Denison Timothy, Litt Brian
Medtronic Neuromodulation, Minneapolis, MN, USA.
Neuromodulation. 2014 Jun;17 Suppl 1:48-57. doi: 10.1111/ner.12170.
To provide a general control system framework for neuromodulation, its practical challenges, and historical underpinnings in cardiac rhythm devices, and to illustrate the potential of closed-loop techniques in neuromodulation with a case study using an adaptive neural stimulation system that integrates sensing, actuation, and state estimation for the treatment of chronic pain through spinal cord stimulation.
The current state of neuromodulation can be viewed in a classical dynamic control framework: the nervous system is the classical "plant," the neural stimulator is the actuator, tools to collect clinical data are the sensors, and the physician's judgment is the state estimator and mechanism for closing the therapy feedback loop. This framework highlights the opportunities available to advance neuromodulation.
Technology has the capability to address key factors limiting the performance of current systems: observability, the ability of the device to monitor the state of the nervous system from sensor-based measurements in real time; and controllability, the ability of the device to drive the nervous system to a desired physiological state using suitable algorithms and actuation.
Technological advances in neuromodulation using such a control framework have the potential to improve neurologic therapies. Future opportunities for extending the role of these systems are briefly discussed.
提供一个用于神经调节的通用控制系统框架、其实际挑战以及心脏节律装置中的历史基础,并通过一个使用自适应神经刺激系统的案例研究来说明闭环技术在神经调节中的潜力,该系统集成了传感、驱动和状态估计,用于通过脊髓刺激治疗慢性疼痛。
神经调节的当前状态可以在一个经典的动态控制框架中看待:神经系统是经典的“被控对象”,神经刺激器是执行器,收集临床数据的工具是传感器,而医生的判断是状态估计器和关闭治疗反馈回路的机制。这个框架突出了推进神经调节的可用机会。
技术有能力解决限制当前系统性能的关键因素:可观测性,即设备从基于传感器的测量中实时监测神经系统状态的能力;以及可控性,即设备使用合适的算法和驱动将神经系统驱动到期望生理状态的能力。
使用这种控制框架的神经调节技术进步有潜力改善神经治疗。简要讨论了扩展这些系统作用的未来机会。