Despite the efficiency of deep brain stimulation (DBS) in the treatment of Parkinson's disease (PD), the respective systems need to be further optimized. The lack of accurate PD-related quantitative biomarkers limits the improvement of adaptive DBS (aDBS) systems. Now, most DBS devices are open-loop sets with fixed stimulation parameters, which prevents them from coping with movement fluctuations and rapid changes of the symptoms. At the same time, ample evidence has shown that abnormal oscillations in the composition of local field potential (LFP) signals recorded in PD patients can reflect, to a certain extent, the crucial symptoms of the desease. Therefore, acquisition of LFP signals, extraction of abnormal oscillations, and acquisition of indicative biomarkers is the core technical issue with respective to the aDBS systems. Here, we review the current feature extraction methods in PD, summarize results of the latest research, analyze the difficulties of extracting the quantitative biomarkers, and discuss the developmental trend of feature extraction for aDBS.
from Physiology via xlomafota13 on Inoreader https://ift.tt/2wYdRkc
via IFTTT
Δεν υπάρχουν σχόλια:
Δημοσίευση σχολίου
Σημείωση: Μόνο ένα μέλος αυτού του ιστολογίου μπορεί να αναρτήσει σχόλιο.