician rated scales such as the Essential Tremor Rating Assessment Scale (TETRAS) which is biased towards the upper limbs, requires training and is not objective. There is a need for a more precise, less variable measure of tremor that can used easily be non-expert clinicians. This study questions whether it is possible to quantify ET and dystonia using a measurement system in a virtual reality (VR) environment. Data will be collected from measurement sensors embedded in the VR environment from healthy control participants, and those with ET with and without dystonia. Participants will be placed in a VR environment and instructed to perform the TETRAS. This will help to develop an algorithm which can measure ET severity using machine learning. It is expected that the algorithm will provide a better assessment of ET and dystonia than the TETRAS. This study may pave the way towards the development of simpler devices to which the algorithm can be applied. ;

Related Conditions & MeSH terms

• Tremor

• NCT number: NCT06386822
• Study type: Interventional
• Source: The Bionics Institute of Australia
• Contact: Sarah Osborn, BSc
• Phone: 61396677500
• Email: sosborn@bionicsinstitute.org
• Status: Recruiting
• Phase: N/A
• Start date: August 1, 2023
• Completion date: December 2024