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Review
. 2016 May 17:6:375.
doi: 10.7916/D8DR2VCC. eCollection 2016.

Using Portable Transducers to Measure Tremor Severity

Affiliations
Review

Using Portable Transducers to Measure Tremor Severity

Rodger J Elble et al. Tremor Other Hyperkinet Mov (N Y). .

Abstract

Background: Portable motion transducers, suitable for measuring tremor, are now available at a reasonable cost. The use of these transducers requires knowledge of their limitations and data analysis. The purpose of this review is to provide a practical overview and example software for using portable motion transducers in the quantification of tremor.

Methods: Medline was searched via PubMed.gov in December 2015 using the Boolean expression "tremor AND (accelerometer OR accelerometry OR gyroscope OR inertial measurement unit OR digitizing tablet OR transducer)." Abstracts of 419 papers dating back to 1964 were reviewed for relevant portable transducers and methods of tremor analysis, and 105 papers written in English were reviewed in detail.

Results: Accelerometers, gyroscopes, and digitizing tablets are used most commonly, but few are sold for the purpose of measuring tremor. Consequently, most software for tremor analysis is developed by the user. Wearable transducers are capable of recording tremor continuously, in the absence of a clinician. Tremor amplitude, frequency, and occurrence (percentage of time with tremor) can be computed. Tremor amplitude and occurrence correlate strongly with clinical ratings of tremor severity.

Discussion: Transducers provide measurements of tremor amplitude that are objective, precise, and valid, but the precision and accuracy of transducers are mitigated by natural variability in tremor amplitude. This variability is so great that the minimum detectable change in amplitude, exceeding random variability, is comparable for scales and transducers. Research is needed to determine the feasibility of detecting smaller change using averaged data from continuous long-term recordings with wearable transducers.

Keywords: Fourier analysis; Tremor; accelerometry; measurement; transducer.

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Conflict of interest statement

Funding: This work was supported by a grant from the Spastic Paralysis Research Foundation of Kiwanis International, Illinois-Eastern Iowa District.

Conflicts of Interest: R.E. has collaborated with Great Lakes NeuroTechnologies and APDM Wearable Technologies in the development of their motion transducers. J.M. and Portland State University have a financial interest in APDM, Inc., a company that may have a commercial interest in the results of this research and technology. This potential conflict has been reviewed and managed by Oregon Health & Science University.

Ethics statement: This study was performed in accordance with the ethical standards detailed in the Declaration of Helsinki. The authors' institutional ethics committee has approved this study and all patients have provided written informed consent.

Figures

Figure 1
Figure 1. Cartoon of a Motion Sensor (Green) Mounted on the Dorsum of the Hand. In general, tremor in a body part will consist of rotation and translation in three-dimensional space. Many modern motion sensors contain a triaxial accelerometer and gyroscope for capturing this motion.
Figure 2
Figure 2. Amplitude Spectra (Degrees/Second) of Hand Tremor Recorded with a Gyroscope Transducer. Tremor was recorded from the dorsum of the hand while the upper limb was at rest, extended horizontally and anteriorly, and while performing finger-to-nose movements (graphs left to right). The patient has a Holmes tremor due to a previous midbrain hemorrhage. The tremor spectral peaks are very sharp during rest and posture. During movement, the tremor peak is superimposed on spectral activity produced by the voluntary movement. The mean tremor amplitude in degrees is the peak amplitude divided by 2πf, where f is the tremor frequency (3.8 Hz).
Figure 3
Figure 3. Tremor in an Archimedes Spiral Recorded with a Digitizing Tablet. In the left column, the X component of an Archimedes spiral (displacement) is shown with its first and second derivatives (velocity and acceleration), computed with a frequency impulse response differentiator in MATLAB. The power spectrum of displacement, velocity, and acceleration are shown on the right. Note how differentiation accentuates the 4.3 Hz tremor relative to the lower-frequency voluntary movement.
Figure 4
Figure 4. The Time-frequency Power Spectrum of Tremor Recorded with a Triaxial Gyroscope on the Wrist of a Patient with Parkinson Disease. This recording was made during normal uncontrolled activities. The resultant power spectrum is the sum of the power spectra of the X, Y, and Z channels. The image color intensity shows how the signal power (radians2/second2; 2π radians = 360 degrees) is distributed over time and frequency. Note how the presence and amplitude of tremor fluctuate with time. The 5 Hz tremor nearly stops at 21 minutes, when there is an abrupt increase in normal voluntary movement.
Figure 5
Figure 5. Tremor from 19 Patients with Essential Tremor Recorded with a Digitizing Tablet while Each Patient drew the Large and Small Archimedes Spirals of the Fahn–Tolosa–Marín (FTM) Scale. The average tremor amplitude (T) and average tremor rating (FTM) of the four spirals (two with each hand) are plotted on a log base 10 scale. The regression line and equation are shown. A logarithmic relationship between transducer measure and tremor rating has been found for all transducers used in tremor studies.

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