Adaptive Closed-loop Control of Deep Brain Stimulation for Movement Disorders

运动障碍深部脑刺激的自适应闭环控制

基本信息

  • 批准号:
    1134296
  • 负责人:
  • 金额:
    $ 33万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-08-15 至 2015-12-31
  • 项目状态:
    已结题

项目摘要

1134296TuninettiDeep Brain Stimulation (DBS) provides remarkable therapeutic benefits for otherwise drug-resistant degenerative neurological disorders, such as Parkinson's disease and Essential Tremor, for which no cure exists at present. DBS uses surgically implanted electrodes to deliver high frequency electrical stimulation to the area of the brain that controls motor functions. The stimulation blocks the abnormal nerve signals that cause disease symptoms, such as tremor, but its underlying mechanisms are unclear. Today's DBS systems operate open-loop, i.e., the physician sets DBS parameters by looking at the patient's reaction to stimulation and chooses the combination that reduced symptoms the most. Stimulation is provided continuously and its parameters remain constant over time until the next visit to the physician.This interdisciplinary research integrates the forefront of electrical engineering, mathematics, and neuroscience principles into the development of models and methods to the response of the area of the brain that controls movement to DBS. It proposes a concrete design of the next generation of DBS systems via adaptive and predictive closed-loop control in an on-off fashion, where on and off times of stimulation are determined/adapted in real-time with the patient's condition. Adaptation of the stimulation parameters to each patient's condition at any given time will: a) diminish brain over-stimulation, thus reducing the damage to healthy neurons and delaying the development of a possible intolerance to DBS, b) lower power consumption, thus prolonging DBS battery life and reducing the risks and costs related to surgeries for battery replacement, and c) reduce DBS side effects on other cognitive functions, such as speech, thus further improving patients' quality of life besides better motor functions control. This will yield improved and personalized health-care at reduced risks and costs.This research has three main thrusts: 1) Modeling the dynamics of the area in the brain that controls movement by using signals measured from the patient's brain so as to predict the effect of the DBS stimulation parameters; 2) Designing a closed-loop DBS control where brain signals are integrated with signals from the patient?s tremor affected limbs, such as measured by noninvasive Surface ElectroMyoGraphy (sEMG), so as to obtain a more complete picture of the patient?s pathological state. sEMG signal parameters are continuously monitored to predict the re-emergence of the tremor once DBS is stopped and serve as input to the controller, together with the neuronal activity; 3) Prototyping in software the second generation of DBS systems by implementing low-complexity and energy-efficient algorithms for real-time predictive closed-loop control of DBS.Although this research focuses on degenerative movement disorders, the discoveries have far reaching implications on the treatment of a number of neurological conditions, such as severe depression, epilepsy, obsessive compulsive disorder, and chronic pain, which have recently been considered for DBS-type treatments. The transformative approach of this proposed research, based on the real-time monitoring of the brain activity, enables DBS stimuli adaptation for those diseases that do not present continuous and/or visible symptoms such as tremor; such adaptation is impossible with any current open-loop technology.
深部脑刺激(DBS)对帕金森氏病和原发性震颤等抗药性退行性神经疾病提供了显著的治疗效果,目前尚无治愈方法。DBS使用手术植入的电极向控制运动功能的大脑区域提供高频电刺激。这种刺激阻止了导致震颤等疾病症状的异常神经信号,但其潜在机制尚不清楚。今天的DBS系统是开环运行的,即医生通过观察患者对刺激的反应来设置DBS参数,并选择最能减少症状的组合。刺激是持续提供的,其参数随着时间的推移保持不变,直到下一次去看医生。这项跨学科的研究将电气工程、数学和神经科学原理的前沿整合到开发模型和方法中,以应对大脑控制运动的区域对DBS的反应。它提出了下一代DBS系统的具体设计,通过开关方式的自适应和预测闭环控制,其中刺激的开关时间根据患者的情况实时确定/调整。随时调整刺激参数以适应每个患者的情况将:a)减少大脑过度刺激,从而减少对健康神经元的损害,并延缓可能对DBS不耐受的发展;b)降低功耗,从而延长DBS电池寿命,降低与手术更换电池相关的风险和成本;c)减少DBS对其他认知功能(如语言)的副作用,从而在更好地控制运动功能的同时,进一步提高患者的生活质量。这将在降低风险和成本的情况下产生更好的和个性化的医疗保健。本研究有三个主要方面:1)通过使用从患者大脑测量的信号来建模大脑中控制运动的区域的动力学,从而预测DBS刺激参数的效果;2)设计一种闭环DBS控制,其中大脑信号与患者的信号集成在一起,例如通过无创表面肌电(SEMG)测量到的S震颤患肢的信号,以便更全面地了解患者的S的病理状态。持续监测sEMG信号参数,以预测DBS停止后震颤的再次出现,并作为控制器的输入,以及神经元的活动;3)通过实施低复杂度和高能效的算法对DBS进行实时预测闭环控制,在软件中构建第二代DBS系统的原型。虽然本研究侧重于退行性运动障碍,但这些发现对许多神经系统疾病的治疗具有深远的影响,如严重的抑郁、癫痫、强迫症和慢性疼痛,这些疾病最近被考虑用于DBS类型的治疗。这项拟议研究的变革性方法基于对大脑活动的实时监测,使DBS刺激能够适应那些没有连续和/或可见症状的疾病,如震颤;这种适应在任何当前的开环技术中都是不可能的。

项目成果

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Daniela Tuninetti其他文献

A new sum-rate outer bound for interference channels with three source-destination pairs
具有三个源-目的地对的干扰信道的新总速率外界
The Two-User Causal Cognitive Interference Channel: Novel Outer Bounds and Constant Gap Result for the Symmetric Gaussian Noise Channel in Weak Interference
二用户因果认知干扰通道:弱干扰中对称高斯噪声通道的新颖外界和恒定间隙结果
The Gaussian Interference Channel with lack of codebook knowledge at one receiver: Symmetric capacity to within a gap with a PAM input
一个接收器缺乏码本知识的高斯干扰信道:在 PAM 输入间隙内的对称容量
On the capacity of interference channels with partial codebook knowledge
部分码本知识下的干扰信道容量研究
Interference channels with source cooperation in the strong cooperation regime: Symmetric capacity to within 2 bits/s/Hz with Dirty Paper Coding
强合作机制中源合作的干扰通道:使用脏纸编码将对称容量控制在 2 位/秒/赫兹以内

Daniela Tuninetti的其他文献

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{{ truncateString('Daniela Tuninetti', 18)}}的其他基金

Collaborative Research: CIF: Medium: Fundamental Limits of Cache-aided Multi-user Private Function Retrieval
协作研究:CIF:中:缓存辅助多用户私有函数检索的基本限制
  • 批准号:
    2312229
  • 财政年份:
    2023
  • 资助金额:
    $ 33万
  • 项目类别:
    Continuing Grant
CIF: Small: Fundamental Tradeoffs Between Communication Load and Storage Resources in Distributed systems
CIF:小:分布式系统中通信负载和存储资源之间的基本权衡
  • 批准号:
    1910309
  • 财政年份:
    2019
  • 资助金额:
    $ 33万
  • 项目类别:
    Standard Grant
CIF: Small: Collaborative Research: From Pliable to Content-Type Coding
CIF:小型:协作研究:从柔性编码到内容类型编码
  • 批准号:
    1527059
  • 财政年份:
    2015
  • 资助金额:
    $ 33万
  • 项目类别:
    Standard Grant
EARS: Collaborative Research: Let's share CommRad -- spectrum sharing between communications and radar systems
EARS:协作研究:让我们共享 CommRad——通信和雷达系统之间的频谱共享
  • 批准号:
    1443967
  • 财政年份:
    2015
  • 资助金额:
    $ 33万
  • 项目类别:
    Standard Grant
CIF: Small: Modules as a Framework for Interference Alignment in Networks
CIF:小型:模块作为网络中干扰对齐的框架
  • 批准号:
    1218635
  • 财政年份:
    2012
  • 资助金额:
    $ 33万
  • 项目类别:
    Standard Grant
CAREER: Etiquette for Collaborative Communication and Networking
职业:协作沟通和网络礼仪
  • 批准号:
    0643954
  • 财政年份:
    2007
  • 资助金额:
    $ 33万
  • 项目类别:
    Continuing Grant

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An Adaptive Closed-Loop Robotic Exoskeleton for Upper Extremity Motor Rehabilitation
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