Today, we would like to present our work which concerns the design of an implantable, programmable, and wireless-based smart VP-SHOT system using mixed-signal CMOS circuit approach. This is a collaborative work between the University of Santo Tomas, Department of Electronics Engineering, Davao Doctors' Hospital, Department of Neurosurgery, and the Southern Philippines Integrated Neurosurgical Training Program. Hydrocephalus is a condition where there is an accumulation of pressure in the ventricles caused by an extra buildup of cerebrospinal fluid. The usual approach to alleviate this problem is the use of a VP-SHOT. The VP-SHOT tends to drain this extra CSF, thereby relieving the brain of pressure. However, there are some problems with the existing VP-SHOT. The VP-SHOT has limited control options. It's usually done magnetically by presetting these thresholds. Therefore, it also would be manually readjusted based on the pain perception of the patient. It caters some difficulty in diagnosing failures such as clogging or SHOT malfunction. And more so, if you want to have measurements of the ICP, that will not be possible in real-time because it will entail surgery using lumbar puncture. So this does not cater for at-home real-time scenarios. Therefore, for several decades, there is the pursuit of a SMART-SHUNT. The SMART-SHUNT would likely be a device that is capable of measuring conditions such as ICP, or the cerebrospinal fluid drainage rate, and adjusting this rate with corresponding sensors, valves, electronics, and telemetry. So before we try to begin to design the core circuits, we need to understand the nature of the intracranial pressure. Generally, the ICP will have low amplitude corresponding to a micropressure range, as well as low frequency. However, if you are to design circuits in this domain with very low input signal and low frequency, you'll be corrupted by noise. So that would be one design challenge which will be addressed by our work. So our work is based on the CMOS technology, which stands for Complementary Metal Oxide Semiconductor. It's understood to be the cell or the driving force of microelectronics that are used to realize amplifiers, filters in the analog domain, as well as switches in the digital domain. So mixed signal generally means the combination of both analog and digital sub-blocks. The current state of the art implies that there are commercial VP-SHUNTS that have adjustable thresholds. By using magneto-mechanical approach, several works have done macro-scale modeling of real-time pressure and flow rate measurements, emulating that of the physiological range as well as shunting. With technological advancement, we're now seeing micrometer-sized sensors developed using the system called MEMS, which stands for Microelectromechanical Systems, offering both low-power dissipation and micro-scale analog sensing. MEMS technology, however, can be readily combined with CMOS technology to form a so-called system-on-chip with very good form factor and implantability. Our proposed SMART-SHUNTS system will consist of the core electronics for sensing and control, as well as saw devices for compensating under- and over-drain scenarios of a passive fault. We propose to utilize differential pressure sensing using two micropressure sensors, ICP1 and ICP2. By doing so, we can have a measure of the CSF flow rate following Bernoulli's equation. Shunt plugging may be manifested by the negative back pressure due to buildup of CSF at the distal end. The corresponding saw devices are to be driven depending on the accumulated pressure in reference to the decoded pre-set pressure threshold. Meanwhile, the core electronics are to be interfaced to a wireless transceiver. This is the idea of saw devices. Generally, you have interdigitated electrodes on a piezoelectric substrate, for which you apply a high-frequency signal causing the surface to vibrate. When it vibrates, then it tends to push fluids or droplets from one point to the other. Our proposed VP-SHUNT electronics will consist of a low-noise and high-performance piezo-resistive sensor-front-line interface coupled to an integrated circuit for accumulating the differential ICP pressure. It also consists of a digitally programmable pressure-threshold circuit for setting up the acceptable pressure ranges for diagnosing shunt, under- and over-drain scenarios. We propose also the use of surface-acoustic wave devices to provide forward and backward flows of CSF to alleviate shunt valve under- and over-drain. For real-time ICP measurements, we have developed a high-resolution 12-bit analog-to-digital converter. MEMS pressure sensors generally are piezo-resistive in nature, where a deflection or deformation connotes a change in resistance. Following Ohm's law, if we supply a constant current to a change in resistance, we can generally extract a change in voltage in proportion to the applied pressure. Now, we need to have a very good sensor front-end, and we need to have very low-noise performance. To do that, we propose the use of chopper-stabilized technique for the IA for good noise rejection and high input impedance with low-noise contribution. This will consist of upscaling the very low-frequency ICP data to a high frequency, and then downscaling and corresponding filtering. We utilize a pressure integrator so that we tend to accumulate the pressure that is also for detecting clogged valve, as well as for filtering transient or noisy high-frequency variations in the pressure. Now, this is our saw-based shunt driver decision logic. It just consists of a comparator with hysteresis, with upper and lower thresholds defining a margin. When the output of the pressure integrator is within the range set up by the upper threshold, VUT, and lower threshold, then the shunt is perfectly fine, understood to be perfectly fine. Otherwise, if it is greater than the upper threshold, it's understood to be under-drained, and vice versa. For the pressure-threshold setting, we utilize a switch-to-resistor approach that are digitally coded. And for now, we developed an 8-bit resolution pressure-threshold setting. For the analog-to-digital converter, we chose the SAR topology, which stands for successive approximation register. We intend them with an RC hybrid digital-to-analog converter for purposes of low power, good form factor, and low noise performance. To drive the saw devices, we built this voltage-controlled oscillator with the corresponding multiplexer, whose frequency is coupled to the corresponding saw device, depending on the under-drain or over-drain scenario. Simulation results reveal that we have a very good sensor front-end, having a noise efficiency factor of around 2.28, which is comparable to noise efficiency factors of implantable neural signal amplifiers, as well as providing a high gain, which is necessary for micropressure measurements. Now for the other components of the mixed-signal circuit, it can be seen that the programmable threshold has achieved a high linearity for setting up digitally the limits of acceptable normal physiological ICPs, and for activating the corresponding saw device to induce either forward or backward flow for under-drain or over-drain scenarios, respectively. Meanwhile, the successive approximation ADC shows convergence of digital data towards the target analog value at a resolution of 12 bits, equivalent to our micropressure data. Meanwhile, the integrator is able to show charge accumulation analogous to a capacitor in the charging phase. Its corresponding time constant may be adjusted by using the appropriate resistor-capacitor pairs. This constant may also be digitally set using a switch-resistor string to accommodate patient-dependent flow rates or real-time ICP. So, in conclusion, what is the contribution of our work is that we're able to do a preliminary design using pre-layout simulation of a viable mixed-signal sensing and actuator interface for implementing a smart and implantable VP-SHUT. We're still going to talk forward for the next steps like developing a wireless interface, as well as the corresponding application-specific digital blocks for notification, and also we'll be collaborating with a partner to develop the saw devices on a piezoelectric substrate, then we send the chip for fabrication. Thank you so much for your attention and a warm invite to render this talk. Hope that we can foster collaborations in the future so that we may develop our own brain chip.

SMART-SHUNT system

hydrocephalus

VP-SHOT

CMOS technology

micropressure sensors