Abstract

Although upper limb motor impairments are common, the primary tools for assessing and tracking these impairments in a clinical setting are subjective, qualitative rating scales that lack resolution and repeatability. Markerless motion capture technology has the potential to greatly improve clinical assessment by providing quick, low-cost, and accurate tools to objectively quantify motor deficits. Here we lay some of the groundwork necessary to enable markerless motion capture systems to be used in clinical settings. First, we adapted five motor tests common in clinical assessments so they can be administered via markerless motion capture. We implemented these modified tests using a particular motion capture sensor (Leap MotionTM Controller, hereafter referred to as the Leap Motion sensor) and administered the tests to 100 healthy subjects to evaluate the feasibility of administrating these tests via markerless motion capture. Second, to determine the ability of the Leap Motion sensor to accurately measure tremor, we characterized the frequency response of the Leap Motion sensor. During the administration of the five modified motor tests on 100 healthy subjects, the subjects had little trouble interfacing with the Leap Motion sensor and graphical user interface, performing the tasks with ease. The Leap Motion sensor maintained an average sampling rate above 106 Hz across all subjects during each of the five tests. The rate of adverse events caused by the Leap Motion sensor (mainly jumps in time or space) was generally below 1%. In characterizing the frequency response of the Leap Motion sensor, we found its bandwidth to vary between 1.7 and 5.5 Hz for actual tremor amplitudes above 1.5 mm, with larger bandwidth for larger amplitudes. To improve the accuracy of tremor measurements, we provide the magnitude ratios that can be used to estimate the actual amplitude of the oscillations from the measurements by the Leap Motion sensor. These results suggest that markerless motion capture systems are on the verge of becoming suitable for routine clinical use, but more work is necessary to further improve the motor tests before they can be administered via markerless motion capture with sufficient robustness for clinical settings.

Degree

MS

College and Department

Ira A. Fulton College of Engineering and Technology; Mechanical Engineering

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2016-12-01

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd8998

Keywords

leap motion sensor, markerless motion capture, motor assessment, motor test, motor control, neurological exam, clinical rating scale, kinematics, hand, fingers, palm

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