INTRODUCTION:

In the central nervous system, cranial nerve damage causes several neurological disorders such as stroke, depression, epilepsy, Parkinson's disease replaces the impaired function, the stray nerves of the peripheral nervous system. It is relatively easy to apply an electronic contraction technology for nerve regulation by artificially stimulating the peripheral nervous system that connects important organs such as brown adipose tissue, liver, and pancreas, and the brain. The charge balance system must be robust against fluctuations of circuit and load impedance and suitable for miniaturization. In this study, a two-phase stimulus connecting the current sink and source to the tissue for a period of time was described. The anode, cathode, pulse width, separation, amplitude, repetition period, and the same current pulse parameters can vary depending on the particular application. Due to process and load fluctuations, a discrepancy of about 2-5% between current amplitudes of the cathode phase and the anode phase can occur, resulting in a tissue charge imbalance. It must be biologically safe and maintain a state of charge balance, which means that charge accumulation is not allowed for a period of time[1].

Another effective method is to periodically short-circuit and discharge electrodes for a sufficient period of time. Conventional methods for charge balancing can be classified into open-loop and closed-loop filling methods. The calibration technique is divided into a dynamic copy method and a charge measurement method. Load fluctuations and leaks contribute to the imbalance of residual charge in such a method. Charge balance is achieved by inserting a large number of compensatory small amplitude spikes after each two-phase pulse. Due to reduced amplitude of the correction spike, achievable calibration and stimulation rates have their limits. A digital controller is required to calculate the offset. This is performed in an analog domain without requiring digital processing. It can be easily integrated into a chip implementation of a stand-alone stimulus driver circuit. Implant internal devices from common electronic drugs consist of subsystems such as power, data, clocks, recovery, stimulus data generators, stimuli, and remote measuring devices. Generally, consists of pulse profile data and 5-9 bits current amplitude data. The current amplitude required for stimulation in all cycles is provided by the current mode DAC based on amplitude data. The input of the DAC is the quantized value of the externally acquired stimulus signal. The mechanism of the PI controller maintains the analog value. The DAC current is mirrored for cathode and anode phases by continuously switching the current sink and source with a typical CMOS stimulus driver.

Concept of Electroceutical in Medicine for Nerve Cell Treatment

Figure 1 shows the algorithm used in this study based on biological properties of neurons.

The refractory curve is shown in Figures 1 a) and 1 b). It means the recovery time when excitatory neurons return to the rest state and prepare for the next stimulus[2].

When a neuron is in the TRefractory state, it should not be excited by any stimulus. Applying a stimulating current to neurons in a TRefractory state will completely waste E-STIM. E-S equipment with closed loops can find AMP, PW, and optimal FREQ along the SD curve.

Since the optimum stimulus can be set, the device can save a lot of E-STIM in the saving expansion. AP can be distinguished from another neuron using two amplitude thresholds and a time frame as shown in Figure 1c). The signal current is compared to the depolarizing critical current TH1 produced by the 8-bit current DAC. The depolarization threshold is typically set to be 5σ of the signal. It is programmed by the two-wire interface (TWI) displayed on the data and clock as shown in Figure 1 b). The comparator is disabled during the period of Φ1[3]. The reference is when the current is converted to the repolarization threshold TH2. The action potential is detected when the signal passes through TH2 within the Φ2 period.

The intensity-duration curve is shown in Figures 2 a) and 2 b).

The charge amount Qth required by the threshold value for inducing nerve excitement depends on both the intensity (I) and the duration (t). I value also depends on t. They are inversely proportional.

When both A and B are constant, A = IRh and its biological meaning are minimum intensities that can induce excitement of an infinite duration of neurons. It is the minimum duration when the intensity is 2 * IRh at B = TCh. It is the point that induces excitement of the minimum ESTIM nerve.

From Fig a,

Therefore, the stronger the stimulus, the more fibers reach the threshold. Fiber-effective threshold depends not only on the intensity of the stimulus, but also on the duration of the stimulus. Depolarization of excitatory membranes requires a flow of charge throughout the membranes [4].

Due to dominant capacitance of the membrane, the parameter associated with effective membrane depolarization is the total amount of charge passed across the membrane. The charge (Q) passed for a short-term stimulus that produces a constant transmembrane current is proportional to the product of the current I and the time T.

Q = I x T-(16)

Therefore, if the amount of charge required to activate the fiber is Q t and the duration of stimulation is D, the current I t required to achieve activation is as follows.

t = Q t / D-(17)

During a long-term stimulation, the equation cannot predict charge transfer across the nerve membrane.

If the stimulus is too small, the membrane potential has not reached the threshold. It is a common sense that the fire resistance period is the characteristic recovery time, which is the period associated with the movement of the image point on the left branch. Physiology, indefinite long term or cell is a term that repeats certain actions or is impossible. Most commonly refers to muscle cells or nerve cells that can be electrically excited. The absolute indefinite period corresponds to depolarization and repolarization while the opponent's indefinite period corresponds to hyperpolarization.

After the action potential is initiated by using an electrochemical, the fire resistance period is defined in two ways. The absolute fire resistance period that coincides with almost the entire period of the action potential and opens to prevent depolarization of nerve cells[5]. Due to invalidation of the Na + channel, a channel remains disabled until the membrane is gobbled. The next channel closes and becomes disabled, regaining its ability to open in response to a stimulus. For the mating fire resistance period, the absolute value is applied immediately. Similarly, by repolarizing the voltage gate potassium channel to prevent it, the action potential is terminated and the open membrane potassium conductivity increases sharply. K+ ions that move extracellularly can create a membrane potential close to the equilibrium potential of potassium, which causes a short membrane potential, that is, the membrane potential is temporarily more audible than the normal resting potential. The membrane is made up of the following sounds. When the potential reaches the activation threshold (-55 mV), depolarization is actively driven by neurons to exceed the activated membrane equilibrium potential (+30 mV). The second stage is repolarization, where the voltage gate sodium ion channel during repolarization is disabled by the current depolarized membrane to activate the voltage gate potassium channel, disabling the sodium ion channel and the potassium ion channel. Opening serves to repolarize the membrane potential of all cells to resting membrane potential.

Proposal of Electroceutical for Nerve Cell Treatment:

3-1. Model:

The required nonlinear oscillating motion can be achieved using a post-spike reset mechanism separate from the 2-state variable differential equations as described by Izhikevich[6]. The goal is to use the simplest possible circuit in an analog VLSI implementation that can reproduce the functioning of a nonlinear equation coupling system. The positive feedback current is generated by S1 and mirrored by S2 to S3. It depends approximately secondarily to the membrane potential. The magnitude of the current provided by S7 is determined by the membrane potential in a manner similar to that of a membrane circuit. The transistor (S6) provides a non-linear leakage current. The transistor and capacitance are adjusted so that the potential C2 changes slower than C1. Following the membrane potential spike, the comparator generates a short pulse on transistor S8 to allow the additional charge controlled by the voltage at node W5 to be transferred to C2. This circuit is designed and manufactured with 0.35 μm CMOS technology. Since transistors in this circuit operate with most strong inversions, the firing pattern is about 104 faster than biological real-time on an "accelerated" time scale. The power consumption of the circuit is less than 10 pJ / spike.

A similar circuit was presented by Wijekoon and Dudek. However, it operates with a weak inversion to provide spike timing on the biological time scale. Figure 3 shows a blueprint of the Izhikevich neuron circuit, which is mounted on to a 0.35μM CMOS VLSI.

3-2. Configuration:

Figure 4 shows the design of the electronic drug method constructed in this study. Early implementations, especially with electronic drugs, require consideration of implantable stimulators and several design factors. Main stimulation parameters are amplitude, pulse width, and stimulation rate. The magnitude of the stimulation current must exceed the threshold to generate action potentials. The stimulus can provide an output current in the range of 32 μA to 1 mA, which is sufficient to cover a variety of neurostimulation applications. Figure 4 was designed with the balance between current stimulation and charge in mind[7]. The design stimulation pulse width was set to be 100μS and the velocity was set to be 400μS. After the stimulation step, the active filling and dispersion step occurred within a 50μS timing window. In addition to these design parameters, power and small area are required considering multi-channel implementation. In this method, an electrode model with a tissue resistance of RE = 100mΩ, CE = 200nF, and 100kΩ is assumed. At least 10 V voltage compliance is required to transfer 1 mA of current to a 10kΩ load. These proposed stimuli are common for 1.8 V and 3.3 V standard CMOS transistors.

3-3. Electrode-electrolyte interface model:

Proprietary calibration techniques are required to match amplitudes of the cathode and anode current pulses. For pulse amplitudes of ~ 3 mA, the amplitude difference between both pulses can be reduced to be less than 2 μA after calibration. can. The function of stimulation is to generate stimulation current pulses[8]. Detection of neural signals can be performed between two consecutive stimulation pulses. Nerve signal detection must be performed at the same nominal electrode potential as the potential before the simulation pulse is applied. In applications, the frequency is generally less than 100 Hz. The pulse duration is set to be in the range of 20μS to several hundred μS. Amplitudes of the cathode and anode current pulses have a range from a few hundred μA to a few mA depending on the application.

3-4. Charge Balancing:

Nerve stimulation is achieved by transferring charges to nerve tissue via conduction electrodes. It is performed by applying a constant stimulation current for a certain period of time. Tissue destruction and electrolysis are induced through electrode dissolution and pH changes. A simple way to prevent the accumulation of these charges is to employ a current source and a two-phase stimulation pulse. The DC current is kept below Idc <10 nA to prevent charges from accumulating on the resulting electrodes and generating a strong Faraday current. On the other hand, the stimulation current is known to be 1 mA. Since it is difficult in an actual integrated circuit, other charge balancing techniques are provided. First, the block capacitor needs to integrate the total stimulation current so that it is much larger than the interface and capacitor CE. It is mounted externally.

3-5. Current Driver:

Feedback Controlled Charge Balance Technology has been proposed to actively adjust excessive electrode potentials to the safety windows [9]. This voltage is not directly accessible as only the mating electrode or stimulation electrode can be electrically connected. VCE ≈ ΔVE can be measured without a current. Safety in the case of VE > VCM ± ΔVE, the excess electrode voltage is offset by applying a small charge packet of possible polarity using a stimulus current source after the measurement. The inspection and charging operation are repeated until the electrode potential is within the safety window. As a result, the interaction occurs through the counter electrode capacitor. The current is a general stimulus current. The time is very short, demonstrating the importance of considering stability. The linear mode driver can be replaced with a switching network to minimize the power loss of the electrical stimulator.

3-5. DAC:

In the two-phase stimulation design, the cathode current pulse and the anode current pulse are created by the NMOS current DAC (nDAC) and the MIMO current DAC (pDAC), respectively. In general, the average DC leakage current should be less than 100-300nA to prevent tissue damage and electrode electrolysis[10]. A low DC leak capacitor is preferably added between the stimulus and the electrode for safety reasons. However, it can generate an average mismatch current that can charge the capacitor. Therefore, the stimulus output voltage can drift close to the power rail. The closed loop optimizes AMP, PW, and FREQ to minimum values for guiding nerves. The IREF generator, which includes BGR, OPAMP, and R-2R calibration networks to classify the power budget, consumes the most 9.83uA in the low voltage domain VDD. The CE driver consumes 7.22μA. The WE driver, the stimulation channel including the charge balance window, and the digital controller each consumes 6.3μA[11]. In the case of high voltage domain VDDH, all bias current including VREF generator, IREF generator, and HV amplifier is consumed by the CE driver, totaling 10.6μA. AMP, PW, FREQ, and VDDH are 2 mA, 2 mS, 500 Hz, and 9V, respectively, when the proposed method is not applied. However, when applied to closed-loop systems, these parameters can be optimized to be 0.5 mA, 400 us, 200 Hz, and 3 V, respectively[12]. In this method, the bandgap reference (BGR) creates a stable VREF at 600 mV. OPAMP uses the R-2R ladder calibration bank and VREF of 31.25uA to generate a stable IREF. ISTIM_MAX is 8 mA because IREF is copied by IDAC in an 8-bit code. LSB (1/16) * 4-bit code for calibration of IREF is added to IDAC[13]. The working electrode (WE) driver applies a stimulating current to the target neuron. It is supplied by a high voltage source, a compliance voltage, and a VDDH. Cascade current regulation is chosen over other DAC architectures to ensure linearity and simplify the control circuitry[14]. The designed DAC can generate a current of 4 to 128 μA in 4 μA steps to minimize current consumption. This current is amplified eight times at the output driver stage.

3-6. Current mirror OTA’s Driver:

Mismatches in the output driver circuit can result in changes in each phase current amplitude during stimulation[15]. Discrepancies are not important for a single stimulation cycle. However, residual charge can accumulate after each stimulation cycle. The voltage difference should not exceed 100 mV as it can damage the tissue. The two electrodes are short-circuited directly with a low voltage comparator for comparison[16]. For one clock cycle, the comparator compares the voltage difference between the two electrodes. With charge balance, the comparator consists of multiple low voltage operational amplifiers with a total current consumption of less than 2μA. The spectral density of the input reference thermal noise of this OTA is given in (8.6), where gm1 is the transconductance of input devices M1, M5, M6, and M7, gm3 is the transconductance of nMOS current mirror elements M21-M3, and gm7 is the transconductance of pMOS current mirror elements M1, M8, M11, and M12. OTA input conversion noise can be minimized by guaranteeing gm1 >> gm3 and gm7. This is done by adjusting the size of the transistor so that M4, M6, M5, and M7 operate in inversion with a weak element transconductance ratio. The drain current (gm / ID) is up to M21 to M11 and the gm / ID is greatly reduced[17]. A dimensionless figure of merit that clearly captures the essence of the trade-off is the proposed noise efficiency factor (NEF). Total amplifier supply current UT is thermal voltage kT / q, BW is amplifier bandwidth Vni, and rms is amplifier input reference rms voltage noise. An amplifier with noise generated only by the thermal noise of one ideal bipolar transistor has NEF = 1. For all physical circuits, NEF > 1. With the latest IC amplifiers, the supply voltage changes by about 5 times, while the supply current can change by several tens of times (for example, 1 nA to 1 A). Therefore, NEF is closely related to power consumption [18].

Implementation Result:

In Figure 10, the parameter optimizer first looks for the optimum amplitude. The amplitude was set to minimum and maximum values to find the optimum amplitude. Experimentally setting of PW to 2.50mS instead of infinity resulted in an error of less than the ideal IRh of 10%. However, if there was no response from the spike detector, the optimizer gradually increased the amplitude to 2.50mS. The reason for linearly adjusting the optimizer amplitude was to prevent neurons from jumping in the TRefractory state. The next step was to find the best PW. Finding the optimal amplitude was almost the same. However, the starting AMP was 2 * IRh. At this stage, the PW was set to a minimum of 2.50mS and the PW increased linearly so as not to enter the TRefractory state. At these traction stages, the optimizer could find a single pulse (AMP * PW) with a minimum energy consumption stimulus. The final step was to find the optimal pulse-to-pulse duration[21]. The optimizer started by setting AMP and PW to their optimum values and FREQ to the maximum value with the shortest inter-pulse time[19]. While the ES device applied a stimulating current to the target neuron, the spike detector could monitor the neural response and calculate whether each pulse could induce it[20]. If the nerve stimulation reoccurred, it indicated the end of the TRefractory state. The pulse during the period was ignored[22]. The optimizer could determine the optimal FREQ to 1 / TRefractory because the three intermediate stimulation pulses did not induce it.

In the past, active charge balancers have not been extensively studied in active charge balancing.

The voltage is not directly accessible as only the mating electrode or the stimulation electrode can be electrically connected[23]. As long as the current flows, the voltage drop of the "resistor" with a large tissue impedance is mainly seen, not the voltage of the interface capacitance. VCE ≈ ΔVE can be measured without current[24]. The exact value is not important only if the overvoltage exceeds the safety voltage window around the common mode potential. Safety in case of VE > VCM ± ΔVE, small charge of polarity is possible using stimulus current source after measurement. To offset excess electrode voltage, packets can be applied. Current spikes can be made. However, other implementations are possible[25]. As a result, the feedback control charge balance technology is proposed to actively adjust the excessive electrode potential to the safety window[26]. This provides system workers with precise control over safe operating conditions. For feedback systems, stability must be considered. The charge balancer is based on comparing the voltage of the electrode VE with the mating electrode VCM. Therefore, even if it is added to the electrode capacitor voltage VCE, the voltage on the large-scale electrode VCCE can be seen.

FIG. 12 shows a biofeedback stimulation chip micrograph. The proposed IC was manufactured with a 180 nm HV BCD process with a chip area of 2 mm x 2.3 mm. The performance of the stimulus is summarized in the table. Bias from VDD and VDDH domains consumed 23.4 uA and 10.6 uA, respectively[27]. Stimulation parameters can be programmed in the range of 31.25 uA-8mA, 10 us-2.55 ms and DC-1kHz. The proposed IC was manufactured with a 180 nm HV BCD process with a chip area of 1.5 mm x 1.5 mm. The performance of the stimulus is summarized in the table. Complex waveforms in the 31.25 uA-8 mA range can be programmed with 10 us-2.55 ms, DC-1kHz, 255 pulses / train / cluster, and a maximum duration of 24 hours. Izhikevich can mimic four types of nerve spikes based on the mathematical SNC model[28].

The first two cases of Figures 13 a) and 13 b) show an appropriate balance. The controller time constant (4.7 mS) was larger than the stimulation cycle (2 mS). In Figure 13c), the controller has a lower gain and a smaller constant than the stimulation period[29]. The balance current in this case was similar to the pulse insertion technique. However, the dispersed charge was very small for each cycle. Finally, when the offset balancing current was controlled high, the gain with a large time constant and the electrode steady-state potential became positive and negative thresholds over time as shown in Fig. 13d). You can move between. In Fig. 13 d), each time the electrode potential fell below 100 mV, the offset balancer significantly increased the balance current and stepped the steady-state potential to a higher value. These results show that when time constants are too small, they can offset current updates that are too large or too small, consistent with effects of normal state potentials.

The total energy consumption of an ES equipment is generally more than 99%. The AMP, PW, FREQ, and VDH can reduce the amplitude, pulse width, frequency of stimulation current, and power supply voltage of current driver for each device. In this method, a closed loop can be formed to adjust the stimulation current in the closed loop. With existing devices, it is not possible to provide only electrical stimulation to target neurons or read the target state before/after stimulation[30]. Several closed-loop procedures, stimuli, detections, and tuned devices can find the optimal device that exceeds the nerve here threshold of the target neuron that induces the same response. When an excitatory neuron returns to a dormant state, it means a recovery time that can prepare for the next stimulus. When it enters a nerve cell at a T-Refractory state, it should not be excited by some stimuli for a while. Measurement results before and after applying the closed loop to the device are shown. AMP, PW, FREQ, and VDDH were 2.1 mA, 2.1 ms, 500 Hz, and 9.2 V, respectively, when the proposed method was not applied. When the closed loop system was applied, these parameters were optimized to be 0.6 mA, 404 us, 200 Hz, and 3.1 V, respectively. Therefore, the number of devices can decrease sharply at 0.67%.

CONCLUSION:

Successful cases of electronic contracts are visualized. There is increasing interest in the development of advanced new electronic contracts that can replace conventional drugs. Centered on global IT companies, related markets are gradually expanding. CMOS-based neurostimulation systems have been widely developed for use in various implantable biomedical applications such as nerve prostheses that can restore limb movements and implants that can help restore vision in patients with visual impairment. They can also be used for the purpose of Deep Brain Stimulation (DBS) for patients with epilepsy. The basic concept of neurostimulators is to transfer and recover a controlled amount of charge to initiate behavior in the brain and stimulate degenerated or damaged neurons in important parts of the body.

In this study, a high-quality programmable qi-mimicking stimulus IC generated a large number of pulses. It can train and cluster with dead time slots, thus increasing the single duration of the therapy up to 24 hours. A new stimulation method based on the SNC artificial neuron model was proposed and constructed to mimic the behavior of neuronal cells. The stimulation IC proposed by SNC can output spikes of four types of neurons at 10 μW consumption. For long-lived implantable medical applications, there is a need to develop highly energy-efficient biofeedback stimulation systems. To extend their lifespan and to optimize adaptive parameters of new device reduction technology, closed-loop algorithm can be applied based on biological properties of neurons.

ACKNOWLEDGEMENT:

This work was supported by the Dong-Ju College Research Fund.

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Received on 08.12.2021 Accepted on 29.12.2021

Int. J. Tech. 2021; 11(2):63-69.

DOI: 10.52711/2231-3915.2021.00009