A Programmable Multi-Biomarker Neural Sensor for Closed-Loop DBS

• Main Authors: Mahboubeh Parastarfeizabadi, Abbas Z. Kouzani, Jaclyn Beckinghausen, Tao Lin, Roy V. Sillitoe
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Circuits; closed-loop; multiple biomarkers; neural sensor; programmable
• Online Access: https://ieeexplore.ieee.org/document/8567905/

Most of the current closed-loop deep brain stimulation (DBS) devices use a single biomarker in their feedback loop, which may limit their performance and applications. This paper presents the design, fabrication, and validation of a programmable multi-biomarker neural sensor which can be integrated into closed-loop DBS devices. The device is capable of sensing a combination of low-frequency (7&#x2013;45 Hz), and high-frequency (200&#x2013;1000 Hz) neural signals. The signals can be amplified with a digitally programmable gain within the range of 50&#x2013;100 dB. The neural signals can be stored into a local memory for processing and validation. The sensing and storage functions are implemented via a combination of analog and digital circuits involving pre-amplifiers, filters, programmable post-amplifiers, microcontroller, digital potentiometer, and flash memory. The device is fabricated, and its performance is validated through: 1) bench tests using sinusoidal and pre-recorded neural signals; 2) <italic>in-vitro</italic> tests using pre-recorded neural signals in saline solution; and 3) <italic>in-vivo</italic> tests by recording neural signals from freely moving laboratory mice. The animals were implanted with a PlasticsOne electrode, and recording was conducted after recovery from the electrode implantation surgery. The experimental results are presented and discussed confirming the successful operation of the device. The size and weight of the device enable tetherless back-mountable use in pre-clinical trials.