Literature DB >> 27511464

Clinical validation of a precision electromagnetic tremor measurement system in participants receiving deep brain stimulation for essential tremor.

Thushara Perera1, Shivanthan A C Yohanandan, Wesley Thevathasan, Mary Jones, Richard Peppard, Andrew H Evans, Joy L Tan, Colette M McKay, Hugh J McDermott.   

Abstract

Tremor is characterized commonly through subjective clinical rating scales. Accelerometer-based techniques for objective tremor measurement have been developed in the past, yet these measures are usually presented as an unintuitive dimensionless index without measurement units. Here we have developed a tool (TREMBAL) to provide quantifiable and objective measures of tremor severity using electromagnetic motion tracking. We aimed to compare TREMBAL's objective measures with clinical tremor ratings and determine the test-retest reliability of our technique. Eight participants with ET receiving deep brain stimulation (DBS) therapy were consented. Tremor was simultaneously recorded using TREMBAL and video during DBS adjustment. After each adjustment, participants performed a hands-outstretched task (for postural tremor) and a finger-nose task (for kinetic tremor). Video recordings were de-identified, randomized, and shown to a panel of movement disorder specialists to obtain their ratings. Regression analysis and Pearson's correlations were used to determine agreement between datasets. Subsets of the trial were repeated to assess test-retest reliability. Tremor amplitude and velocity measures were in close agreement with mean clinical ratings (r  >  0.90) for both postural and kinetic tremors. Test-retest reliability for both translational and rotational components of tremor showed intra-class correlations  >0.80. TREMBAL assessments showed that tremor gradually improved with increasing DBS therapy-this was also supported by clinical observation. TREMBAL measurements are a sensitive, objective and reliable assessment of tremor severity. This tool may have application in clinical trials and in aiding automated optimization of deep brain stimulation.

Entities:  

Mesh:

Year:  2016        PMID: 27511464     DOI: 10.1088/0967-3334/37/9/1516

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  4 in total

1.  Using Remotely Supervised At-Home TES for Enhancing Mental Resilience.

Authors:  Jasmina Paneva; Inge Leunissen; Teresa Schuhmann; Tom A de Graaf; Morten Gørtz Jønsson; Balder Onarheim; Alexander T Sack
Journal:  Front Hum Neurosci       Date:  2022-06-09       Impact factor: 3.473

2.  Neurophysiological analysis of the clinical pull test.

Authors:  Joy Lynn Tan; Thushara Perera; Jennifer L McGinley; Shivanthan Arthur Curtis Yohanandan; Peter Brown; Wesley Thevathasan
Journal:  J Neurophysiol       Date:  2018-08-15       Impact factor: 2.714

3.  Biomechanical System Versus Observational Rating Scale for Parkinson's Disease Tremor Assessment.

Authors:  Ping Yi Chan; Zaidi Mohd Ripin; Sanihah Abdul Halim; Muhammad Imran Kamarudin; Kwang Sheng Ng; Gaik Bee Eow; Kenny Tan; Chun Fai Cheah; Linda Then; Nelson Soong; Jyh Yung Hor; Ahmad Shukri Yahya; Wan Nor Arifin; John Tharakan; Muzaimi Mustapha
Journal:  Sci Rep       Date:  2019-05-31       Impact factor: 4.379

4.  Automatic Resting Tremor Assessment in Parkinson's Disease Using Smartwatches and Multitask Convolutional Neural Networks.

Authors:  Luis Sigcha; Ignacio Pavón; Nélson Costa; Susana Costa; Miguel Gago; Pedro Arezes; Juan Manuel López; Guillermo De Arcas
Journal:  Sensors (Basel)       Date:  2021-01-04       Impact factor: 3.576

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.