dorsal/arxiv
View SchemaRegular and stochastic behavior of Parkinsonian pathological tremor signals
| Authors | Renat M. Yulmetyev, Sergey A. Demin, Oleg Yu. Panischev, Peter Hänggi, Serge F. Timashev, Grigoriy V. Vstovsky |
|---|---|
| Categories | |
| ArXiv ID | physics/0603030 |
| URL | https://arxiv.org/abs/physics/0603030 |
| DOI | 10.1016/j.physa.2006.01.077 |
Abstract
Regular and stochastic behavior in the time series of Parkinsonian pathological tremor velocity is studied on the basis of the statistical theory of discrete non-Markov stochastic processes and flicker-noise spectroscopy. We have developed a new method of analyzing and diagnosing Parkinson's disease (PD) by taking into consideration discreteness, fluctuations, long- and short-range correlations, regular and stochastic behavior, Markov and non-Markov effects and dynamic alternation of relaxation modes in the initial time signals. The spectrum of the statistical non-Markovity parameter reflects Markovity and non-Markovity in the initial time series of tremor. The relaxation and kinetic parameters used in the method allow us to estimate the relaxation scales of diverse scenarios of the time signals produced by the patient in various dynamic states. The local time behavior of the initial time correlation function and the first point of the non-Markovity parameter give detailed information about the variation of pathological tremor in the local regions of the time series. The obtained results can be used to find the most effective method of reducing or suppressing pathological tremor in each individual case of a PD patient. Generally, the method allows one to assess the efficacy of the medical treatment for a group of PD patients.
{
"annotation_id": "c871ed90-87a8-4c87-aede-4b58e7f1cf5c",
"date_created": "2026-03-02T18:01:06.617000Z",
"date_modified": "2026-03-02T18:01:06.617000Z",
"file_hash": "e3b4cb2ae419025ea9e6b23392d14ebd4f80b58867238d17279a6ab63b78ac87",
"private": false,
"record": {
"abstract": "Regular and stochastic behavior in the time series of Parkinsonian\npathological tremor velocity is studied on the basis of the statistical theory\nof discrete non-Markov stochastic processes and flicker-noise spectroscopy. We\nhave developed a new method of analyzing and diagnosing Parkinson\u0027s disease\n(PD) by taking into consideration discreteness, fluctuations, long- and\nshort-range correlations, regular and stochastic behavior, Markov and\nnon-Markov effects and dynamic alternation of relaxation modes in the initial\ntime signals. The spectrum of the statistical non-Markovity parameter reflects\nMarkovity and non-Markovity in the initial time series of tremor. The\nrelaxation and kinetic parameters used in the method allow us to estimate the\nrelaxation scales of diverse scenarios of the time signals produced by the\npatient in various dynamic states. The local time behavior of the initial time\ncorrelation function and the first point of the non-Markovity parameter give\ndetailed information about the variation of pathological tremor in the local\nregions of the time series. The obtained results can be used to find the most\neffective method of reducing or suppressing pathological tremor in each\nindividual case of a PD patient. Generally, the method allows one to assess the\nefficacy of the medical treatment for a group of PD patients.",
"arxiv_id": "physics/0603030",
"authors": [
"Renat M. Yulmetyev",
"Sergey A. Demin",
"Oleg Yu. Panischev",
"Peter H\u00e4nggi",
"Serge F. Timashev",
"Grigoriy V. Vstovsky"
],
"categories": [
"physics.med-ph",
"physics.data-an"
],
"doi": "10.1016/j.physa.2006.01.077",
"title": "Regular and stochastic behavior of Parkinsonian pathological tremor signals",
"url": "https://arxiv.org/abs/physics/0603030"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "71fd3a3c-266b-4c24-b245-6e65355f43ed",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}