Classification of extremity movements by visual observation of signals and their transforms

Manuel Enrique Hernandez, Liran Ziegelman, Tanvi Kosuri, Husain Hakim, Luqi Zhao, Kelly Alexander Mills, James Robert Brašić

Research output: Contribution to journalArticlepeer-review

Abstract

A low-cost quantitative continuous measurement of movements utilizes accelerometers to generate signal outputs to precisely record the positions of extremities during the performance of movements. This procedure can readily be accomplished with inexpensive materials constructed indivisuals throughout the world. The proposed protocol provides the framework for trained raters to assess the signal outputs by visual observation to generate objective measurements like the measurements of the actual movements. Expert raters can then remotely give quantitative suggestions for providers in underserved regions to utilize precision medicine to develop optimal treatment plans tailored to the specific needs of each individual. The proposed protocol lays the foundations for experts located in tertiary centers to provide optimal assessments of signal outputs generated remotely in underserved regions. This protocol provides the means to address gaps in current research including the dearth of objective measurements of movements utilizing automatic intelligence and machine learning to accurately and precisely analyze movement assessments. Future research will include the development of robotic tools to perform assessments and analyses of the movements of human beings to enhance the conduct of movement evaluations of people with Parkinson's disease and related conditions to apply precision medicine for optimal diagnostic and therapeutic interventions.

Original languageEnglish (US)
Article number101739
JournalMethodsX
Volume9
DOIs
StatePublished - Jan 2022

Keywords

  • Accelerometer
  • Continuous wavelet analysis
  • Experimental error
  • Fourier analysis
  • Inertia measurement units
  • Movement disorders
  • Multiple system atrophy
  • Rating scales
  • Typical development
  • Visual classification of extremity signals and their transforms
  • Wearable sensors

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Medical Laboratory Technology

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