Ординатура / Офтальмология / Английские материалы / Artificial Sight Basic Research, Biomedical Engineering, and Clinical Advances_Humayun, Weiland, Chader_2007

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Large-scale Integration–Based Stimulus Electrodes for Retinal Prosthesis

Jun Ohta1, Takashi Tokuda1, Keiichiro Kagawa1, Yasuo Terasawa2, Motoki Ozawa2, Takashi Fujikado3 and Yasuo Tano4

1Graduate School of Materials Science, Nara Institute of Science and Technology (NAIST)

2 Vision Institute, R&D Div., NIDEK Co., Ltd.

3Department of Applied Visual Science, Osaka University Medical School 4Department of Ophthalmology, Osaka University Medical School

Introduction

Since large-scale integration (LSI) technologies allow integration of smart functions such as image sensing, control, amplification, and signal processing with stimulators, LSI-based retinal prosthesis devices are attracting significant interest [1, 2]. We have been developing retinal prosthesis devices based on Complementary Metal Oxide Semiconductor (CMOS) LSI technology [3–11]. In our project, the implanted stimulator is placed underneath the retina (subretinal implantation) or upon the suprachoroid; this stimulation method is called suprachoroidal transretinal stimulation (STS) [12, 13].

In subretinal implantation, a photosensor is integrated with a stimulus electrode in order to substitute for photoreceptor cells. Thus far, a simple photodiode array without any bias voltage, i.e. the solar cell mode, has been used as a photosensor mainly due to its simple configuration [14, 15]. The photocurrent is directly used as the stimulus current into retinal cells. In order to realize sufficient stimulus current using a photosensor in a daylight environment, we first propose a pulse frequency modulation (PFM) photosensor, which is fabricated using standard CMOS LSI technology, although a PFM photosensor needs an external power supply, which can be provided through RF coupling coils. A PFM photosensor converts input light intensity into an output pulse train, the frequency of which is proportional to the light intensity [16, 17]. Recently, another group has proposed that a PFM photosensor or a pulse-based photosensor might be applied to retinal implantation [18, 19].

The PFM appears to be suitable as a retinal prosthesis device in subretinal implantation for the following reasons. First, PFM produces an output of pulse streams, which would be suitable for stimulating the cells. In general, pulse

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Ref. [6]. The PFM is an output representation in which an analog output is converted into a pulse frequency. In order to employ a PFM, relaxation oscillation circuits are constructed as shown in Figure 8.1. The photodiode PD acts as a variable current source controlled by the input light intensity with capacitance CPD associated with the pn-junction. The capacitance is charged through the reset transistor Mr, and then electrically floated. The photocurrent discharges the charged capacitance and thus the voltage at the cathode node of the PD, VPD, decreases from the reset voltage. When VPD reaches the threshold voltage of the inverter Vth, the output pulse is produced after a delay time td and simultaneously Mr is reset. Repeating the process, the output pulse train is generated according to the input light intensity. In such a configuration, the stronger the light intensity, the higher the pulse frequency. The analog value of the light intensity is consequently converted into a pulse train as a digital signal. The output pulse frequency is approximately expressed as:

where Rph is the photosensitivity, Id is a dark current of PD, P is the input light power, td is the delay time of feedback circuitry, respectively. From Eq. (1), the output frequency is proportional to the input light intensity if the delay time is negligible.

Figure 8.2 shows the experimental result of output pulse frequency as a function of input light intensity [6]. A wide dynamic range of over 120 dB is

Figure 8.1. Block diagram of the PFM photosensor.

The frequency limitation, however, causes a reduction in the range of input light intensity. We have alleviated this problem by introducing a variable sensitivity: the output frequency is divided into 2−n with a frequency divider, where n is the number of divisions. Note that the digital output of the PFM is suitable for the introduction of such a logic function of the frequency divider. Table 8.1 summarizes the photosensor requirements for a retinal prosthesis.

Based on the above modifications, we have designed and fabricated a pixel circuitry using standard 0 6- m CMOS technology. Figure 8.3 shows a block diagram of the pixel. The frequency limitation is achieved by a low pass filter using switched capacitors. The biphasic current pulse is implemented by switching the current source and sink alternatively.

Figure 8.4 demonstrates the experimental result of the variable photosensitivity using the chip. The original output curve has a dynamic range of over 6-Log

Figure 8.3. Block diagram of the PFM photosensor with variable photosensitivity.

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Figure 8.4. Output pulse frequency of the PFM photosensor with variable photosensitivity as a function of input light intensity. Reprinted from Ref. [4] with permission from IEEE.

(6th-order range of input light intensity), but is reduced to around 2-Log to be limited at 250 Hz when the low pass filter is turned on. By introducing the variable sensitivity, the total coverage of input light intensity becomes 5-Log between n = 0 and n = 7. The other functions in Table 8.1 have also been demonstrated.

Image Preprocessing Using the PFM Photosensor

When the PFM-based stimulator device is applied to a retinal prosthesis, the resolution is less than approximately 30 × 30. This limitation arises because the electrode pitch is larger than 100 m, according to the electrophysiological experiments, and the width of the chip is less than approximately 3 mm according to the implantation operation. In order to obtain a rough but clear-shaped image with such a low resolution, image processing, such as edge enhancement, is preferable.

In order to implement image processing, we have proposed a new principle of spatial filtering in the pulse frequency domain [7]. The spatial filtering is generally based on the spatial correlation operation using a kernel h as

x y

Here, f x y and g x y indicate the pixel values at x y of input and output images, respectively; h x y is a kernel weight.

Usually, f , g, and h are analog values for analog image processing or integers for digital image processing. In our scheme, f and g are represented as pulse frequency. Thus, for our implementation, we consider a method by which to represent the kernel weight in the pulse domain.

We introduce the interaction with the neighboring pixel as the gate control of the pulse stream from the neighboring pixel. This concept is illustrated in Figure 8.5. The absolute value of the kernel weight, h , is expressed as the on– off frequency of the gate control. The sign is expressed as follows. In order to realize negative weights in the spatial filtering kernel, the pulses from a pixel are collided with those from its neighboring pixels in order to make them disappear. For positive weights, the pulses from the pixel are merged with those from the neighbors. These mechanisms can be achieved by simple digital circuitry. In the architecture, a 1-bit pulse-buffering memory is implemented to absorb the phase mismatch between the pulses to be interacted.

The proposed architecture enables us to execute fundamental types of image processing, such as edge enhancement, blurring, and edge detection. The advantage of our architecture over straightforwardly implemented digital spatial

Figure 8.5. Concept of (a) image processing in the PFM-based image sensor, and its image processing results, (b) original captured image, edge enhancement, and blurring.

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filtering is that the number of required logic gates is small because there is no need for adders or multipliers.

We have also implemented a binarization circuit based on an asynchronous counter with N-bit D-FF. The input of the D-FF of the MSB is fixed to HIGH. When 2N −1 pulses are input, the output of the counter turns HIGH from LOW. This means that the counter works as a digital comparator with a fixed threshold of 2N −1.

According to the proposed architecture, we have designed and fabricated a PFM-based retinal prosthesis device with 16 × 16 pixels. Figure 8.6 shows microphotographs of the fabricated chip, peripheral circuits, and its pixel. As shown in Figure 8.7, each pixel has a PFM photosensor, the above-described image processing circuits, stimulating circuits, and a stimulus electrode, i.e. this chip can stimulate retinal cells. We used this chip for in vitro electrophysiological experiments of stimulating retinal cells, as described in the following section. Here, we present only the image processing results. Figure 8.5b shows the experimental results of image processing using the chip: an original image, edge enhancement, and blurring. These results clearly demonstrate that the proposed architecture works properly.

Figure 8.6. Microphotographs of the fabricated chip, peripheral circuits, and its pixel.