Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, People's Republic of China.
Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Yanshan University, Qinhuangdao 066004, People's Republic of China.
J Neural Eng. 2022 Jun 30;19(3). doi: 10.1088/1741-2552/ac7893.
. We propose a closed-loop transcranial ultrasound stimulation (TUS) with a fuzzy controller to realize real-time and precise control of the motor response and neural activity of mice.. The mean absolute value (MAV) of the electromyogram (EMG) and peak value (PV) of the local field potential (LFP) were measured under different ultrasound intensities. A model comprising the characteristics of the MAV of the EMG, PV of the LFP, and ultrasound intensity was built using a neural network, and a fuzzy controller, proportional-integral-derivative (PID) controller, and immune feedback controller were proposed to adjust the ultrasound intensity using the feedback of the EMG MAV and the LFP PV.. In simulation, the quantitative calculation indicated that the maximum relative errors between the simulated EMG MAV and the expected values were 17% (fuzzy controller), 110% (PID control), 66% (immune feedback control); furthermore, the corresponding values of the LFP PV were 12% (fuzzy controller), 53% (PID control), 55% (immune feedback control). The average relative errors of fuzzy controller, PID control, immune feedback control were 4.97%, 13.15%, 11.52%, in the EMG closed-loop experiment and 7.76%, 11.84%, 13.56%, in the LFP closed-loop experiment.. The simulation and experimental results demonstrate that the closed-loop TUS with a fuzzy controller can realize the tracking control of the motor response and neural activity of mice.
. 我们提出了一种闭环经颅超声刺激（TUS）与模糊控制器，以实现实时和精确控制的运动反应和神经活动的小鼠。.. 在不同的超声强度下测量肌电图（EMG）和局部场电位（LFP）的峰值（PV）的均方根值（MAV）。采用神经网络建立了包括 EMG 的 MAV、LFP 的 PV 和超声强度特征的模型，并提出了模糊控制器、比例积分微分（PID）控制器和免疫反馈控制器，利用 EMG 的 MAV 和 LFP 的 PV 的反馈来调节超声强度。.. 在模拟中，定量计算表明，模拟的 EMG 的 MAV 和预期值之间的最大相对误差分别为 17%（模糊控制器）、110%（PID 控制）、66%（免疫反馈控制）；此外，LFP 的对应值为 PV 分别为 12%（模糊控制器）、53%（PID 控制）、55%（免疫反馈控制）。在 EMG 闭环实验中，模糊控制器、PID 控制和免疫反馈控制的平均相对误差分别为 4.97%、13.15%和 11.52%，在 LFP 闭环实验中，分别为 7.76%、11.84%和 13.56%。.. 模拟和实验结果表明，模糊控制器的闭环 TUS 可以实现对运动反应和神经活动的小鼠的跟踪控制。
