A stochastic time series model for hand tremor.

Randall, Jamie

doi:10.1152/jappl.1973.34.3.390

Cited by 23 publications

(13 citation statements)

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“…As with clinical examination, the amplitude Correspondence to: J. Honerkamp provides, by definition, a good criterion to distinguish between physiological (normal) and pathological forms of tremor, but neither amplitude nor peak frequency helps to decide reliably which kind of pathological tremor is present (Deuschl et al 1992). Previous work showed that physiological tremor can be regarded as a linear stochastic process consistent with the interpretation of the mechanical system of the hand as a damped linear oscillator driven by the uncorrelated firing of motoneurons (Randall 1973;Rietz and Stiles 1974;Elble and Koller 1990). In the case of pathological tremors nonlinear effects (up to chaos) have been established ).…”

Section: Introductionsupporting

confidence: 53%

Characteristics of hand tremor time series

et al. 1993

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Tremor is classified into physiological, essential, and parkinsonian tremor by means of clinical criteria. The aim of our work was to extract quantitative features from the measurements of the acceleration of human postural hand tremor. Different mathematical methods were adopted and modified in order to separate these three types of tremor. Best discrimination between physiological and pathological tremors has been achieved by methods distinguishing nonlinear from linear behavior. On the other hand, methods separating different forms of nonlinear behavior have been found to be superior in discriminating parkinsonian and essential tremor. By these methods physiological and pathological tremors can be separated with an error rate below 20% and essential and parkinsonian tremor with an error rate below 10%. This may help to classify tremor time series by objective mathematical criteria and may increase the understanding of the pathophysiological differences underlying these kinds of tremor.

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Section: Introductionsupporting

confidence: 53%

Characteristics of hand tremor time series

et al. 1993

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“…We will use the phase spectra as an indicator for the presence of reflex contributions by comparing the predicted phase spectra under both hypotheses with those estimated from measured data. For both cases the mechanical properties of the hand are modeled by an autoregressive process of order to two (AR[2]) covered by observational noise (Stiles and Randall 1967;Randall 1973;Rietz and Stiles 1974;Elble and Koller 1990;Gantert et al 1992). The synchronized (possible) non-reflex part of the rectified EMG is also described by an AR[2] process.…”

Section: Introductionmentioning

confidence: 99%

“…Time series of hand tremor and the related muscle activities of the flexor and extensor muscles are obtained by measuring the acceleration of the hand (denoted here by ACC) and the surface electromyogram (denoted here by EMG). The ACC data of physiological tremor have been described as a linear stochastic process driven by uncorrelated firing motoneurons (Stiles and Randall 1967;Randall 1973;Rietz and Stiles 1974;Elble and Koller 1990;Gantert et al 1992;Timmer et al 1993). The description of physiological tremor by a linear model is reasonable because linear approximations hold due to its small amplitude.…”

Section: Introductionmentioning

confidence: 99%

Cross-spectral analysis of physiological tremor and muscle activity

Timmer¹,

Lauk²,

Pfleger³

et al. 1998

Biological Cybernetics

108

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We investigate the relationship between the extensor electromyogram (EMG) and tremor times series in physiological hand tremor by cross-spectral analysis. Special attention is directed to the phase spectrum and the effects of observational noise. We calculate the theoretical phase spectrum for a second-order linear stochastic process and compare the results to measured tremor data recorded from subjects who did not show a synchronized EMG activity in the corresponding extensor muscle. The results show that physiological tremor is well described by the proposed model and that the measured EMG represents a Newtonian force by which the muscle acts on the hand.

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“…We will use the phase spectra as an indicator for the presence of re¯ex contributions by comparing the predicted phase spectra under both hypotheses with those estimated from measured data. For both cases, the mechanical properties of the hand are modeled by an autoregressive process of order 2 (AR[2]) covered by observational noise (Stiles and Randall 1967;Randall 1973;Rietz and Stiles 1974;Elble and Koller 1990;Gantert et al 1992). The synchronized (possible) nonre¯ex part of the recti®ed EMG is also described by an AR[2] process.…”

Section: Introductionmentioning

confidence: 99%

Cross-spectral analysis of physiological tremor and muscle activity

Timmer¹,

Lauk²,

Pfleger³

et al. 1998

Biological Cybernetics

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We investigated the relationship between synchronized muscle activity and tremor time series in (enhanced) physiological tremor by cross-spectral analysis. Special attention was directed to the phase spectrum and its potential to clarify the contribution of reflex mechanisms to physiological tremor. The phase spectra are investigated assuming that the electromyogram (EMG) synchronization was caused by a reflex or a central oscillator. Comparing these results to phase spectra of measured data, we found a significant contribution of reflexes. But reflexes only modify existing peaks in the power spectrum. The main agents of physiological tremor are an efferent pace and the resonant behavior of the biomechanical system.

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A stochastic time series model for hand tremor.

Cited by 23 publications

References 0 publications

Characteristics of hand tremor time series

Characteristics of hand tremor time series

Cross-spectral analysis of physiological tremor and muscle activity

Cross-spectral analysis of physiological tremor and muscle activity

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