Browsing by Author "Jeng, Chi"

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A Fully Integrated 8-Channel Closed-Loop Neural-Prosthetic CMOS SoC for Real-Time Epileptic Seizure Control
(2014-01-01)
Chen, Wei-Ming
;
Chiueh, Herming
;
Chen, Tsan-Jieh
;
Ho, Chia-Lun
;
Jeng, Chi
An 8-channel closed-loop neural-prosthetic SoC is presented for real-time intracranial EEG (iEEG) acquisition, seizure detection, and electrical stimulation in order to suppress epileptic seizures. The SoC is composed of eight energy-efficient analog front-end amplifiers (AFEAs), a 10-b delta-modulated SAR ADC (DMSAR ADC), a configurable bio-signal processor (BSP), and an adaptive high-voltage-tolerant stimulator. A wire-less power-and-data transmission system is also embedded. By leveraging T-connected pseudo-resistors, the high-pass (low-pass) cutoff frequency of the AFEAs can be adjusted from 0.1 to 10 Hz (0.8 to 7 kHz). The noise-efficiency factor (NEF) of the AFEA is 1.77, and the DMSAR ADC achieves an ENOB of 9.57 bits. The BSP extracts the epileptic features from time-domain entropy and frequency spectrum for seizure detection. A constant 30-mu A stimulus current is delivered by closed-loop control. The acquired signals are transmitted with on-off keying (OOK) modulation at 4 Mbps over the MedRadio band for monitoring. A multi-LDO topology is adopted to mitigate the interferences across different power domains. The proposed SoC is fabricated in 0.18-mu m CMOS and occupies 13.47 mm(2). Verified on Long Evans rats, the proposed SoC dissipates 2.8 mW and achieves high detection accuracy 92% within 0.8 s.
A Fully Integrated 8-Channel Closed-Loop Neural-Prosthetic SoC for Real-Time Epileptic Seizure Control
(2013-01-01)
Chen, Wei-Ming
;
Chiueh, Herming
;
Chen, Tsan-Jieh
;
Ho, Chia-Lun
;
Jeng, Chi
A Hardware Implementation of Real-Time Epileptic Seizure Detector on FPGA
(2011)
Chen, Tsan-Jieh
;
Jeng, Chi
;
Chang, Shun-Ting
;
Chiueh, Herming
;
Liang, Sheng-Fu
a considerable portion of epilepsy cannot be well treated by today\'s available therapies. Brain stimulation with closed-loop seizure control was recently proposed. In our previous work, high accuracy of seizure controller (92-99% during wake-sleep states) using a microcontroller has been proposed and implemented to verify functionality of seizure detection and suppression on a freely moving rat. In this paper, the soft intellectual property (IP) of epileptic seizure detector in the implantable system on chip (SoC) for epileptic seizure control is proposed to achieve continuous real-time processing and low power consumption. All the essential macros for epileptic seizure detector are implemented and integrated in field programmable gate array (FPGA) to verify functionality and capability. The evaluation results of the prototype supported possible application of a portable and continuous real-time seizure control.
The Implementation of a Low-Power Biomedical Signal Processor for Real-Time Epileptic Seizure Detection on Absence Animal Models
(2011-12-01)
Chen, Tsan-Jieh
;
Chiueh, Herming
;
Liang, Sheng-Fu
;
Chang, Shun-Ting
;
Jeng, Chi
Epilepsy is one of the most common neurological disorders, with a worldwide prevalence of approximately 1%. A considerable portion of epilepsy patients cannot be treated sufficiently by today's available therapies. Implantable closed-loop neurostimulation is an innovative and effective method for seizure control. A real-time seizure detector is the kernel of a closed-loop seizure controller. In this paper, a low-power biomedical signal processor based on reduced instruction set computer (RISC) architecture for real-time seizure detection is implemented to achieve low-power consumption and perform continuous and real-time processing. The low-power processor is implemented in a 0.18 mu m complementary-metal-oxide semiconductor technology to verify functionality and capability. The measurement results show the implemented processor can reduce over 90% power consumption compared with our previous prototype, which was implemented on an enhanced 8051 microprocessor. This seizure detector was applied to the continuous EEG signals of four Long-Evans rats with spontaneous absence seizures. It also processed 24 h long-term and uninterrupted EEG sequence. The developed seizure detector can be applied for online seizure monitoring and integrated with an electrical stimulator to perform a closed-loop seizure controller in the future.
The Implementation of a Low-Power Biomedical Signal Processor for Real-Time Epileptic Seizure Detection on Absence Animal Models
(2011-12-01)
Chen, Tsan-Jieh
;
Chiueh, Herming
;
Liang, Sheng-Fu
;
Chang, Shun-Ting
;
Jeng, Chi
Epilepsy is one of the most common neurological disorders, with a worldwide prevalence of approximately 1%. A considerable portion of epilepsy patients cannot be treated sufficiently by today\'s available therapies. Implantable closed-loop neurostimulation is an innovative and effective method for seizure control. A real-time seizure detector is the kernel of a closed-loop seizure controller. In this paper, a low-power biomedical signal processor based on reduced instruction set computer (RISC) architecture for real-time seizure detection is implemented to achieve low-power consumption and perform continuous and real-time processing. The low-power processor is implemented in a 0.18 mu m complementary-metal-oxide semiconductor technology to verify functionality and capability. The measurement results show the implemented processor can reduce over 90% power consumption compared with our previous prototype, which was implemented on an enhanced 8051 microprocessor. This seizure detector was applied to the continuous EEG signals of four Long-Evans rats with spontaneous absence seizures. It also processed 24 h long-term and uninterrupted EEG sequence. The developed seizure detector can be applied for online seizure monitoring and integrated with an electrical stimulator to perform a closed-loop seizure controller in the future.