J. Biomedical Science and Engineering, 2013, 6, 1-7 JBiSE
http://dx.doi.org/10.4236/jbise.2013.610A2001 Published Online October 2013 (http://www.scirp.org/journal/jbise/)
The effect of transcorneal electrical stimulation in visual
acuity: Retinitis pigmentosa
Daniel Robles-Camarillo1, Luis Niño-de-Rivera2, Jessica López-Miranda3, Félix Gil-Carrasco3,
Hugo Quiroz-Mercado4
1Department of Telematic Engineering, Universidad Politécnica de Pachuca, Zempoala, México
2Graduate Department, ESIME UC, Instituto Politécnico Nacional, México City, México
3Retina Service, Asociación Para Evitar la Ceguera en México, México City, México
4Ophthalmology Service, Denver Health Medical Center, Denver, USA
Email: danielrc@upp.edu.mx
Received 25 July 2013; revised 30 August 2013; accepted 15 September 2013
Copyright © 2013 Daniel Robles-Camarillo et al. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Transcorneal Electrical Stimulation (TES) was ap-
plied to a group of volunteer patients suffering from
Retinitis Pigmentosa (RP), in order to investigate the
effect of TES in Visual Acuity (VA). 28 partial blind
patients with diagnosis of classic RP, Usher syndrome
I and/or II were stimulated transcornealy, during a
period of 52 weeks using a non conventional wave-
form, only in the lowest visually capable eye. The pro-
posed waveform has been modeled from the natural
response of human retina and delivered by means of
an adaptive generator designed and built for tissue
stimulation. Statistical results show the improvement
of average VA or at least the contention of the disease
natural progress. Categorized analysis of results in-
dicates the same effect that if the age of patients, time
since diagnosis and genetic disorder variation (classic
RP, Usher syndrome I and/or II) are considered, in
this case clinical and electrophysiological follow-up
parameters were statistically analyzed in order to
know the effect of TES. General results yield an im-
provement of 48.15% in the average of VA for stimu-
lated eyes against an average degreasing of 8.06% in
the same scale, with respect to their basal condition
before the start of the experiment.
Keywords: Transcorneal Electrical Stimulation;
Retinitis Pigmentosa; Adaptive Waveform Model; Visual
For most of the degenerative retinal and optic nerve
diseases, there is no satisfactory treatment to reverse or
even stop the course of degeneration. As a result, several
million people worldwide become blind every year,
however, TES has been used for the treatment of “am-
blyopia and amauroses”, for “retino-choroiditis with pig-
ment infiltration”, “glaucoma” and “white optic atrophy”
[1]. Recent studies suggest that Transcorneal Electrical
Stimulation (TES) using 20 Hz biphasic pulses up to
1100 uA can improve retinal function in human eyes
with Central Retinal Artery Occlusion (CRAO) [2]. Most
recent experiments report that 5 ms biphasic pulses at 20
Hz produce a tendency for most functional human visual
parameters to improve or remain constant such as Visual
Acuity (VA), Visual Field (VF), etc. [3]. In experiments
with animals, it is present the same tendency to apply
squared electrical pulses between 0.5 and 5 ms/phase at
20 Hz, and a range of current intensities from 50 to 500
mA [4]. However, retinal cellular processes do not have
sudden transients, as is proposed by the model of photo-
receptors ionic currents [5], which have non linear dyna-
mics against time.
The relationship between the parameters of TES and
its neuroprotective effect in axotomized retinal ganglion
cells (RGCs) is not clear yet. TES generally has been
proposed using pulse trains [2-4] to modulate neural
activity. However, biphasic waveform does not allow
fine control of the pattern of elicited activity. Usui et al.
[5] reported that a single rod behaves as a bandpass filter
whose characteristics are affected by the stimulus strength
and frequency, and their network model indicates that the
contribution of individual ionic currents to band-pass
filtering of small signals is largely regulated by the
calcium-dependent currents IK(Ca) and ICl(Ca), where-
as the filtering of large signals is regulated by the hyper-
polarization-activated current, Ih. Furthermore, the rod
network model electrically interconnects between single
D. Robles-Camarillo et al. / J. Biomedical Science and Engineering 6 (2013) 1-7
rod models and reveals that the acceleration of signals
that spread laterally through the rod network is not
attributed to Ih but IK(Ca) [5]. The use of alternative sti-
mulus waveforms to improve the control of neural acti-
vation has not been well studied. The choice of stimulus
waveform for use in TES should be made with some
understanding of the temporal response properties of the
neurons being activated. The goal is to find the wave-
form parameters to optimally excite a group of neurons.
It is first necessary to find the waveform which these
neurons are more sensitive.
The flow of ions through neural membrane cells is
analogous to the sum of positive and negative electrical
currents at a node; this implies the generation of multiple
action potential waveforms. Neuronal graded action po-
tentials play a central role in retinal process between the
photoreceptors and the RGCs. In this way retinomorphic
waveforms designed for TES should be analogous to
biological computation. We suppose that the use of novel
stimulus waveforms has the potential to improve control
and effect of the patterns of elicit neural activation, both
in terms of the temporal structure of elicited spike trains,
and in the types of neurons or neuronal substructures
being activated.
According to cellular and neural threshold which ex-
plains the biochemical communication process by means
ionic exchange; electrical, mechanical and chemical im-
pulses can fire this process [6], but in no cases do those
processes have a high frequency behavior [5,7]. With
this in mind, we have proposed an experimental protocol
in order to apply TES to 28 patients with Retinitis Pig-
mentosa (RP) diagnosis (Dx), along a period of 52 weeks
using a stimulation waveform model based on the natural
human cellular response to a light impulse, previously
modeled and reported [8,9].
1.1. Waveform Mathematical Model
The stimulation waveform reported in this paper and
used in experiments (registered at clinicaltrials.gov NCT-
00802698) fits more accurately with the human ocular
system, because it is a copy of the voltage waveforms
present in the cornea. When light stimulated the human
retina and registered using a multi-focal electroretino-
graphy (mfERG), the curve was processed to obtain a set
of mathematical approximation functions [8]; we mod-
eled the curve by means of the mean squared statistical
regression method getting the description of the elec-
troretinography (ERG) by a continuous polynomial [9].
The Linear Model
The general model for each curve section is indicated in
Equation (1), where t represents the time, and f(t) the
tatatat at (1)
Figure 1(a) shows a common biphasic waveform ap-
plied in TES research [2] and Figure 1(b) the simulation
of the modeled voltage waveform, from a healthy volun-
teer’s mfERG [8].
The proposed polynomial in Equation (1) is linear;
however, the mfERG curve has a non linear behavior. To
avoid that difficulty, the fitting curve was divided into
three sections: we calculated the middle time between a
voltage crest and a trough in order to locate the begin-
ning and the end between data groups [10] shown in Ta-
ble 1; the approach is a non linear approximation of the
waveform required. Table 2 shows the linear polynomi-
als to define the mathematical model.
1.2. Adaptive Model
In order to estimate the analog stimulating signal, an
adaptive Finite Impulse Response (FIR) filter is then pro-
posed, and its coefficients are estimated from an adaptive
identification system in which weights are calculated by
the Normalized Least Mean Squared (NLMS) algorithm.
The polynomial models are represented in Figure 2 by
Y(n), using 1 ms as sampling time; the constant factor k
digitally limits the waveform voltage amplitude [8,9].
0 20 40 60 80
Time ms
20 ms
50 ms
Voltage mV
Figure 1. (a) Biphasic waveform applied on transcorneal ex-
periments [2]; (b) Simulation of the voltage waveform used in
these experiments [8].
Table 1. Time parameters for each mathematical model.
Time intervals Section 1 Section 2 Section 3
Start time (ms) 0 39.95 71.73
End time (ms) 36.13 69.56 84.74
Table 2. Mathematical models.
SectionFitting polynomials (t represents time)
1 234
0 15170 16830 12340 17980 1293..t.t.t. t
1101 19750 10240 00320 000012..t.t. 3
1103 0895014630 00260 00001346..t.t. 3
Copyright © 2013 SciRes. OPEN ACCESS
D. Robles-Camarillo et al. / J. Biomedical Science and Engineering 6 (2013) 1-7
Copyright © 2013 SciRes.
of the study; the research protocol was previously ap-
proved and registered by the human experimentation in-
stitutional committee APEC hospital (registered at clini-
caltrials. gov NCT00802698) which was conducted ac-
cording to good clinical practice (GCP).
x(n) = 1
The electrodes applied in this research in order to
stimulate corneal tissue are shown in Figure 4(a), and
they are those commonly used to measure voltage re-
sponses in ERG tests: 2 gold-cup scalp for reference and
ground electrodes and a monopolar contact-lens elec-
trode, commonly known as the Ganzfeld contact-lens
(ERG-jet, Universo Plastique Switzerland), Figure 4(b)
shows the analog waveform present in the electrodes
when the stimulator is active.
Figure 2. Block diagram of the adaptive system [8,10].
Convergence Algorithm
The system’s adaptation is carried out by using the nor-
malized convergence algorithm NLMS, shown in Equa-
tion (2), using α = 1 and x(n) = 1 as a bias constant vec-
tor. In order to calculate the adaptive FIR weights w(n);
xT(n) indicates the transpose of the vector x(n).
Before beginning the patient’s stimulation, slit-lamp
examinations and ophthalmoscopy were performed, vis-
ual acuity (VA) was tested using Early Treatment Dia-
betic Retinopathy Study (ETDRS) eye chart, Humphrey
24-2 BB visual fields (Humphrey Instruments, San Lean-
dro, CA, USA) and visionmonitor8k electrophysiological
recordings (Metrovision, Pérenchies, France) baseline
and every 10 weeks. After those examinations, we chose
the eye with the worst visual acuity (lower than 20/20) or
worst visual capacity (ETDRS characters read) as the eye
under test. To assess the changes induced by TES, those
examinations and tests were repeated every five weeks
for each patient, in order to monitor the TES effect.
    
wnwnxn en
xnx n
 
1.3. Electronic Design
The FIR filter output is programmed into a microcon-
troller’s memory, allowing us to convert the digital data
into an analog signal, indicated in Figure 2 as digital to
analog converter (DAC). Using conventional electronics,
we designed a portable electronic device preprogrammed
with the electrical phosphene threshold (EPT) average,
previously reported [9,10]. Those characteristics permit
the transcorneal electrotherapy to be randomized for each
2.1. Inclusion Criteria
We selected 28 volunteers suffering from classic RP and/
or Usher syndrome type I or II, female (not pregnant
women) or male older than 18 years, without macular
edema or other related ocular diseases such as glaucoma,
nor previous ocular surgery (intraocular lens (IL), re-
tinopexia, vitrectomy, trabeculectomy), and typical in-
traocular pressure around 14 to 16 mmHg.
This research followed the tenets of the Declaration of
Helsinki, all patients gave written informed consent after
an explanation of the nature and possible consequences
Floating power source
Slave μc
Master μc
Sonorous indication
Luminous indication
Regulated voltage
Digital data
Battery charger
Voltage source
LCD Display
Attenuator &
Figure 3. Block diagram of the electronic system [9,10].
D. Robles-Camarillo et al. / J. Biomedical Science and Engineering 6 (2013) 1-7
Tek Hold: 12.5ks/s 2 Acqs 0.000 VDC
Ch 1 100 mV M 20 ms Ch 1
34 mV
1 Freq
11.79 Hz
Figure 4. (a) Stimulating electrodes; (b) Voltage waveform
measured with osciloscope [9].
2.2. Methods
All patients were transcorneally stimulated 45 minutes
per week during fifty two weeks, with the voltage wave-
form shown in Figure 4(b) calibrated with maximum
crest to 300 mV, and frequency of 11.8 Hz, which is the
analog voltage signal generated by using the bipolar
voltage waveform generator shown in Figure 3. In order
to compare the evolution in the Stimulated Eye (SE), we
recorded the visual capacities for the contralateral eye
too (Non Stimulated Eye NSE); those were the control
Electrodes Placement
Patients were prepared with the electrodes, following the
standard ERG procedure according to the ISCEV stan-
dard [2,8-12], previous to each TES session as is de-
scribed: the skin of the patient’s face was cleaned by
applying propanediol 1.2 with sterilized cotton. The
ground electrode and the electrical reference electrode
were placed by applying polyoxyethylene 20 and attach-
ing them with adhesive tape. A drop of tetracaine hy-
drochloride 5 mg was applied in the patient’s eye to re-
duce the mild foreign body sensation and the lens elec-
trode was placed on the cornea applying hipromelosa 2%
into the lens, this procedure was done only to the eye
being tested. Figure 5 shows the patient wearing the
This protocol started with 42 patients but only 28 com-
pleted the 52 week stimulation period and the last fol-
low-up visit (55th week). There were no adverse events
reported (ketaritis, irritation of conjunctiva, etc.), pro-
duced by the disposable contact-lens electrode.
3.1. Results of Average VA of All Patients
In order to verify the effect of TES in visual capacities of
patients, we used the least mean squared (LMS) lineal
regression method, to compare the tendency between
ETDRS data, for SE and NSE. Figure 6 shows the statis-
Figure 5. Patient wearing the electro-
des ready for TES [9].
on stimulated
VA Snellen ratio
0 10 20 30 40 50 60
Week s
0.0010 t + 0.5726
0.0035 t + 0.4641
Figure 6. Comparison of the VA average measurements
between SE (circle), vs NSE (square) for all patients and
the statistical approximation equation (solid line).
tical comparison of VA average measurements between
SE against NSE for all patients in ETDRS chart Snellen
As we can see, the average statistical tendency is
growth for VA in Snellen ratio for SE and it is repre-
sented by the positive slope in the equation (correlation
coefficient = 0.9629). On the other hand for NSE the
same equation has a negative slope (correlation coeffi-
cient = 0.9272), which indicates a constant decrease of
the VA average in those results. The VA average for SE
reaches similar ETDRS average values around 25 weeks
of treatment.
3.2. Results of Average VA of all Patients:
Comparison vs Control Parameters
Similar results are presented by read characters in the
same ETDRS chart. Figure 7 shows this comparison.
3.3. Effect of TES Considering the Age of
In order to compare the effect of TES between groups of
patients, we analyzed the VA average by categorizing
patients in three age groups: subjects younger than 30,
between 31 and 50 and older than 51 years old. Figure 8
shows those results.
Copyright © 2013 SciRes. OPEN ACCESS
D. Robles-Camarillo et al. / J. Biomedical Science and Engineering 6 (2013) 1-7 5
(a) (b)
on stimulated
on stimulated
Difference to baseline (VA Senllen chart)
Difference to baseline (ETDRS characters read)
0 20 40 60
Week s
0 20 40 60
Figure 7. Comparison of lectures between SE (circle), vs NSE
(diamond) for all patients: (a) VA average in Snellen ratio; (b)
ETDRS average of characters read.
0 10 20 30 40 50 60
Age < 30
Non stimulated
VA Snellen chart
31 < Age < 50
51 < Age
Figure 8. Comparison of the VA average lectures between SE
(edge) vs NSE (shaded) for each age group.
In all cases the VA average for SE has a slight ten-
dency to grow but NSE shows a declining behavior
throughout the 55 weeks. In cases of patients younger
than 30, eyes with lower VA reach the same lecture val-
ues than NSE after 20 weeks of treatment, but patients
between 31 to 50 years old; the same condition is
reached after 30 weeks, in cases of patients older than 51
that condition is reached after the 45th week. In all cases
the VA average for SE improves over time.
Table 3 shows statistical data for the linear regression
analysis. The first coefficient of SE model is positive
(slope), which indicates that the tendency of data is
growing with time (t); opposite to the same parameter for
NSE, which has negative slope and tendency to decrease
versus time. The correlation coefficient (r) is a measure-
ment of the strength of the linear dependence between
two variables; a value equal to 1 implies that linear equa-
tion describes the relationship between the variables per-
fectly; a value 0 implies that there is no linear correlation.
The coefficient of determination (r2) which provides a
measurement of how well future outcomes are likely to
be predicted by the model and standard error (StdError)
is the difference between the estimate and the true value.
3.4. Analysis for Time Since Diagnosis
A similar behavior occurred for the time since Dx group:
fewer than 5 years, between 5 to 10 years and higher
than 10 years from the Dx time. Figure 9 shows the
graphic results, and Table 4 their statistical model and
As we can see the VA average at least remain constant
throughout the 55 week period, in the case of the 10 <
Dx time group in both SE and NSE, but in cases for Dx
time < 5 years and 5 < Dx time < 10 years, the VA for
SE is very close to the VA average for NSE around week
25 of treatment, then those values keep on growing,
compared with average VA for NSE which decreases
with time.
In Table 4 the linear model for SE is positive in all
cases, but for NSE it is negative in two groups, which
represents a similar behavior that was described in Table
3.5. According to the Genetic Variation
Another group of patients has been established according
to the type of diagnosis: classic RP, Usher syndrome I
20/ 100
20/ 100
20/ 100
Non stimulated
VA Snellen chart
0 10 20 30 40 50 60
Week s
Dx Time < 5
5 < Dx Time < 10
10 < Dx Time
Figure 9. Comparison of the VA average lectures between SE
(edge) vs NSE (shaded) for time since diagnosis (years) groups.
Copyright © 2013 SciRes. OPEN ACCESS
D. Robles-Camarillo et al. / J. Biomedical Science and Engineering 6 (2013) 1-7
Copyright © 2013 SciRes.
Table 3. Linear regression results for VA: Age of patients (years).
Group Regression model
r r2 StdError
age < 30 VA(t) = 0.0023 t + 0.3967 0.8668 0.9310 0.0173
31 < age < 50 VA(t) = 0.0044 t + 0.5123 0.9431 0.9711 0.0205
51 < age VA(t) = 0.0030 t + 0.4416 0.4784 0.6916 0.0586
age < 30 VA(t) = 0.0002 t + 0.4466 0.0445 0.2109 0.0195
31 < age < 50 VA(t) = 0.0019 t + 0.6682 0.6119 0.7823 0.0289
Non stimulated
51 < age VA(t) = 0.0003 t + 0.5177 0.0510 0.2258 0.0251
Table 4. Linear regression results for VA: Time since diagnosis (years).
Group Linear model
r r2 StdError
Time < 5 VA = 0.0042 t + 0.5244 0.9829 0.9914 0.0104
5 < Time < 10 VA = 0.0037 t + 0.4641 0.7972 0.8929 0.0351
10 < Time VA = 0.0020 t + 0.3536 0.4027 0.6346 0.0459
Time < 5 VA = 0.0013 t + 0.6565 0.3368 0.5804 0.0342
5 < Time < 10 VA = 0.0013 t + 0.5403 0.5773 0.7598 0.0210
Non stimulated
10 < Time VA = 0.0003 t + 0.4782 0.0437 0.2091 0.0251
and Usher syndrome II, Figure 10 shows their character-
0 10 20 30 40 50 60
Non stimulated
VA Snellen chart
Usher I
Usher II
These results are similar to those reported in Tables 3
and 4, for SE patients the slope in their linear model is
positive, but negative for NSE (in all cases) which indi-
cates the tendency to rise and drop respectively against
time of VA in both analyses. Table 5 shows the regres-
sion analysis parameter for this group of patients.
The 82.14% of the cases (23/28 patients) were unable
to finish at least one of the Humphrey 24-2 BB visual
fields test, due to the device automated fixation control
(AFC), those patients could not focus their eye on the
monitor’s central point through out the test, for several
Those data did not reach statistical significance. In
cases of a-wave, b-wave and implicit time for ERG re-
cordings. The 67.85% of stimulated patient’s eye did not
complete at least one test, again due to the AFC when the
visionmonitor8k system was used; those data were not
considered for statistical analysis. Figure 10. Comparison of the VA average lectures between SE
(edge) vs NSE (shaded) accords the type of diagnosis.
ters read had similar changes too; for SE the average
difference is 15.6% but for NSE the same difference is
5.45% throughout the 55 weeks (graphical data shown
in Figure 7(b)).
Statistical analyses indicate that TES applied to patients
suffering RP, Usher syndrome I and/or II, in general im-
proves their VA 48.15% (without separate patients in
groups), meanwhile NSE has a general decreasing ten-
dency around 8.06% in respect to the basal VA average
measurements. The average amount of ETDRS charac-
Statistically the group composed of SE of patients
with less than 5 years since diagnosis is the most effi-
D. Robles-Camarillo et al. / J. Biomedical Science and Engineering 6 (2013) 1-7 7
Table 5. Linear regression results for VA: Diagnosis type.
Group Linear model
r r2 StdError
RP VA = 0.0038 t + 0.4919 0.8915 0.9442 0.0251
Usher I VA = 0.0022 t + 0.2550 0.7602 0.8719 0.0236
Usher II VA = 0.0034 t + 0.5257 0.8384 0.9156 0.0281
RP VA = 0.0012 t + 0.6205 0.4674 0.6837 0.0233
Usher I VA = 0.0007 t + 0.3045 0.5167 0.7188 0.0134
Non stimulated
Usher II VA = 0.0004 t + 0.6053 0.0471 0.2170 0.0331
cient modeled, because their correlation coefficient (r)
and coefficient of determination (r2) are so close to 1
(Table 4), followed by the group of SE of patients be-
tween 31 and 50 years old, with the same characteristics
(Table 3). This means that the variability of measure-
ments (VA) is low enough to describe the statistical
modeled tendency, making the model accurate for statis-
tical validation.
With those estimations it is possible to affirm the
safety of the proposed TES waveform and parameters as
well as a partial effect of recovery and in some cases the
improvement of VA characteristics. It is more challenging
to prove the efficacy of treatment and establish methods
of comparison between similar treatments [3] in a disease
such as RP, due to the natural course of disease pro-
gression in these patients, it can be highly variable [3].
We acknowledge that our trial is small and most results
are not statistically significant, but in further proposed
protocols we will consider correcting the statistical va-
The authors thank Prof. Domenica Petulla (Culver Academies, IN,
USA), for her writing assistance, to Consejo Nacional de Ciencia y
Tecnología (CONACyT, México), the Universidad Politécnica de Pa-
chuca (UPP, México), the Instituto Politécnico Nacional (IPN, México)
and “Hospital Dr. Luis Sánches Búlnes” (APEC, México) for their
support in this research.
[1] Horsager, A. (2009) Prosthetic visual perception: Retinal
electrical stimulation in blind human patients. Ph.D. Thesis,
University of Southern California, Los Angeles.
[2] Inomata, K., Shinoda, K., Ohde, H., Tsunoda, K., Hana-
zono, G., Kimura, I., Yuzawa, M., Tsubota, K. and Mi-
yake, Y. (2007) Transcorneal electrical stimulation of ret-
ina to treat longstanding retinal artery occlusion. Graefes
Archive for Clinical and Experimental Ophthalmology,
245, 1773-1780.
[3] Schatz, A., Röck, T., Naycheva, L., Willmann, G., Wilhelm,
B., Peters, T., Bartz-Schmidt, K., Zrenner, E., Messias, A.
and Gekeler, F. (2011) Transcorneal electrical stimula-
tion for patients with retinitis pigmentosa—A prospective,
randomized, sham-controlled exploratory study. Investi-
gative Ophthalmology & Visual Science, 10, 6932
[4] Morimoto, T., Miyoshi, T., Sawai, H. and Fujikado, T.
(2010) Optimal parameters of transcorneal electrical stimu-
lation (TES) to be neuroprotective of axotomized RGCs
in adult rats. Experimental Eye Research, 90, 285e291.
[5] Usui, S., Kamiyama, Y., Ogura, T., Ishihara, A. and Hamada,
T. (1997) Physiological engineering model of the outer
retina. Proceedings of the International Conference on
Neural Networks, 4, 2309-2314.
[6] Hammond, C. (2001) Cellular and molecular neurobiol-
ogy. 2nd Edition, Academic Press, Paris.
[7] López-Miranda, M.J., Robles-Camarillo, D., Nino-de-
Rivera, L. and Quiroz-Mercado, H. (2010) Transcorneal
electrical stimulation in patients with retinitis pigmentosa.
Proceedings of the Annual Meeting 2010, Meeting Ab-
stracts, 51, 1356.
[8] Robles-Camarillo, D., Niño-de-Rivera, L., Quiroz-Merca-
do, H. and López-Miranda, M.J. (2006) Distributed reti-
nal response model based on adaptive system. Proceed-
ings of the BIOSIGNAL 2006, Brno, 352-354.
[9] Robles-Camarillo, D., Niño-de-Rivera, L., Quiroz-Mercado,
H. and López-Miranda, M.J. (2008) Waveform generator
system to transcorneal stimulation based on a digital
adaptive model. 5th International Conference on Electri-
cal Engineering, Computing Science and Automatic Con-
trol, 12-14 November 2008, 120-124.
[10] Robles-Camarillo, D., Niño-de-Rivera, L., Quiroz-Mercado,
H. and López-Miranda, M.J. (2009) Portable transcorneal
electrical stimulator system, applied on electrotherapy for
low vision patients. 52nd IEEE International Midwest Sym-
posium on Circuits and Systems, 2-5 August 2009, 1-4.
[11] Marmor, M., Fulton, A., Holder, G., Miyake, Y., Brigell,
M. and Bach, M. (2009) ISCEV Standard for full-field
clinical electroretinography (2008 update). Documenta
Ophthalmologica, 118, 69-77.
[12] Hood, D., Bach, M., Brigell, M., Keating, D., Kondo, M.,
Lyons, J., Marmor, M., McCulloch D. and Palmowski-
Wolfe A. (2011) ISCEV standard for clinical multifocal
electroretinography (mfERG) (2011 edition). Documenta
Ophthalmologica, 124, 1-13.
Copyright © 2013 SciRes. OPEN ACCESS