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Closed-loop wearable ultrasound deep brain stimulation system based on EEG in mice.

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机构: [1]Neurosurgery Center, Department of Functional Neurosurgery, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, The Neurosurgery Institute of Guangdong Province, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, People’s Republic of China [2]Institute of Biomedical and Health engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, People’s Republic of China [3]Department of Ultrasound, Shenzhen Hospital (Futian) of Guangzhou University of Chinese Medicine, Shenzhen 518034, People’s Republic of China
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关键词: ultrasound deep brain stimulation closed-loop neurostimulation EEG deep learning epilepsy

摘要:
Epilepsy is one of the most common severe brain disorders. Ultrasound deep brain stimulation (UDBS) has shown a potential capability to suppress seizures. However, because seizures occur sporadically, it is necessary to develop a closed-loop system to suppress them. Therefore, we developed a closed-loop wearable UDBS system that delivers ultrasound to the hippocampus to suppress epileptic seizures.Mice were intraperitoneally injected with 10 mg/kg kainic acid (KA) and divided into sham and UDBS groups. Epileptic seizures were detected by applying both long short-term memory (LSTM) and bidirectional LSTM (BILSTM) networks according to EEG signal characteristics. When epileptic seizures were detected, the closed-loop UDBS system automatically activated a trigger switch to stimulate the hippocampus for 10 min and continuously record EEG signals until 20 min after ultrasonic stimulation. EEG signals were analyzed using the MATLAB software. After EEG recording, we observed the survival rate of the experimental mice for 72 hours.The BiLSTM network was found to have preferable classification performance over the LSTM network. The closed-loop UDBS system with BiLSTM could automatically detect epileptic seizures using EEG signals and effectively reduce epileptic EEG power spectral density (PSD) and seizure duration by 10.73%, eventually improving the survival rate of early epileptic mice from 67.57% in the sham group to 88.89% in the UDBS group.The closed-loop UDBS system developed in this study could be an effective clinical tool for the control of epilepsy.© 2021 IOP Publishing Ltd.

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出版当年[2020]版:
大类 | 2 区 医学
小类 | 2 区 工程:生物医学 3 区 神经科学
最新[2025]版:
大类 | 3 区 医学
小类 | 3 区 工程:生物医学 3 区 神经科学
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出版当年[2019]版:
Q1 ENGINEERING, BIOMEDICAL Q2 NEUROSCIENCES
最新[2023]版:
Q2 ENGINEERING, BIOMEDICAL Q2 NEUROSCIENCES

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第一作者机构: [1]Neurosurgery Center, Department of Functional Neurosurgery, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, The Neurosurgery Institute of Guangdong Province, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, People’s Republic of China [2]Institute of Biomedical and Health engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, People’s Republic of China
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