Ординатура / Офтальмология / Английские материалы / Artificial Sight Basic Research, Biomedical Engineering, and Clinical Advances_Humayun, Weiland, Chader_2007
.pdf190 Ren et al.
stratums of parenchyma were peeled off to expose osteal tissue. Along the bone wall, the upper eyelid was opened and the cartilage of orbit was removed with rongeur. Conjunctivae were opened along eyeball wall until ciliary vasa were touched. Between the two ciliary vasa, the white colored optic nerve (about 3 mm width) was obviously exposed without any pull and push. Throughout the exposing procedure, care should be taken not to damage the blood vessels on the choroid.
Implantation of stimulating electrodes
With the help of surgical microscope, a tungsten electrode was inserted into the exposed optic nerve through the incision of the orbit. There were three positions for placing the stimulating electrode (Figure 10.3). The distances from all of the three sites to the optic nerve head were the same, about 2 mm in front of anterior band for better retina–optic nerve mapping. Site 1 was at the surface of the optic nerve sheath, with the cut-end electrode pressing on the sheath. Site 2 was intraand para-optical nerve sheath. An incision was cut using a bistoury with tip angle 15 . Then the electrode was inserted into the space between dura and pia of the optic nerve. For site 3, electrode was passed through dura and pia and penetrated into the optic nerve bundles, about 1 mm deep into the optic nerve.
Implantation of recording electrodes
An incision in the skin nearby the occipital bone was cut, which was contra lateral to the stimulated optic nerve, about 8 mm anterior to the lambda and 7 mm lateral to the midline. And a corresponding hole through the site of skull was drilled. A tungsten electrode ( 100 m) was screwed into the skull to contact the dura, used as a recording electrode. A stainless steel electrode inserted into one of the rabbit’s earlobe was the ground. The reference electrode, which was the same type as the ground one, was inserted subcutaneously at the forehead.
Electrical Stimulation and Recordings of Electrical Evoked Cortical Potential
For the first experiments three different places of the optic nerve were stimulated respectively. The reference electrodes were all located at the sclera for the three different stimulating positions. A short charge-balanced biphasic pulse was used for the electrical stimulation. The biphasic rectangular pulse consisted of a negative pulse and a second opposing pulse. The pulses duration were 1 ms. The current amplitude was 50 A, which was generated with an electronic stimulator (RX7 Moray, Tucker-Davis Technologies, USA) and a stimulus isolator (MS16, Tucker-Davis Technologies, USA). While the electrical stimulation was applied to the optic nerve, the electrical evoked cortical potentials (EEPs) were recorded from the recording electrodes on the cortex opposite to the stimulated eye. EEPs were recorded using a data acquisition system (RX7 Moray, TuckerDavis Technologies, USA) connected to a low noise, battery-operated amplifier (RA16PA Tucker-Davis Technologies, USA) and filtered with a band-pass of 1–300 Hz. Results from 50 trials were averaged and analyzed.
For the experiments where stimuli with different parameters were applied we chose the third stimulating position. Firstly, the amplitude of the pulse was
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Figure 10.3. Schematic of three anatomical positions for electrical stimulation: (a) the surface of the optical nerve sheath; (b) intraand para-optical nerve sheath; and (c) intra-optical nerve by the penetrating electrode.
varied (25uA, 50uA, 100uA) while the duration of each pulse was kept constant (0.6 ms). Then we changed the duration of the pulse (0.3ms, 0.6ms, 1.2ms) and the pulse amplitude was kept 25 A.
In all the electrophysiological experiments, cortical responses to electrical stimulation were recorded within 1–3 h after electrode implantation.
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Result
The EEPs could be recorded with the recording electrode when the electrical stimulation was applied to any of the three stimulating positions, which are shown in Figure 10.4. The implicit times of the first positive peak (P1) and the amplitudes of the EEPs both are significantly different among the three different
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Figure 10.4. Diagram of stimulating current pulse (Top). EEPs recorded after biphasic electrical pulse applied to different stimulating places of the optic nerve (Bottom): (a) EEP elicited by stimulating the surface of the optical nerve sheath, (b) EEP elicited by stimulation with the electrode intraand para-optical nerve sheath, and (c) EEP elicited by stimulation with the electrode intra-optical nerve. For the three stimulating places, the pulses duration were 1 ms and the current amplitude was 50 A.
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stimulation methods. The stimulation of the penetrating electrode implanted into the optic nerve elicits the strongest signal of EEP while that of the electrode placed at the surface of the optic nerve sheath elicits the weakest signal of EEP. And the stimulation with the electrode penetrated in the optic nerve also has the shortest implicit time (Figure 10.4c), while the other two have longer implicit time.
The EEP waveforms elicited by different stimulation parameters are shown in Figures 10.5 and 10.6. Figure 10.5 shows the waveforms when the amplitude of the pulse was changed. As a general rule, the data from the experiments indicates that the higher the stimulation current, the higher the response amplitude of the epidural recording. The stimulation of 100 A elicited a higher response than the other two. The implicit time of P1 elicited by the stimulation of 100 A was similar to that by the stimulation of 50 A, which was about 4 ms. The implicit time of P1 elicited by the stimulation of 25 A was longer than the other two, which was about 8 ms. Figure 10.6 shows the waveforms when the duration of the pulse was changed. The result indicates that the longer the pulse duration, the higher the response amplitude of the epidural recording, which can be explained by the different charge densities of the different stimulation.
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Figure 10.5. EEP waveforms elicited by the different pattern stimulations with fixed pulse duration and varied amplitude: (a) pulse duration 0.6 ms, amplitude 100 A; (b) pulse duration 0.6 ms, amplitude 50 A; and (c) pulse duration 0.6 ms, amplitude 25 A.
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Figure 10.6. EEP waveforms elicited by the different stimulations with varied pulse duration and fixed amplitude: (a) pulse duration 1.2 ms, amplitude 25 A; (b) pulse duration 0.6 ms, amplitude 25 A; and (c) pulse duration 0.3 ms, amplitude 25 A.
Stimulation of longer pulse duration has higher charge density than that of shorter pulse duration, so the stimulation whose pulse duration is 1.2 ms elicits the strongest signal of EEP (Figure 10.6a).
The experimental results demonstrated that the visual cortex can be excited by the electrical stimuli to the optical nerve at any of the three anatomical positions i.e., stimulation at the surface of the optical nerve sheath, intraand para-optical nerve sheath, and intra-optical nerve by the penetrating electrodes. Furthermore our experiments indicate that different stimulation parameters can elicit different responses at the visual cortex, suggesting that this approach may be useful for a visual prosthesis system.
Light Evoked Potential Measured at Optic Nerve Bundle
In order to investigate the mechanism of the response of the retina to the color stimulation and the effect of the optic nerve sheath to the conduction of bioelectrical signal, we conducted another series of experiment. Evoked potentials were recorded from the optic nerve while the eye of the rabbit was stimulated by photic stimuli.
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Methods
Tungsten electrodes ( 100 m) were used for recording the evoked potential and two positions were chosen for placing the recording electrode. Site 1 was at the surface of the optic nerve sheath, with the cut-end electrode pressing on the sheath. For site 2, electrode was passed through dura and pia and penetrated into the optic nerve bundles, about 1 mm deep into the optic nerve. Three different photic stimuli (white light, blue light, red light) were used to stimulate the eye. In all the experiments the stimulus was a Ganzfeld flash of short duration generated with a visual electrophysiological diagnostic system (TEC, China). For each kind of stimulus, two different frequencies of 1.98 Hz and 7.3 Hz were used here, which were chosen purposely to cancel 50 Hz power-line interference. While the photic stimulation was applied to the eye, the light evoked potentials (LEPs) were recorded from the recording electrodes (Figure 10.7).
Results
Like the recordings of EEP, we recorded and calculated LEP waveforms by a computer using OpenEx software (Tucker-Davis Technologies, USA). The evoked potentials were filtered with a band-pass of 1–300 Hz and results from 50 trials were averaged and analyzed.
The LEP waveforms when the recording electrode was at the surface of the optic nerve sheath are shown in Figure 10.8. There were no distinct waveforms of LEP for any of the stimulation.
(a) Intra-Optic Nerve
(b) At Optic Nerve Sheath
Figure 10.7. Diagram of the photic stimulation and the recording of the light evoked potential.
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Figure 10.8. LEP recorded from the recording electrode at the optical nerve sheath by different wavelengths of the stimulating light sources.
The result indicates that minimal LEP signals were measured at the surface of the optical nerve sheath position by the recording electrode, which demonstrates that the optic nerve sheath can shield the conduction of bioelectrical signal. So
Figure 10.9. LEP recorded from the recording electrode penetrated into the optical nerve by different wavelengths of the stimulating light sources.
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when we want to stimulate the optic nerve, it will be more effective to penetrate the stimulating electrode in the optic nerve bundle.
Figure 10.9 shows the waveforms when the recording electrode was penetrated in the optic nerve. Different patterns of the LEP can be recorded when different wavelengths of the stimulating light sources are applied to the rabbit retina, which indicates the different color coding processes can be detected from the recording electrode penetrated into the optical nerve. The blue light stimulation elicited the strongest response and the 7.3 Hz red light stimulation did not elicit distinct response.
The results of our experiment demonstrate that the LEP can be measured only at the position of intra-optical nerve by the penetrating recording electrode. Comparing with the other wavelengths of light stimulation, the LEP was recorded strongest by the blue light stimulation. As shown in Figure 10.9c, there were no LEP signals recorded at the red light stimulation with the stimulation frequency greater than 7.3 Hz.
The Hardware Design of Visual Prosthesis
In the past several years, many approaches have been pursued to provide the neural electrical simulation at various positions of the visual pathway, such as visual cortex and retinal and optic nerve, to restore the vision of the blind patient. Although the most significant difference of these approaches is the interface to the nervous system, all of them share a common set of components, such as micro-camera, visual information processing and extraction system, power and information transmission system, neural electrical simulator and electrode array (Figure 10.2).
Here we present some progress of hardware design in our projects.
Image Acquisition System
As the prosthesis is going to be implanted into the human eye, all the components should be small in size with low weight and low power dissipation. A number of image acquisition devices or mini-cameras are available and suitable for this application. It is possible to integrate both Charge Coupled Device (CCD) and Complementary Metal-Oxide Semiconductor (CMOS) cameras into the visual prosthesis. Although CMOS camera is more susceptible to noise and has lower light sensitivity than CCD, it is more suitable for implantable visual prosthesis application with some crucial features, such as lower power dissipation, single supply operation and camera-on-a-chip integration. As a result of the rapid development of advanced microelectronic fabrication techniques, now A/D conversion can also be integrated into one common CMOS camera microchip with the image sensors. OV6650FS (Omnivision Co.) was chosen as the photo-sensor in our image acquisition system, for it is the minimum CMOS camera on the market and has relatively lower power dissipation. On the other hand, the resolution
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of CIF (352 × 288) of OV6650FS is enough for visual prosthesis prototype. Noelle R. Stiles et al have found that only 625 pixels are enough for object recognition by blind people [10]. In the first step of visual prosthesis research, the miniature camera will be set in the patient’s spectacle. Further it will be implanted into patient’s pupil after a more biocompatible subminiature custom camera is developed.
The real-time image acquisition and processing in visual prosthesis consists of the implementation of various image processing algorithms like edge detection, edge enhancement, decimation, etc. [11]. Accordingly it needs high performance CPU to satisfy the high level of computational complexity. Especially when the penetrating electrodes and image are not clear in mapping the relationship, extra algorithms are required to design the appropriate stimulation pattern for the optical nerve prosthesis. For these reasons, one type of high performance DSP (TMS320DM642) was used to fulfill the successive image acquisition and processing. Figure 10.10 shows the basic connection between DSP and CMOS camera.
Image Processing Strategies
The ultimate goal of vision prostheses is to artificially produce visual perception in individuals with profound loss of vision due to disease or injury. With the help of visual perception, these individuals can perform activities, such as reading text, recognizing faces and exploring unfamiliar spaces.
Due to the constraints of fundamental physiology and the complexity of implanting process, none of the visual prosthesis can consist of enough electrodes to make a relationship with image sensors one by one. The image grabbed by the micro-camera must be extracted to form some necessary visual information as simply as possible. Then the neural encoder will transform the visual information to the electrical stimulus pattern. So some advanced strategies should be established to extract effective visual information from the original image. Some useful algorithms [12] which can be applied are given below.
Figure 10.10. Functional diagram of the image acquisition system.
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Histogram Equalization
Histogram equalization is one of the popular image enhancement transformations. It is used to obtain a uniform histogram and can improve contrast of the image. This algorithm can be used on a whole image or just a part of the image.
Histogram modeling [13] is usually introduced using continuous, rather than discrete, process functions. Therefore, we suppose that the image of interest contains continuous intensity levels (in the interval [0,1]) and that the transformation function f which maps an input image A(x,y) into an output image B(x,y) is continuous within the interval. Furthermore, we assume that the transfer law (which may also be written in terms of intensity density levels, e.g. HB (s) = f (HA(r))) is single-valued and monotonically increasing (as the case in histogram equalization) so that it is possible to define the inverse law HA (r) = f−1(HB (s)). An example of such a transfer function is illustrated in Figure 10.11.
Edge Detection
The edges of an image hold much information, such as position, texture, shape and size. An edge is where the intensity of an image moves from a low value to a high value or vice versa.
The human visual system is very sensitive to details, especially abrupt changes or edges. These details in the frequency domain are always located in the high frequencies.
One way to detect edges or variations within a region of an image is by using the gradient operator. For instance, the gradient G is a vector with two elements Gx and Gy, where Gx is the gradient in the width direction and Gy is the gradient in the height direction. Since G is a vector, its magnitude Gm and direction anglecan be given as:
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Figure 10.11. Example of histogram transformation function.