Using Portable Transducers to Measure Tremor Severity

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

Quantitative Gait and Balance Outcomes for Ataxia Trials: Consensus Recommendations by the Ataxia Global Initiative Working Group on Digital-Motor Biomarkers

\ua9 2023, The Author(s).With disease-modifying drugs on the horizon for degenerative ataxias, ecologically valid, finely granulated, digital health measures are highly warranted to augment clinical and patient-reported outcome measures. Gait and balance disturbances most often present as the first signs of degenerative cerebellar ataxia and are the most reported disabling features in disease progression. Thus, digital gait and balance measures constitute promising and relevant performance outcomes for clinical trials. This narrative review with embedded consensus will describe evidence for the sensitivity of digital gait and balance measures for evaluating ataxia severity and progression, propose a consensus protocol for establishing gait and balance metrics in natural history studies and clinical trials, and discuss relevant issues for their use as performance outcomes

Quantitative gait and balance outcomes for ataxia trials: consensus recommendations by the Ataxia Global Initiative Working Group on Digital-Motor Biomarkers

With disease-modifying drugs on the horizon for degenerative ataxias, ecologically valid, finely granulated, digital health measures are highly warranted to augment clinical and patient-reported outcome measures. Gait and balance disturbances most often present as the first signs of degenerative cerebellar ataxia and are the most reported disabling features in disease progression. Thus, digital gait and balance measures constitute promising and relevant performance outcomes for clinical trials.This narrative review with embedded consensus will describe evidence for the sensitivity of digital gait and balance measures for evaluating ataxia severity and progression, propose a consensus protocol for establishing gait and balance metrics in natural history studies and clinical trials, and discuss relevant issues for their use as performance outcomes

Morphology Analysis of Intracranial Pressure Using Pattern Matching Techniques

We present a clustering algorithm based on Dynamic Time Warping (DTW) to automatically classify intracranial pressure (ICP) beats based on their morphology. The algorithm detects, classifies and labels each beat as a low--pressure or high--pressure beat based on morphology. The trend is removed during prepocessing to ensure the classifications are independent of the mean ICP. An ICP beat detection algorithm is used to automatically detect each beat. We measured the performance of the algorithm compared to expert classification of ICP beats acquired from intensive care unit patients using linear and non-- linear temporal alignment techniques. The algorithm achieved a superior performance using non--linear temporal alignment

Winning entry of the K. U. leuven time series prediction competition

In this paper we describe the winning entry of the time series prediction competition which was part of the International Workshop on Advanced Black-Box Techniques for Nonlinear Modeling,held at K.U. Leuven, Belgium on July 8–10, 1998. We also describe the source of the data set, a nonlinear transform of a 5-scroll generalized Chua’s circuit. Participants were given 2000 data points and were asked to predict the next 200 points in the series. The winning entry exploited symmetry that was discovered during exploratory data analysis and a method of local modeling designed specifically for the prediction of chaotic time series. This method includes an exponentially weighted metric, a nearest trajectory algorithm, integrated local averaging, and a novel multi-step ahead cross-validation estimation of model error for the purpose of parameter optimization. 2

Statistical Methods of Analysis and Visualization of . . .

INTRODUCTION Chronic high frequency stimulation of the subthalamic nucleus (STN) has been shown to have dramatic effects for the treatment of symptoms of Parkinsons disease (PD) [13 ]. Nevertheless, the ideal target location in humans is not known. Furthermore, the methods to select the current target of the STN remain non-standard among surgeons [4, 5]. In both clinical and experimental studies neuronal structures have been classified by three parameters: kinesthetic activity (response to movement), phasic activity (spike pattern), and tonic activity (firing rate) [6]. The analysis of phasic activity (spike pattern) has depended largely on human description and observer interpretation of spike activity, which introduce an element of human error and inconsistency and which cannot form a basis for comparison between different researchers. The kinesthetic and tonic activity on the other hand can be evaluated based on objective characteristics of the spike trai