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Purpose: Eyemate is a system for the continual monitoring of intraocular pressure (IOP), comprised of an intraocular sensor, and a hand-held reader device. The eyemate-IO sensor is surgically implanted in the eye during cataract surgery. Once implanted, the sensor communicates telemetrically with the hand-held device to activate and record IOP measurements. The aim of this study was to assess the possible influence of electromagnetic radiation emitted by daily-use electronic devices on the eyemate IOP measurements. Methods: The eyemate-IO sensor was placed in a plastic bag, immersed in a sterile sodium chloride solution at 0.9% and placed in a water bath at 37 C. The antenna, connected to a laptop for recording the data, was positioned at a fixed distance of 1 cm from the sensor. Approximately two hours of quasi-continuous measurements was recorded for the baseline and for cordless phone, smart-phone and laptop. Repeated measures ANOVA was used to compare any possible differences between the baseline and the tested devices. Results: For baseline measurements, the sensor maintained a steady-state. The same behavior was observed with the devices measurements during active and inactive states. Conclusion: We found no evidence of signal drifts or fluctuations associated with the tested devices, thus showing a lack of electromagnetic interference with data transmission. Patients who already have the eyemate-IO sensor implanted, or those considering it, can be informed that the electromagnetic radiation emitted by their daily-use electronic devices does not interfere with IOP measurements made by the eyemate-IO sensor.
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Influence of electromagnetic radiation emitted by daily-use
electronic devices on the Eyemate® system
Azzurra Invernizzi1,2,*, Shereif Haykal1,2,*, Valeria Lo Faro1,*, Vincenzo Pennisi3, Lars Choritz3
1. Laboratory for Experimental Ophthalmology, University of Groningen, University
Medical Center Groningen, Groningen, the Netherlands
2. Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells &
Systems, University Medical Center Groningen, Groningen, the Netherlands
3. Department of Ophthalmology, Otto-von-Guericke University Magdeburg,
Magdeburg, Germany
* these authors contributed equally to this work
Correspondence:
Azzurra Invernizzi, Laboratory for Experimental Ophthalmology, University Medical Center
Groningen, P.O.Box 30.001, 9700 RB Groningen, Netherlands. Phone: +31 50 3612510; Fax:
+31 50 3611709; e-mail: a.invernizzi@umcg.nl
Lars Choritz, Department of Ophthalmology, Otto-von-Guericke University Magdeburg,
Magdeburg, Germany. Email: lars.choritz@med.ovgu.de
Running title: Influence of electromagnetic radiation on the Eyemate® system
Authors’ contributions:AI, SH, VLF, VP and LC conceptualized, designed the experimental
setup and collected the data. AI performed data analysis and visualization. AI, SH and VFL
wrote and finalised the manuscript. LC supervised the study and revised the final draft of
the manuscript. All authors read and approved the final manuscript.
.CC-BY-NC-ND 4.0 International licenseIt is made available under a
is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.was not peer-reviewed) (whichThe copyright holder for this preprint . http://dx.doi.org/10.1101/19011692doi: medRxiv preprint first posted online Nov. 20, 2019 ;
Acknowledgements:
We want to thank Jacqueline van den Bosch for her useful feedback on the experiment
design and Frans W. Cornelissen for his feedback on data analysis and support during the
writing process.
Funding: This project has received funding from the European Union’s Horizon 2020
research and innovation programme under the Marie Sklodowska-Curie grants agreement
No. 661883 (EGRET cofund) and No.675033 (EGRET plus). The funding organizations had no
role in the design, conduct, analysis, or publication of this research.
1
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is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.was not peer-reviewed) (whichThe copyright holder for this preprint . http://dx.doi.org/10.1101/19011692doi: medRxiv preprint first posted online Nov. 20, 2019 ;
Abstract
Purpose: Eyemate® is a system for the continual monitoring of intraocular pressure (IOP),
comprised of an intraocular sensor, and a hand-held reader device. The eyemate®-IO
sensor is surgically implanted in the eye during cataract surgery. Once implanted, the
sensor communicates telemetrically with the hand-held device to activate and record IOP
measurements. The aim of this study was to assess the possible influence of
electromagnetic radiation emitted by daily-use electronic devices on the eyemate® IOP
measurements.
Methods: The eyemate®-IO sensor was placed in a plastic bag, immersed in a sterile sodium
chloride solution at 0.9% and placed in a water bath at 37°C. The antenna, connected to a
laptop for recording the data, was positioned at a fixed distance of 1 cm from the sensor.
Approximately two hours of “quasi-continuous” measurements was recorded for the
baseline and for cordless phone, smart-phone and laptop. Repeated measures ANOVA was
used to compare any possible differences between the baseline and the tested devices.
Results: For baseline measurements, the sensor maintained a steady-state. The same
behavior was observed with the devices measurements during active and inactive states.
Conclusion: We found no evidence of signal drifts or fluctuations associated with the tested
devices, thus showing a lack of electromagnetic interference with data transmission.
Patients who already have the eyemate®-IO sensor implanted, or those considering it, can
be informed that the electromagnetic radiation emitted by their daily-use electronic
devices does not interfere with IOP measurements made by the eyemate®-IO sensor.
Keywords: Glaucoma, Intraocular pressure, eyemate® system, telemetry, electromagnetic
2
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radiation.
Background
Glaucoma is one of the leading causes of irreversible blindness worldwide, with a predicted
increase in prevalence as the world’s population continues to age.1 While the underlying
causes of glaucoma vary, the main controllable risk factor for all subtypes of glaucoma is
increased intraocular pressure (IOP).2 IOP is usually measured by a trained specialist in a
clinical setting during working hours. However, IOP exhibits both short and long-term
fluctuations throughout the day,3,4 which can easily be missed by acquiring static IOP
measurements at the clinic in the traditional manner. Although still controversial, some
studies have suggested that such fluctuations are an independent risk factor for the
development and progression of glaucoma.5,6 Therefore, monitoring IOP fluctuations could
potentially improve our understanding of glaucoma and how to best control it, and in turn
improve patient care.
Several approaches and devices have been proposed for the continuous monitoring of IOP
throughout the day.7 Currently, the only CE-certified device for continuously monitoring IOP
intraocularly is the eyemate® (Implandata Ophthalmic Products GmbH, Hannover,
Germany). The eyemate® system comprises a wireless pressure sensor and handheld device
(Mesograph). The sensor communicates with the Mesograph device telemetrically, both to
provide it with an energy source and to transfer IOP recordings made by the sensor.
Implantation of the sensor is usually performed during cataract surgery, where the sensor is
placed in the ciliary sulcus after capsular implantation of the intraocular lens. Once
implanted, the sensor is meant to remain in the patient’s eye indefinitely.11
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The eyemate® system enables glaucoma patients to measure their own IOP at any time
during the day without the need for a doctor’s visit. It also allows ophthalmologists to
produce IOP profiles for their patients throughout the day, enabling the detection of any
possible fluctuations. Given the novelty of the device, clinical studies of its long-term
outcome are still scarce. A study of the long-term safety of the implanted first-generation
sensor in 5 open-angle glaucoma patients over an average period of 37.5 months has
reported “good functionality and tolerability”.8 A more recent study of patients who
received the implant following Boston Keratoprosthesis surgery reported that the sensor
successfully detected postoperative IOP peaks and that measurements made by the sensor
showed satisfactory agreement with finger palpation.9
As the eyemate®-IO sensor communicates with the hand-held reader telemetrically, some
patients might fear that the electronic devices that they use on a daily basis might
somehow interfere with this communication, leading to unreliable measurements of IOP. In
this study, we address these concerns by investigating the effect of electromagnetic
radiation produced by everyday electronic devices on the measurements made by an
eyemate®-IO sensor.
Methods
Data acquisition
The latest generation of eyemate® wireless intraocular transducer sensor was used for
studying the influence of electromagnetic radiation on the IOP measurements. The sensor
was placed in a plastic bag, immersed in a sterile sodium chloride solution at 0.9% and
4
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placed inside a tissue bath reservoir (RES-01, Experimetria Ltd., Hungary) containing Milli
Q-water. A circulating water bath (CWB-02, Experimetria Ltd., Hungary) connected to the
tissue bath was used to maintain the temperature constant around 37°C in the system
(Figure 1, panel a).
An antenna, connected to the Mesograph device, which in turn was connected to a laptop
for recording the data, was positioned at a fixed distance of 1 cm from the sensor (Figure 1,
panel b). Approximately two hours (116 minutes) of “quasi-continuous” measurements
were recorded for the baseline and for each device at a sample rate of approximately 10
Hz.
To obtain the baseline measurements, any disturbing electromagnetic impulses were
eliminated. All plugs were removed from the sockets in the test room, no lights were
switched on, no telephones (fixed line, cordless, or smart- phone). Only the data acquisition
computer and the water pump, placed at 2 m from the experimental setup, were left in the
room. The duration of the data acquisition was based on the maximal storing capacity of
the readout file (64 KB limit).
Figure 1 - Experimental setup. Panel ashows an overview of the setup, including the tissue-bath reservoir,
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and the Mesograph reader for recording measurements. Panel bshows a closer look at the eyemate®-IO
sensor and the fixed antenna.
In order to have comparable measurements for testing the influence of each electronic
device, the same environment was recreated: the plugs were removed from the socket, no
lights were switched on and only the data acquisition computer and the water pump were
left in the room.
For each device, the experiment was divided into four different measurement intervals: the
initial twenty-five minutes were used as “baseline” (named no device to avoid confusion);
after this time, each single device - smartphone (Huawei P10 Lite), cordless phone (Philips
CD180) and laptop (ASUS ZenBook UX410) - was positioned next to the sensor in
inactive-mode. For the smartphone and laptop the inactive mode meant to set the device
in flight mode while for the cordless phone it meant putting it in stand-by (no call). The
measurements in inactive mode were made for twenty-five minutes, after which the device
was switched to active mode for the following twenty-five minutes. This consisted of an
active call for the smartphone and the cordless phone and active Wi-Fi and video streaming
for the laptop. The final measurement period consisted of a no device recording for the
remaining forty-one minutes.
Data analysis
In order to compare the baseline data with data acquired with different devices, the
baseline timeline was divided into four sub-phases corresponding to the four measurement
intervals (no device, device inactive, device active and no device) acquired for the devices.
Absolute pressure values, which represent the raw output data from the sensor used to
obtain the final IOP measurement, were used to evaluate possible IOP fluctuation. A
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polynomial fitting of degree 9th, that takes into account environment pressure and
temperature, was applied to the acquired raw data (Figure 2, panel:a). Fitted data was
binned by averaging of ten samples per second (Figure 2, panel: b). Using the binned data,
we computed the mean, the maximum and minimum values for each measurement
period/interval of baseline and devices data. The range of fluctuations for each of the four
time-events was then determined by calculating the difference between the maximum and
the minimum values per data-bin, then by averaging the max and min values for each
event. Repeated measures ANOVA with Greenhouse-Geisser correction using SPSS version
25.0 (SPSS Inc., Chicag, Illinois, USA) was used to statistically compare any possible
differences between the baseline and the tested devices to investigate the influence of
daily use devices on the sensor recording.
Results
For baseline measurements, the sensor maintained a steady level for the duration of the
experiment, resulting in a flat profile with no apparent drift. The same behaviour was
observed with the device measurements during active and inactive states.
Small drops in signal measurements were observed corresponding to the time points where
each device was handled in the experimental setup (Figure 2, panel: b, drops in different
time-events are indicated with arrows).
Similar pattern of distributions and range of fluctuations were observed for both baseline
and devices in all four time-events (Figure 3 and Table 1). No statistically significant
difference (p-value = 0.332) was found between the average fluctuation for each
time-events of the baseline and the tested devices.
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Figure 2 - “Quasi-continuous ” data recorded for a device. We show an example of the data recorded for one
of the three tested devices, namely the smartphone. Panel a: fitted data over time; panel b: fitted and
downsampled absolute pressure data over time. Arrows indicate drop in the signal measurements.
Figure 3 - Absolute pressure distributions during the four time-events. A kernel density function was applied
to the data for plotting purpose. Mean and median of each distribution are indicated with black solid line and
red dotted line, respectively.
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Table 1 - Illustration of absolute pressure range fluctuations during the four time-events. For each
time-events, for each device we show the averaged absolute pressure fluctuations calculated based on the
range definition.
Discussion
The eyemate® is a system capable of continuously monitoring IOP intraocularly. The
eyemate®-IO sensor is designed to be implanted in the patient’s eye during cataract surgery
in order to transmit IOP measurements telemetrically.10-11 Because this sensor is constantly
sending and receiving electromagnetic signals, patients might fear that their daily use
electronic devices may be a source of interference in the IOP measurements. To date, the
number of studies investigating this promising new technology and its potential limitations,
such as electromagnetic interference, is still lacking.12-13-14
Here, we investigated the interference of electromagnetic radiation emitted by three
daily-use electronic devices (a cordless phone, a smartphone and a laptop) on the
measurements made by the eyemate® system. We found no evidence of signal drifts or
fluctuations associated with the tested devices, indicating a lack of interference of the
electromagnetic radiation emitted by the devices on the telemetric transmission of data
between the sensor and the antenna of the eyemate® system.
However, abrupt signal drops were revealed in the measurement profiles of the three
devices, which corresponded with the time points when each device was handled in the
9
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experimental setup. These signal drops are most likely unrelated to electromagnetic
interference with the readings, but probably due to an abrupt change to the surrounding
magnetic field following the repositioning of the tested device close to the sensor. No
reduction in the number of samples recorded was present.
A similar study has been previously conducted using the Triggerfish® contact lens sensor
(SENSIMED AG, Lausanne, Switzerland) with the same purpose of identifying the influence
of electromagnetic radiation on the continuous measurement of the eye pressure by the
sensor.12-13 The study assessed possible signal drift, noise and fluctuations in IOP
measurements recorded by the contact lens sensor due to possible electromagnetic
interference from similar daily-use devices. No drift or signal fluctuation was reported.
The Triggerfish® device measures small changes in ocular circumference at the
corneal-scleral junction corresponding to changes in intraocular pressure, volume and
ocular biomechanical properties as well. Although the Triggerfish® contact lens sensor is
placed superficially on the cornea and the eyemate®-IO sensor is placed intraocularly, both
sensors share a similar method of telemetric communication with an external antenna for
IOP monitoring. Therefore, our current results are in line with those reported for the
Triggerfish®.13
Limitations
An intrinsic limitation of the study is the limited data storage capacity of the reading out
system. This restricted our ability to test signal drift and fluctuation over a longer period of
time, as was done with similar IOP recording system.13 Another possible limitation is the
restricted number of devices tested. Future studies may consider including other devices
10
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which are becoming more commonly used, e.g. bluetooth headphones, WiFi connected
camera.
Conclusions
Measurements made by the eyemate® system showed no apparent signal drift or evidence
of being influenced by external electromagnetic radiation produced by the devices that we
tested. Patients who already have the eyemate®-IO sensor implanted, and those who are
considering to have one, should be informed that the electromagnetic radiation emitted by
their daily-use electronic devices does not interfere with IOP measurements made by the
eyemate® system.
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In this review, we distinguish among risk factors associated with the development of open-angle glaucoma in individuals with healthy eyes, predictive determinants for the development of open-angle glaucoma in subjects with ocular hypertension, and prognostic factors for the progression of open-angle glaucoma in individuals who already have the disease. We primarily reviewed recent longitudinal population-based epidemiological studies, prospectively planned clinical trials, and cohort studies. Risk factors consistently associated with the development of open-angle glaucoma in individuals with healthy eyes include older age and an approximately 1 mm Hg increase in intraocular pressure (IOP) at baseline. Family history for open-angle glaucoma may be associated with the development of open-angle glaucoma as well. Predictive factors for the development of open-angle glaucoma in individuals with ocular hypertension may be older age, thinner central corneal thickness, higher cup-to-disk ratios of the optic disc, and higher pattern standard deviation values on the Humphrey automated perimeter at baseline. Given multi-center trials that showed similar predictive factors for the development of open-angle glaucoma in individuals with ocular hypertension, a calculator is available to clinicians for assessing the 5-year likelihood of developing open-angle glaucoma in ocular hypertensive patients with certain characteristics. Prognostic factors for the progression of open-angle glaucoma in individuals who already have the condition include older age at baseline, higher IOP at baseline, and thinner central conreal thickness. Self-report of diabetes may be associated with open-angle glaucoma progression. In conclusion, the only modifiable factor associated with open-angle glaucoma that has been consistently identified is elevated baseline IOP. Future research needs to evaluate the importance of others modifiable factors such as IOP fluctuation or nutritional factors.
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Purpose: To analyze the dynamics of telemetrically measured intraocular pressure (IOP) during the first year after implantation of a Boston keratoprosthesis type I (BI-KPro) cornea and to compare agreement of telemetric IOP measurements with finger palpations. Design: Prospective, open-label, multicenter, single-arm clinical trial. Methods: In the ARGOS (NCT02945176) study, 12 individuals underwent implantation of an Eyemate-IO intraocular system. Follow-up after surgery took place 12 months later with 13 visits planned per patient. During BI-KPro surgery, an electromagnetic induction sensor ring enabling telemetric IOP data transfer to a hand-held reading device outside the eye was implanted into the ciliary sulcus with or without trans-scleral suture fixation. Comprehensive ophthalmic examinations and IOP assessments through the telemetric system were compared to IOP assessed by finger palpation by 2 experts. Results: Preoperative IOP measured by Goldmann tonometry was 13.4 ± 6.2 mm Hg. Telemetric IOP peaked at 23.1 ± 16.5 mm Hg at the first postoperative day. On day 5, mean IOP was 16.0 ± 5.2 mm Hg and 20.95 ± 6.5 mm Hg after 6-12 months. IOP estimation by finger palpation was grouped in 4 categories: normal, A; soft/hypotonic, B; borderline, C; and hypertonic, D. Mean telemetric IOP was 18.2 ± 6.1 mm Hg in category A, 8.9 ± 2.8 mm Hg in B, 22.4 ± 4.9 mm Hg in C, and 34.3 ± 11.0 mm Hg in D. Differences in mean telemetric IOPs per category were statistically significant (P < .001). Daily IOP fluctuations and peaks could be identified. Conclusions: Telemetric IOP assessment seems to be able to identify postoperative IOP peaks and a longitudinal increase of IOP after BI-KPro surgery. IOP measurements using the telemetric Eyemate-IO sensor showed a satisfactory agreement with those of finger palpations by 2 experts.
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Importance: To investigate the long-term safety of a novel intraocular telemetric pressure sensor. Background: Acquisition of accurate intraocular pressure (IOP) data is vital for sufficient medical care of glaucoma patients. Non-invasive self-tonometry with a telemetric IOP sensor can provide important information regarding the individual IOP profile. Design: Retrospective analysis of long-term follow-up data assessed during outpatient visits in a university hospital. Participants: 6 patients with open-angle glaucoma were included. Unfortunately, 1 patient passed away shortly after completion of the original 1-year study. Methods: Within the scope of a prospective 1-year pilot clinical trial, a telemetric IOP sensor was inserted into the ciliary sulcus after intracapsular lens implantation during planned cataract surgery. Patients were regularly examined as outpatients even beyond the duration of the 1-year study. Data concerning sensor functionality, safety parameters, and home self-tonometry were assessed. Main outcome measures: Long-term sensor functionality and safety. Results: Sensor measurements were always successful in every patient. Additionally, home self-tonometry was conducted without any problems by every patient. The average follow-up period was 37.5 months (21-50 months). During this period, the average number of IOP measurements performed per patient was 1273 (223-2884 measurements). No severe adverse events were reported. A varying degree of pupillary distortion was observed after 6-12 months in every patient; this remained unchanged thereafter with only one exception. Conclusions and relevance: Telemetric IOP sensors showed good functionality and tolerability during long-term follow-up. Non-invasive self-tonometry with a telemetric IOP sensor can provide useful additional data for future monitoring of patients with glaucoma.
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Glaucoma is a common optic neuropathy that can lead to irreversible vision loss, and intraocular pressure (IOP) is the only known modifiable risk factor. The primary method of treating glaucoma involves lowering IOP using medications, laser and/or invasive surgery. Currently, we rely on in-office measurements of IOP to assess diurnal variation and to define successful management of disease. These measurements only convey a fraction of a patient’s circadian IOP pattern and may frequently miss peak IOP levels. There is an unmet need for a reliable and accurate device for 24-h IOP monitoring. The 24-h IOP monitoring devices that are currently available and in development fall into three main categories: self-monitoring, temporary continuous monitoring, and permanent continuous monitoring. This article is a systematic review of current and future technologies for measuring IOP over a 24-h period.
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While mean intraocular pressure (IOP) has long been known to correlate with glaucomatous damage, the role of IOP fluctuation is less clearly defined. There is extensive evidence in the literature for and against the value of short-term and long-term IOP fluctuation in the evaluation and prognosis of patients with glaucoma. We present here the arguments made by both sides, as well as a discussion of the pitfalls of prior research and potential directions for future studies. Until a reliable method is developed that allows for constant IOP monitoring, many variables will continue to hinder us from drawing adequate conclusions regarding the significance of IOP variation.