Literature DB >> 20417235

Force sensing system for automated assessment of motor performance during fMRI.

Bill Rogers1, Wei Zhang, Shalini Narayana, Jack L Lancaster, Donald A Robin, Peter T Fox.   

Abstract

Finger tapping sequences are a commonly used measure of motor learning in functional imaging studies. Subjects repeat a defined sequence of finger taps as fast as possible for a set period of time. The number of sequences completed per unit time is the measure of performance. Assessment of speed and accuracy is generally accomplished by video recording the session then replaying in slow motion to assess rate and accuracy. This is a time consuming and error prone process. Keyboards and instrumented gloves have also been used for task assessment though they are relatively expensive and not usually compatible in a magnetic resonance imaging (MRI) scanner. To address these problems, we developed a low cost system using MRI compatible force sensitive resistors (FSR) to assess the performance during a finger sequence task. This system additionally provides information on finger coordination including time between sequences, intervals between taps, and tap duration. The method was validated by comparing the FSR system results with results obtained by video analysis during the same session. Copyright 2010 Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 20417235     DOI: 10.1016/j.jneumeth.2010.04.011

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  3 in total

1.  The effect of biomechanical variables on force sensitive resistor error: Implications for calibration and improved accuracy.

Authors:  Jonathon S Schofield; Katherine R Evans; Jacqueline S Hebert; Paul D Marasco; Jason P Carey
Journal:  J Biomech       Date:  2016-02-09       Impact factor: 2.712

2.  Concurrent TMS to the primary motor cortex augments slow motor learning.

Authors:  Shalini Narayana; Wei Zhang; William Rogers; Casey Strickland; Crystal Franklin; Jack L Lancaster; Peter T Fox
Journal:  Neuroimage       Date:  2013-07-15       Impact factor: 6.556

3.  An engineered glove for investigating the neural correlates of finger movements using functional magnetic resonance imaging.

Authors:  Laura Bonzano; Andrea Tacchino; Luca Roccatagliata; Matilde Inglese; Giovanni Luigi Mancardi; Antonio Novellino; Marco Bove
Journal:  Front Hum Neurosci       Date:  2015-09-14       Impact factor: 3.169

  3 in total

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