A Multifunctional and Flexible Implantable Electrooptic Neural Probe With Embedded Micropump and Precise Flowmeter

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Mohammad Makhdoumi Akram;Amir Aghajani;Réjean Fontaine;Frédéric Nabki;Wei Shi;Benoit Gosselin
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引用次数: 0

Abstract

In this study, we introduce a multifunctional and flexible neural probe that includes a microlight-emitting diode ( $\mu $ -LED) for fluorescence excitation and optogenetics sensing, a micropump for drug delivery, and microelectrodes for electrophysiological recording. The microprobe has dimensions of 0.7 mm (W), 0.1 mm (H), and 10 mm (L). It integrates a polydimethylsiloxane (PDMS)-based micropump that operates through an electrolysis reaction at room temperature, a precise flowmeter for drug delivery, a $\mu $ -LED for neural stimulation, and four electrodes for recording action potentials. In addition, the probe includes a flexible printed circuit board (Flex-PCB) equipped with a bio-amplifier, LED driver, RF transceiver, and a microcontroller (MCU) to control the LED, capture and digitize brain activity, and to transmit neural data to a computer nearby. The MCU includes a proportional–integral–derivative (PID) controller and an analog-to-digital converter (ADC) for recording electrophysiological signals and measuring flow rate during experiments. The PDMS-based micropump contains a potassium hydroxide (KOH) reservoir for water electrolysis, a flexible membrane, a drug reservoir, and microfluidic channels for drug delivery, each with a capacity of $20~\mu $ L. This capacity allows for a duration of 1 h of continuous flow at the highest rate of 250 nL/min. Parallel gold-plated electrodes are integrated to function as a capacitance-based flowmeter, accurately measuring flow rates from 30 to 250 nL/min with an error margin of about 5% and a resolution of 20 pF per 100 pL/min. The PID controller maintains the desired flow rate by adjusting the pulsewidth modulation (PWM) duty cycle of the micropump driver. The probe also features four gold-plated square electrodes ( $125~\mu $ m in diameter) for capturing electrophysiological signals and a blue $\mu $ -LED for optogenetic stimulation or fluorescence excitation. It was tested in vitro to evaluate its performance in realistic experimental conditions. The probe, weighing just 1.5 g, is suitable for various neuroscience applications.
一种内置微泵和精密流量计的多功能柔性植入式电光神经探头
在这项研究中,我们介绍了一个多功能和灵活的神经探针,包括一个用于荧光激发和光遗传学传感的微发光二极管($\mu $ led),一个用于药物输送的微泵,以及用于电生理记录的微电极。微探头的尺寸为0.7 mm(宽)、0.1 mm(高)和10 mm(长)。它集成了一个基于聚二甲基硅氧烷(PDMS)的微泵,该微泵可以在室温下进行电解反应,一个精确的药物输送流量计,一个用于神经刺激的led,以及四个用于记录动作电位的电极。此外,探针还包括一个柔性印刷电路板(Flex-PCB),配有生物放大器,LED驱动器,射频收发器和微控制器(MCU),用于控制LED,捕获和数字化大脑活动,并将神经数据传输到附近的计算机。单片机包括比例-积分-导数(PID)控制器和模数转换器(ADC),用于记录电生理信号和测量实验过程中的流量。基于pdms的微泵包含一个用于电解水的氢氧化钾(KOH)储层、一个柔性膜、一个药物储层和用于药物输送的微流体通道,每个容量为20~ 1 μ l,该容量允许以最高250 nL/min的速度持续1小时的连续流动。并联镀金电极集成为一个基于电容的流量计,精确测量流量从30至250 nL/min,误差范围约为5%,分辨率为20 pF / 100pl /min。PID控制器通过调节微泵驱动器的脉宽调制(PWM)占空比来维持所需的流量。探针还具有四个镀金的方形电极(直径125~ $ $ μ $ m),用于捕获电生理信号,蓝色$ $\ μ $ led用于光遗传刺激或荧光激发。对其进行了体外测试,以评估其在实际实验条件下的性能。该探针仅重1.5克,适用于各种神经科学应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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