A Programmable EEG Monitoring SoC with Optical and Electrical Stimulation for Epilepsy Control

Abstract

In this paper, a cross-domain integration system composed of a gene transfer technique with a pre-clinical trial, an on-chip circuit design, an off-chip hardware with peripheral unit integration, and a custom software is presented. Opsin protein-gene transfer is successfully conducted to demonstrate that gene transfer treatment with optical stimulation has several benefits compared with electrical treatment. The proposed wireless programmable stimulating system on chip (WPSSoC) is composed of two sensing channels combined with a decimation filter to acquire intracranial electroencephalography (iEEG), an epilepsy detection unit (EDU), a stimulator with a waveform controller, and an ultra-low-power embedded transceiver. The equivalent sample rate of sensed data is 375 samples/s with 16-bit output data. The performance of intermodulation distortion with a third order (IMD 3) is approximately 68 dB. The EDU extracts approximate entropy (ApEn) and spectrum bins for the classifier. The stimulator with controller features on the waveform-adjustable function to provide 0-510 µA of electrical stimulation and 0-50 mW of optical stimulation. The proposed transceiver is implemented with a 2.45 GHz on-off keying (OOK) carrier frequency. Transmitter and receiver front-ends perform at 50.6 and 12.7 pJ/bit of energy per bit, respectively. Power consumption and area of WPSSoC are about 1 mW and 13.67 mm 2 in a 0.18 µm process, respectively. Circuits of each part are integrated in a 4.3 cm × 2 cm printed circuit board. The shrunk device is verified with Thy1-ChR2-YFP gene transfer in C57BL/6 mice by using a custom software which is used to provide commands and monitor iEEG. INDEX TERMS ChR2 gene transferring, electrical stimulation, epilepsy, implantable device, in vivo testing, open-/closed-loop control, optical stimulation, system-on-chip, wireless monitoring and control.

Intelligent Wireless EEG Measurement System With Electrical and Optogenetic Stimulation for Epileptic Seizure Detection and Suppression

“…The features include specific frequency tones for epileptic seizure, approximate entropy (ApEn), and the amplitude of signals. According to previous studies [18], [25], the frequency tones around 5, 10, and 15 Hz are larger in the epileptic seizure waveforms than the normal iEEG signals. Based on this observation, the sampling frequency in the SAR ADC is selected to be 1 kHz.…”

“…Furthermore, the artifacts on the measured electroencephalography (EEG) signals induced by optical stimulation are less than those caused by electrical stimulation. Both advantages of optical stimulation over electrical stimulation have been proven by our previous work [18]. Nevertheless, potential drawbacks of optical stimulation are the requirement of transgenic cells in the brain, larger power consumption than electrical stimulation, and the issue of heat deposited in tissue [19].…”

“…The amplitude, frequency, duration, and duty cycle of the stimulation are all adjustable with the BLE module control on the stimulator. Boost converter LT1615ES5-1#TRMPBF is used to convert the supply from the battery into a 20 V supply for the current DAC and switches, which can avoid voltage saturation for 1 ms stimulation under 1 mA current with the impedance model derived from [18]. AD5410 is selected for the DAC structure because it can offer programmable current source output from 0 mA to 20 mA with a 12-bit resolution, which covers the current intensity in previous studies [8], [13]- [15].…”

“…The processed data also serve as the input of the AI algorithm for epileptic seizure detection. Figure 8 illustrates the operation of the AI algorithm, which is improved from our previous work [18] with a detection window to enhance its accuracy. The AI algorithm is described as follows.…”

“…To fulfill the challenging requirements, a system including the above functions on a 27.3 mm × 23.6 mm double-layer PCB is presented in this paper. Compared with the previous work [18], this paper overcomes the drawbacks in [18] including low-output stimulated voltage less than 3.3 V, higher power consumption because of using sigma-delta analog-to-digital converter (ADC), low epileptic seizure identification without detection window in artificial intelligence (AI) algorithm, and low gain with 27 dB in the analog front-end that is insufficient for EEG signal acquisition. The proposed system in Figure 1 can provide 20 V output stimulated voltage in an animal study, a 12-bit successive approximation register (SAR) ADC is used for the benefits of low power and multichannel EEG signal acquisition, a detection window after classification is employed to enhance the accuracy of epileptic seizure detection, and an amplifier with gain of 1000 is used to improve the acquisition ability of low EEG signal.…”