ArticleIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society2019
Automatic Sleep Stage Classification Based on Subthalamic Local Field Potentials.
Article in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 59 citations in OpenAlex.
- Shared Spectral Parameters Between EEG and Basal Ganglia LFP Distinguish Sleep-Specific Oscillations in Parkinson's Disease.European journal of neurology · 2026Article
- The potential of utilizing Local Field Potential (LFP) in diagnosis and management of Parkinsonism's hallmark symptoms: a comprehensive review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Review
- Personalized supervised and unsupervised intracranial sleep decoding during deep brain stimulation.NPJ digital medicine · 2026Article
- Excessive daytime sleepiness in parkinsonism is associated with cortical and basal ganglia beta oscillatory activity.Communications biology · 2026Article
- Local field potential biomarkers for adaptive deep brain stimulation in Parkinson's disease: A scoping review.Surgical neurology international · 2026Review
- Toward an Automatic Classification of the Different Stages of Sleep: Exploring Patterns of Neural Activity in the Subthalamic Nucleus.The European journal of neuroscience · 2025Article
- Local Field Potential Biomarkers of Non-Motor Symptoms in Parkinson's Disease: Insights From the Subthalamic Nucleus in Deep Brain Stimulation.The European journal of neuroscience · 2025Review
- EEG-Based Detection of Mild Cognitive Impairment Using DWT-Based Features and Optimization Methods.Diagnostics (Basel, Switzerland) · 2024Article
- Chronic intracranial recordings in the globus pallidus reveal circadian rhythms in Parkinson's disease.Nature communications · 2024Article
- Generalized sleep decoding with basal ganglia signals in multiple movement disorders.NPJ digital medicine · 2024Article
- Automatic sleep-wake classification and Parkinson's disease recognition using multifeature fusion with support vector machine.CNS neuroscience & therapeutics · 2024Article
- Proceedings of the 11th Annual Deep Brain Stimulation Think Tank: pushing the forefront of neuromodulation with functional network mapping, biomarkers for adaptive DBS, bioethical dilemmas, AI-guided neuromodulation, and translational advancements.Frontiers in human neuroscience · 2024Article
- Machine learning for adaptive deep brain stimulation in Parkinson's disease: closing the loop.Journal of neurology · 2023Review
- Pathological pallidal beta activity in Parkinson's disease is sustained during sleep and associated with sleep disturbance.Nature communications · 2023Article
- Discovering Themes in Deep Brain Stimulation Research Using Explainable Artificial Intelligence.Biomedicines · 2023Review
- Novel methods for elucidating modality importance in multimodal electrophysiology classifiers.Frontiers in neuroinformatics · 2023Article
- Closed-Loop Adaptive Deep Brain Stimulation in Parkinson's Disease: Procedures to Achieve It and Future Perspectives.Journal of Parkinson's disease · 2023Review
- Hyper-parameter tuning and feature extraction for asynchronous action detection from sub-thalamic nucleus local field potentials.Frontiers in human neuroscience · 2023Article
- Parkinsonian daytime sleep-wake classification using deep brain stimulation lead recordings.Neurobiology of disease · 2023Article
- Detection of Parkinson's disease from EEG signals using discrete wavelet transform, different entropy measures, and machine learning techniques.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
15 authors at 7 institutions in 2 countries.
Funding
Abstract
Deep brain stimulation (DBS) is an established treatment for patients with Parkinson's disease (PD). Sleep disorders are common complications of PD and affected by subthalamic DBS treatment. To achieve more precise neuromodulation, chronicsleepmonitoringand closed-loop DBS toward sleep-wake cycles could potentially be utilized. Local field potential (LFP) signals that are sensed by the DBS electrode could be processed as primary feedback signals. This is the first study to systematically investigate the sleep-stage classification based on LFPs in subthalamic nucleus (STN). With our newly developed recording and transmission system, STN-LFPs were collected from 12 PD patients during wakefulness and nocturnal polysomnography sleep monitoring at one month after DBS implantation. Automatic sleep-stage classificationmodels were built with robust and interpretable machine learning methods (support vector machine and decision tree). The accuracy, sensitivity, selectivity, and specificity of the classification reached high values (above90% at most measures) at group and individual levels. Features extracted in alpha (8-13 Hz), beta (13-35 Hz), and gamma (35-50 Hz) bandswere found to contribute the most to the classification. These results will directly guide the engineering development of implantable sleepmonitoring and closed-loopDBS and pave the way for a better understanding of the STN-LFP sleep patterns.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.