Oliveira Filho Florêncio Mendes, Dos Santos Silva Ed Frank, de Freitas Santos Sanval Ebert, Bandeira Santos Alex Álisson, Zebende Gilney Figueira
Computer Engineering, SENAI CIMATEC UNIVERSITY, Salvador, Brazil.
State University of Feira de Santana, Bahia, Brazil.
Sci Rep. 2025 Mar 24;15(1):10068. doi: 10.1038/s41598-025-94252-2.
The control of Levodopa (L-dopa) in Parkinson's patients receiving chronic deep brain electrical stimulation (with an implant of an electrode into sub-cortical structures) will be studied here. Our main objective is to apply the Detrended Fluctuation Analysis (DFA) method and Shannon Entropy (H) in order to study the speed of tremor recorded in 16 patients with Parkinson's disease. These Parkinson's patients were divided into two groups (High Amplitude tremor and Low Amplitude tremor), and basically with two conditions of deep brain stimulation (on-off) and two conditions of L-dopa (on-off). These conditions (on-off) have a clear influence on the [Formula: see text] exponent and the Shannon Entropy respectively. In this sense, the auto-correlation exponent gives us information whether or not there is persistence in the signal produced by the Parkinsonian rest tremor, mainly differentiating those in Low and High Amplitude, or even identifying behavior change with a typical time scale. However, the Shannon Entropy gives us information about the uncertainty in the position of Parkinsonian rest tremor. In this way, a high value of H informs us that we have a high uncertainty in the signal of this tremor. Therefore, by combining these two techniques we have a better view of the (signal/noise) effects of deep brain stimulation and L-dopa (medication) in all patients with Parkinson's disease, and thus helping to make a better analysis of this health problem, and with the possibility of supplementation in the Unified Parkinson's Disease Rating Scale and Tremor Rating Scale, identifying fluctuation patterns on different time scales, the nature of the tremor, and its evolution over time.
本文将研究接受慢性深部脑电刺激（将电极植入皮质下结构）的帕金森病患者左旋多巴（L-多巴）的控制情况。我们的主要目标是应用去趋势波动分析（DFA）方法和香农熵（H）来研究16例帕金森病患者记录的震颤速度。这些帕金森病患者被分为两组（高振幅震颤组和低振幅震颤组），基本处于深部脑刺激的两种状态（开-关）和左旋多巴的两种状态（开-关）。这些状态（开-关）分别对[公式：见原文]指数和香农熵有明显影响。从这个意义上说，自相关指数为我们提供了帕金森静止性震颤产生的信号是否存在持续性的信息，主要区分低振幅和高振幅的情况，甚至识别具有典型时间尺度的行为变化。然而，香农熵为我们提供了关于帕金森静止性震颤位置不确定性的信息。这样，H值高表明该震颤信号的不确定性高。因此，通过结合这两种技术，我们能更好地了解深部脑刺激和左旋多巴（药物治疗）对所有帕金森病患者的（信号/噪声）影响，从而有助于更好地分析这个健康问题，并有可能补充统一帕金森病评定量表和震颤评定量表，识别不同时间尺度上的波动模式、震颤的性质及其随时间的演变。
