Transdermal Optical Communications

Abstract — This work presents a modelling approach

suitable for transdermal optical channel characterization.

Transdermal optical channels concern the communication

links between body implantable medical devices (IMDs)

and external optical communication devices, which imposes

several challenging design considerations concerning signal

degradation. The achieved results show that, signal

degradation effects due to skin depth can be adequately

modelled following the proposed approach.

Keywords—Optical Wireless Communications, Transdermal

Channels, Implantable Medical Devices.

I. INTRODUCTION

In the past few decades we have witnessed an increase of the

population life expectancy, as well as the prevalence of

illnesses requiring a close monitoring by means of implantable

medical devices (IMD), improving the patient’s quality of life

and contributing to sustain their lives.

Since the development of the first implantable pacemaker, in

1958, the field of biomedical engineering has seen phenomenal

technological achievements [1]. These achievements have

resulted in smaller, safer, more complex and smarter IMDs.

Currently, millions of people worldwide rely on implantable

medical devices, and such devices with external RF

communications are already being used for a wide variety of

applications, including temperature monitors, pacemakers,

defibrillators, functional electrical stimulators (FES), blood

glucose sensors, cochlear implants and retina [2]. Nowadays,

IMDs offer the possibility to perform real-time monitoring of

several functions of the human body, helping in the diagnosis

and treatment of illnesses and disorders. However, to perform

this function, they require complex electronics systems with

ability to process the collected information and also to

communicate with an external device.

Thus, the wireless modality for access and remote control of

IMD is an increasingly requirement. Many limitations of current

IMDs with wireless communication functions, come from their

RF connections. Three of the most challenging aspects in

modern IMDs are: 1) electromagnetic interference (EMI); 2)

security & privacy; and 3) powering considerations [3]. The first

two are related with the fact that IMDs usually communicate

with the external interfaces by means of inductive or RF

connections. Therefore, they are subject to interference from

another electronic equipment, such as cell phones, or they may

be a target of third parties unauthorized access [3, 4].

Additionally, patients may not even be allowed to perform some

medical exams, such as MRI (magnetic resonance imaging) [6].

In order to mitigate these problems, optical signals emerged as a

viable alternative for wireless data transmissions with IMDs [2,

7]. Its main advantages are: i) radiation spectrum not

regularized; ii) high data rates (transdermal optical connections

at 50 Mbps, were reported [8]); iii) no radiation hazards; iv)

electromagnetic interference (EMI) immunity; v) Security

issues; vi) maturity of optoelectronic devices.

Regarding the powering issue, the most used methods are

based on rechargeable batteries, charged by induction and RF

harvesting. Alternatively, optical signals have recently gained

attention as an energy harvesting method, suitable for IMDs

since it mitigates EMI issues [9,10].

II. STATE OF ART

In the beginning of 90s, studies started on some applications

of optical links through the skin with data rates up to 1 Mbps,

such as neuromuscular stimulators [11], artificial hearts and

implanted cardiac assist devices [12], stimulating bladder [13]

and laboratory animal monitoring system [14].

In 1999, work reported in [15] illustrates the start of turning

attention to the benefits of wireless optical communications for

transdermal connections aiming biomedical applications. In this

work a prototype telemeter that recorded one channel of high-

frequency extracellular neuroelectric signals was constructed

and implanted in a rabbit. A transmitter based on a LED was

used, where the 880 nm wavelength was chosen as the one with

most efficient transmission through the skin. The receiver was

based on a four-diode GaAlAs panel. The system was designed

for a 8-channel connection at 15 kHz/channel and the integrated

circuits consumed 12.5 μA current for signal amplification,

encoding, and multiplexing and used another 7 μA for the optical

output.

In 2004, [2] reports an important contribution to the optical

communications in IMDs applications. In this work transdermal

tests was conducted with samples of pork skin, where it was

performed a connection at 115.2 kbps for several skin samples

with a LED transmitter at 860 nm and a PIN photodiode at the

receiver.

In 2005, [16] shows a development of a bidirectional

transcutaneous optical data transmission system that promises

adequate performance for monitoring and control of an artificial

heart. Two narrow directional visible LEDs with a peak

emission wavelength of 590nm were used to transmit data from

inside the body to outside the body. The transmission from

outside the body to inside the body was performed by a narrow

Manuel Faria

Dept. Eng. Eletrotécnica e de Computadores do Instituto Superior Técnico,

Universidade de Lisboa, Lisboa, Portugal. (manuel.faria@tecnico.ulisboa.pt)

directional near-infrared LED with a peak emission wavelength

of 940 nm. The ASK modulator employs a carrier pulse signal

(50 kHz) to support a maximum data transmission rate of

9600 bps. An in vitro experiment showed that the maximum

tissue thickness of near-infrared optical data transmission

without error was 45 mm. Electric power consumption for the

data transmission links was 122 mW, for near-infrared light and

162mW for visible light.

In 2007, an optical transdermal connection performed a data

communication at 40 Mbps, from an implanted device to a

receiver outside the body, through a skin sample with 3 mm

thickness [18]. The average power consumption recorded was

4.3 mW for the transmitter module.

In 2008, the innovation proposed for optical transdermal

systems already implemented was the use of an LD (laser diode)

[19]. There, a transmitter based on a VCSEL laser diode in the

infrared region, at 850 nm, with a Manchester code encoding,

was used to test an optical telemetry systems through pork skin

samples with different thicknesses. It was proved a system

transmitting at data rates up to 16 Mbps, through a skin thickness

of 4 mm while achieving a bit error rate (BER) of 10-9, with

consumption of 10 mW or less.

The concern with the energy consumption by the implanted

device is evident in [7], where it was proposed a retroreflector

inside the body, to minimize the energy consumption from the

implanted device. This work, in 2012, presents a mathematical

model and experimental results from measurements of direct and

retroreflection link configurations with Gallus derma as the

transdermal channel. An optical window for transdermal

communications was found around 800 and 940 nm wavelength

for both configurations. A numerical analyzes shows that

transmitter power consumptions of 0.4 μW and 4 mW for the

direct and retroreflective links, respectively. It is possible to

achieve a BER of 10-6.

Also in 2012, it was presented a relevant work in the optical

transcutaneous telemetry field [8]. In this work, it was designed

an optical transcutaneous link capable of transmitting data at 50

Mbps through a 4 mm pork tissue, with a BER less than 10-5,

and a power consumption at most of 4.1 mW or less. The main

innovation is the use of a VCSEL driver for the transmitter,

using a modified on-off keying for the modulation scheme,

which allows less power consumption.

Table I, summarizes the state of art just referred.

III. TRANSDERMAL MODEL

A. Channel Modeling

In order to model the transdermal channel three important

factors were considered: the transmittance of the skin, the

misalignment between transmitter and receiver and the

background light noise.

1) Skin Transmissivity

Skin is a complex biological structure composed by a three

essential layers: stratum corneum, epidermis and dermis (Fig.

1). All of these layers have different characteristics that make

the optical behavior different from each other. Furthermore,

human skin is ethnically different, diverse in topology,

penetrated by hair and sweat ducts, which makes this a complex,

dynamic and variable optical medium. Thus, a rigorous

characterization of skin optical properties is an extremely

challengeable task, definable only in the context of an

approximate approach. There are two main effects to take into

account to modulate the skin optics: scattering and absorption. It

Fig. 1. Schematic diagram of optical pathways in skin. (Adapted from

[17])

TABLE I - STATE OF ART OF TRANSDERMAL OPTICAL COMMUNICATIONS

Reference Consumed

power (mW) Data rate Transmitter Receiver

Wavelength

(nm)

Skin thickness

(mm)

Skin

sample

type

BER

[15] - - LED 4 PIN

GaAIAs 880 - rabbit <10-6

[2] - 115.2 kbps LED PIN Si 860 6.9 pork

[16] 122.0 162.0

9600 bps LED PIN Si 940 590

45.0 20.0

pork 0

[18] 4.3 40 Mbps VCSEL PIN GaAs 850 3.0 pork <10-5

[19]

~7.5

~12.5 ~10.3

~16.0

16 Mbps VCSEL PIN Si 850

2.0

2.0 4.0

4.0

pork <10-9

[7] 0.4 x 10-3 - LED PIN Si 790 1.0 rooster <10-6

[8] 2.6 4.1

6.4

50 Mbps VCSEL PIN Si 850 2.0 4.0

6.0

pork <10-5

is important to find a simple metric that join all of this complex

information and summarize it into a parameter to put in the

model – the transmittance of the skin. This is the most

challenging factor of this channel, different from the usual ones

used in OWC (optical wireless communications) [9].

The transmittance of the skin is defined as the ratio of optical

power that passes through the skin, against the incident one. This

parameter is wavelength dependent and account the effects of

absorption, reflection and scattering. In [17], it is presented a

dermis transmittance model as function of the wavelength, for a

predefined skin thickness. This work, considers that the dermis

layer is the only one with an important role on the skin

transmittance, as previously proposed [17]. In fact, it was

demonstrated that most of visible and near infrared radiation is

transmitted through epidermis and stratum corneum layers, with

negligible impairments [17].

In order to extend this model to several dermal thicknesses,

it is necessary to consider the skin attenuation coefficient, α, in

m-1 [20]:

𝑇 = 𝑒−𝛼𝛿 , (1)

where T is the transmittance of the dermis and δ correspond to

the total dermis thickness. Hence, from the data reported in [17],

it is possible to obtain the total description of the attenuation

coefficient, showed in Fig. 2, which is coherent with the

reported in [21].

2) Misalignment

The directional property of the transmitted beam may be a

drawback in terms of additional attenuation, and it is expected

that a part of the optical beam power is not received in the

photodetector area. There are three types of misalignment,

which influence the power losses in the receiver: longitudinal,

lateral and angular. As in transmittance, it is then necessary to

define a single factor that summarizes the problem of three types

of misalignment – the misalignment factor, D. This factor means

the power reduction fraction, between 0 and 1, resulting for the

contribution of each type of misalignment.

To model the losses due to misalignment, it is important to

characterize the radial dependence of the transmitted optical

beam. Therefore, the optical power distribution in the beam must

be known. The model used for the radiation pattern of the

transmitter was based on a Gaussian distribution [22]:

𝐼(𝜌, 𝑧) = 𝐼0(𝑧) exp [−2𝜌2

𝑤2(𝑧)], (2)

where 𝐼0 is the maximum optical intensity on the radial direction

𝑧, 𝜌 = 𝑥2 + 𝑦2 is the radial distance and 𝑤(𝑧) is the radius of

the optical beam.

The longitudinal misalignment, also known as beam

divergence, comes from the optical beam diffraction from the

emitting source. This divergence can significantly reduce the

optical power received at the photodiode, since the effective area

of the photodiode may be less than the total projection area

illuminated by the beam. Following the radiation Gaussian

model previously mentioned, the total power transmitted by the

optical beam, considering a circularly symmetric distribution of

radiation intensity, is given by [23]:

𝑃𝑡𝑜𝑡(𝑧) = 𝐼(0, 𝑧)𝜋

2𝑤2(𝑧), (3)

wherein the optical beam radius 𝑤(𝑧) can be calculated by the

distance between transmitter and receiver, 𝑑, and divergence

angle, 𝜃𝑑𝑖𝑣, of the transmitter is:

𝑤 = 𝑑 tan (𝜃𝑑𝑖𝑣

2). (4)

Thus, considering a perfect alignment between transmitter and

receiver axes, the power at the photodetector plan is defined as

[23]:

𝑃𝑅𝑥(𝑧) = 𝑃𝑡𝑜𝑡(𝑧) {1 − exp [−2𝑟𝑅𝑥

2

𝑤2(𝑧)]}, (5)

where 𝑟𝑅𝑥 is the radius of the active area of the photodiode. Thus,

this factor represents another cut in the emitted power which can

be significant, whenever the illuminated area is considerably

larger than the effective area of the photodetector. However,

note that if the divergence angle of the optical transmitter is too

small, i.e., the optical area of the beam is much close to the

effective area of the emitted beam, a great accuracy to align the

optical source and the detector is required. So there is a tradeoff

between the transmitter divergence angle (and its distance to the

skin) and the power loss due to difference between beam and

photodetector areas, because of the alignment precision

challenges mentioned.

Lateral misalignment occurs when the transmission direction

axis is not fully aligned with the normal axis of the receiver

effective area. The detected optical power depending on the

lateral shift, Δ, of the lateral misalignment is given by [24]:

𝑃𝑅𝐸𝐶(Δ, 𝑧)

= √𝜋

2𝑤(𝑧)𝐼(0, 𝑧)

∙ ∫ {exp [−2𝑥2

𝑤2(𝑧)] erf [

√2

𝑤(𝑧)(Δ + √𝑟𝑅𝑥

2 − 𝑥2)]

𝑟𝑅𝑥

0

− exp [−2𝑥2

𝑤2(𝑧)] erf [

√2

𝑤(𝑧)(Δ − √𝑟𝑅𝑥

2 − 𝑥2)]} 𝑑𝑥.

(6)

Fig. 2. Attenuation coefficient of human dermis as function of wavelength

(based on [17])

In turn, the angular misalignment factor is the power loss due to

the angle α between the transmitted beam axis and the axis of

the receiving plane normal. This case can be approximated to an

adaption of lateral misalignment, since the misalignment angle

α causes a lateral shift in the receiving plane. Thus, the

expression of the received power is the same as (6), with the

lateral shift given by:

Δ𝑅𝑥 = 𝑑 tan(𝛼). (7)

3) Background Noise

The environmental light sources, with emission spectra

overlapping the received data optical signal are another

disturbing factor to the communication. The main sources of

ambient light are the sunlight and the artificial light sources

(e.g. incandescent lamps, fluorescent lamps and LED based

bulbs). Sunlight is the main source of external noise, since it is

the higher intensity source [25]. However it is also important to

study the influence of the typical indoor artificial lighting. This

work, considers a white LED artificial lighting. Due to

developments in the technology of LEDs, the trend indicates

that this will be the main source of lighting in the future, due to

its low power consumption, high efficiency and long lifetime

[26]. For that reason, it was decided to simulate indoor scenario

for a white LED illumination. Moreover, visible light

communications with white LEDs systems is a growing field of

investigation [27, 28]. It was also studied the system imbued in

a total darkness environment.

a) Solar light

To affect the data signal emitted, the solar radiation must

pass the skin barrier, achieve the photodetector effective area,

𝐴𝑒𝑓, and then is converted to electric domain. Thus, the total

current produced by the solar illumination that affects the

receiver is given by:

𝐼𝑠𝑢𝑛 = 𝐴𝑒𝑓 ∫ 𝑊(𝜆)𝑇(𝜆)𝑅(𝜆) 𝑑𝜆, (8)

where 𝑊(𝜆) is the spectral radiant emittance (in W/m2.nm),

𝑇(𝜆) is the transmittance of the skin and 𝑅(𝜆) is the

photodetector responsivity. The model used for the spectral

radiant emittance of the sun was ASTM G173-03, for “Global

Tilt” conditions.

b) Darkness

This is the most favorable case to perform the transmission,

where it is considered a null background light. However, this is

also the case with the lower current levels, because there are no

extra energy coming from the environment. To understand how

much the results are disturbed for the other environment

conditions, this is an important case, since it is the ideal scenario

to perform communication.

c) White LED light

A common way to achieve white light employs a scheme

similar to fluorescent lamps, performing blue wavelength up

conversion with a yellow phosphorous coating. Power LEDs

normally employ this method, due to its simplicity and also

because it translates into cost effective devices. A simple

approach to model the spectral power distribution of white

LEDs is to use Gaussian distributions centered on the device

response maxima [17]. Following this approach, with two peak

wavelengths on blue (~460 nm) and yellow (~550 nm), the

white LED’s spectral power distribution (SPD) can be

approximated by [28]:

𝑆(𝜆) =1

√2𝜋(𝑤1

1

𝜎1

𝑒𝑥𝑝 [− (𝜆 − 𝜆1

√2𝜎1

)

2

] + (1

− 𝑤1)1

𝜎2

𝑒𝑥𝑝 [− (𝜆 − 𝜆2

√2𝜎2

)

2

]),

(9)

where λ1 and λ2 correspond to blue and yellow wavelength

peaks, respectively, while 𝑤1 is a weighting factor describing

the additive proportions of each peak wavelength. Variables σ1

and σ2 represent the power spreading around each respective

peak wavelength. The simulated SPD resembles the real white

LED one, where its power level was calibrated to obtain a

correspondent total typical illuminance of a representative

room, which is around 500 lux [29]. Afterwards, the procedure

to acquire the value of the electric current generated by the

background optical signal was similar to solar light method.

B. Transmitter

The model of the transmitter is composed by a random bit

generator of a non-return to zero (NRZ) bit scheme with a rate

of 1 Mbps. The transmitter model also includes a gain block

representing the conversion of the electrical signal to the optical

domain and a Bessel filter to reproduce the bandwidth

limitation of the optical source. It was considered a low-

frequency noise represented by a Gaussian noise source with a

variance given in [30]. The optical signal extinction ratio

limitation was also taken into account (8 dB).

C. Receiver

The model of the receiver considers the responsivity and all

the typical impairment sources: thermal noise, electric shot

noise, dark current, as well as bandwidth limitations. The

thermal noise is caused by thermal fluctuations of the electric

carriers in the receiver circuit, with an equivalent resistance, RL,

and at temperature, T. This type of noise can be modeled by a

white Gaussian noise, whit a variance given by [31]:

𝜎𝑡ℎ2 =

4𝑘𝐵𝑇

𝑅𝐿

𝐹𝑛, (10)

kB is the Boltzmann constant and Fn is the figure of merit. In fact,

the expression used in the model is a simplification of the

previous one, easier to apply with the datasheet parameters of

the components:

𝜎𝑡ℎ

2 = 𝑁𝐸𝑃2𝑅2𝐵. (11)

The shot noise is a manifestation of the fact that the electric

current is a stream of electrons that are generated randomly. This

current fluctuation can be mathematically described by a

stationary Poisson random process, which can be approximated

by a Gaussian process. The shot noise variance is given by [31]:

𝜎𝑠2 = 2𝑞𝐵(𝐼 + 𝐼𝑑𝑎𝑟𝑘), (12)

where 𝐼𝑑𝑎𝑟𝑘 is dark current which is the current generated by the

photodetector in the absence of any optical signal and comes

from electron-hole pairs thermally generated.

The responsivity is modeled by a gain, wavelength

dependent, in A/W.

The receiver bandwidth limitations, were modeled with a

Bessel filter, that in addition to simulate the bandwidth limit of

the receiver, cut part of the noise present in the signal.

D. MATLAB Implementation

The model was implemented using the SIMULINK toolbox

of MATLAB. The simulator built aims to model the behavior of

a transdermal communication in which the transmitter is outside

the body and the receiver inside, immediately after the skin

barrier. Fig. 3 shows a scheme of the simulator implemented

main modules.

1) Analysis Tools

The purpose of the simulation was to determine the data

signal quality at the reception and its current level. Then, the

used tools aim to generate data indicators of quality: 1) Eye

diagram; 2) Q factor of the eye diagram; 3) Average current

amplitude value. The Q factor of the eye diagram, as also known

as eye signal-to-noise ratio (Eye SNR), is defined as the ratio of

the eye amplitude to the sum of the standard deviations of the

two binary levels:

𝐸𝑦𝑒 𝑆𝑁𝑅 =𝜇1−𝜇0

𝜎1+𝜎0

, (13)

where μ1 and μ0 represent eye level 1 and 0 average amplitudes,

respectively, and σ1 and σ2 are the standard deviation of eye level

1 and 0 average amplitudes, respectively. For both indicators

(eye diagram and Eye SNR) the eyediagram.comscope tool, from

MATLAB’s Communications System Toolbox, was used.

Finally, to measure the average current amplitude of the

output signal a simple mean function of all the signal samples

was made.

2) Simulation Parameteres

The model was simulated to a spectral range from 400 to

1700 nm through a range of skin thicknesses from 0 to 4 mm.

For the transmitter a LED was selected due its low energy

consumption and its low cost, which are care factors for

commercial IMDs. The considered average emission optical

power was 3 mW with a beam divergence angle of 60º. This high

value for the divergence angle allows us to mitigate the

alignment precision difficulties with the receiver. It was also

considered a distance of 1 cm, between the receiver and the

transmitter. The beam divergence was considered constant,

since the distance between the emitter and the skin was invariant

(1 cm) and skin thickness impact is negligible in the beam

divergence. Lateral and angular misalignments were considered

nulls in this simulation.

Due to the wide spectral range of analysis, two type of PIN

photodiodes were selected – Si and InGaAs, for 400 to 1000 nm

and 1050 to 1700 nm, respectively.

Table II shows the main parameters used in the simulation

based on selected components, according to the descripted

concerns.

The simulation was performed for a transmission time of 0.1

in order to generate 100 000 bit, with 100 samples per bit.

TABLE II - SIMULATION PARAMETERS

Component Parameter Symbol Value

Transmitter:

LED

Bit rate Db 1 Mbps

Emitted optical power pemi 3 mW

Wavelength λ 400 - 1550 nm

Beam divergence angle θdiv 60o

Channel:

Skin

Skin thickness δ 0 - 4 mm

Distance transmitter-skin d 1 cm

Receiver 1:

Si PIN

Bandwidth B 30 MHz

Effective area Aef 1.1 mm2

Noise Equivalent Power NEP 6.7 x 10-15 W/Hz1/2

Dark current Idark 0.05 nA

Receiver 2:

InGaAs PIN

Bandwidth B 18 MHz

Effective area Aef 0.92 mm2

Noise Equivalent Power NEP 5 x 10-15 W/Hz1/2

Dark current Idark 0.07 A

Fig. 3. Scheme of the implemented SIMULINK model

IV. SIMULATION RESULTS

A. Signal Quality

As already mentioned, the main factors affecting the signal

are skin thickness, wavelength, background noise and

misalignment.

The eye diagram analysis was one of the indicators chosen

to study the signal degradation. The received signal after being

converted into the electrical domain, is decoupled into two

components - AC (information component) and DC (energy

component). In Fig. 4, is represented two different eye diagrams

with normalized amplitudes for each degradation effect, for the

AC component of the signal. As it is possible to observe in Fig.

4a, for the visible spectral range, the eye diagram quality is

increasing with the wavelength, assuming a constant skin

thickness, as it was predicted by the attenuation coefficient

evolution (Fig. 2). Regarding skin thickness for the same

wavelength, there is a further degradation, larger the skin

thickness, since more tissue corresponds higher signal

attenuation (Fig. 4b). Finally, in Fig.4c, the extreme

environments solar light and total darkness are compared for the

same skin thickness and emission wavelength. This figure shows

that in presence of sunlight the signal undergoes a much greater

degradation than in a place without any illumination. This

behavior is explained by the background current generated by

solar light that substantially increases the amplitude of the data

signal stream that arrives at the receiver. Consequently, it

increases the shot noise, since its variance is current dependent,

as previously demonstrated. These results confirm that

communication is favorable in a scenario without any external

illumination source, where it is possible to achieve higher skin

tissues limits for a certain degradation level of the optical signal.

Eye diagram only provides a visual indication of

degradation, so it is important to have a quantitative metric of

signal quality. Thus, it was made the study of the quality factor,

Q, which is presented in Fig. 5.

As can be seen in Fig. 5, the quality factor varies on the

spectrum depending on the attenuation coefficient of the skin

(Fig. 2). This demonstrates that the quality factor varies

according to the spectral transmittance of the skin for each

emission wavelength. It was also confirmed that the quality

factor of the signal decreases with the skin thickness, whatever

it is the emission wavelength and the illumination environment.

Regarding the results in different illumination environments,

the highest gap is registered for the solar illumination scenario,

in which there is a general decrease of the quality factor

compared with the other two. Therefore, it is confirmed that the

current produced by the solar lighting will cause a decrease in

the quality of the data signal. Moreover, the illumination

obtained by the white LED(s) (500 lux) can be compared to the

total darkness environment, where there are not no significant

differences in the data obtained for the quality factor in these two

environments. This can mean an advantage in terms of

communication, taking into account that a transdermal optical

indoor link, with a typical lighting (500 lux) will not affect

significantly the communication.

From the mentioned results, it is concluded that the optimum

wavelengths lie in region between 1100 and 1300 nm. Data from

the simulation indicates the wavelengths 1250 and 1300 nm as

being the best for communication, once they get larger skin

thickness limits for the same required quality. These results are

consistent with the literature presented in the state of art (section

Fig. 4. Output signal eye diagrams of normalized amplitudes of the AC

component, for different values of the signal wavelength, skin thickness and

lighting conditions.

Fig. 5. Q factor in the three lighting scenarios: a) sunlight; b) total darkness; c) white LED light at 500 lux

II), which indicates spectral optical windows that maximize skin

penetration, between 600 and 1300 nm[2, 7].

B. Average current level

After evaluating the data component of the optical signal

(AC component normalized to the maximum signal amplitude),

the next metric used is intended to measure the energy

component of the optical signal (DC component). The aim is to

evaluate the influence of the received energy level in signal

degradation. If on the one hand, there is greater penetration of

optical radiation to the skin for certain wavelengths, there is also

an increased level of energy received, which will consequently

increase noise level. Thus, as the simulation performed for the

quality factor, values of the average current level at reception

were extracted for the same wavelengths and skin thicknesses.

The indicator values are presented with base ten logarithm of the

average current level (log10 𝐼)̅ – Fig. 6 – for better visibility of

graphical variations.

Fig. 6 demonstrates once again the similarity of indoor white

LED lighting at 500 lux and total darkness environments.

It was also observed that DC component of the electric current

decreases with skin thickness, in the three illumination

environments, because of related attenuation increasing.

However, the current levels are significantly higher in the case

of an environment exposed to sunlight (can be up to two order

of magnitude higher for the same wavelength and skin

thickness), which makes the amplitude of the current less

dependent on the emission wavelength when compared with the

other two cases. These results justify further degradation of eye

diagrams, and thus the overall decrease of the quality factor for

the sunlight illumination environment, since the variance of the

receiver shot noise is dependent on the current amplitude, as

already mentioned. Moreover, the received current level for

white LED lighting environment, for the same wavelength,

corresponds to a quality factor. Therefore, it is also concluded

that, the energy produced by white LED(s) in an environment

with a typical illuminance (500 lux) is not significant, which

explains the results obtained for the quality factor in Fig. 5. In

fact, the gap between the solar white LED lighting

environments it is understood, since the intensity of solar

radiation can reach 1000 W/m2 and the white LED, in case an

illuminance of 500 lux, measured about 1.5 W/m2.

C. Energy Harvesting

The evaluation of the signal energy component (DC level)

presented in the previous section can be also used to evaluate the

energy harvesting capabilities of the implanted receiver, besides

being used to study optical signal degradation. On the one hand

the received electric current can cause signal degradation. On the

other hand can be used to collect energy for IMD battery

charging purposes. Then, in order to find the spectral window

that maximizes the signal quality and the energy level received,

the multiplication of Q factor and average current level values

(normalized at their maximum values) was computed. The

results show that the region that maximizes energy harvesting is

the same as the one that maximizes the quality of

communication, i.e., the region between 1100 and 1300 nm, in

all illumination environments mentioned. Hence the ideal

photodiode suitable to a transdermal optical system must have a

sensitive detection region in the mentioned spectral region, so it

is advisable to use an InGaAs PIN.

The quality factor and the average electric current received

as function of the photodiode effective area was measured, for

an ideal emission wavelength of 1100 nm and a skin thickness

of 4 mm. From Fig. 7, it is noted that the quality of

communication only starts to decrease from 200 mm2, which is

a realistic value for an effective area of a photodetector to

implement in an IMD. This effective area corresponds to an

Fig. 6. Q factor in the three lighting scenarios: a) solar light; b) total darkness; c) white LED light at 500 lux

Fig. 7. Average current level and Q factor of optical signal that reaches the receiver, as function of photodiode effective area, for an 1100 nm wavelength

emission and 4 mm of skin thickness.

average current level of 3.3 μA. Furthermore, for an effective

area of 10 cm2, it is possible to achieve about 15.0 μA of current.

A typical nominal supply current for commercial pacemakers is

20 μA [9]. Thus, these results can be relevant to enhance the

durability of IMDs with low power consumption.

V. EXPERIMENTAL IMPLEMENTATION

An experimental set-up was made in order to complement the discussed model and to study optical signal attenuation through a skin sample. Due to ethical, technical and regulatory barriers, relative to the use of human skin, these study was conducted for three animal’s specimens – pork ham, chicken skin and pork skin. Although animal skin have different properties from human skin, it arise as a reasonable alternative, since they have similar transmission optical windows [2]. The study of optical radiation attenuation on samples, underwent two experimental analyzes: spectral attenuation and frequency response of the transfer function.

A. Experimental Descripiton

1) Espectral Attenuation

This analysis consist on measure the intensity of radiation

spectrum from a white light source. A spectrometer (Ocean

Optics USB4000), linked to a laptop, acquires the radiation

from the white light source. Thus, it is possible to compare the

light spectral intensity obtained by direct incidence of white

light with the one obtained through a skin sample. From the

difference between obtained spectrums it is possible to compute

the attenuation coefficient, given the sample thickness. The

specimen used was pork ham with a thickness of 0.68 mm.

2) Frequency response analysis

This experimental implementation consists in measure the

transfer function frequency response of the transmitted optical

signal through different samples and compare it with the

obtained for direct radiation incidence (without sample), for

different LEDs. From the difference between frequency

responses it is possible to obtain the attenuation coefficient of

each specimen, given their thicknesses. The specimens used

was pork ham, chicken skin and pork skin with thicknesses of

0.28, 1.29 and 2.50 mm, respectively.

The measures was obtained from a Vector Network Analyzer

(VNA), which employs a sinusoidal signal for a frequency

scanning, to be transmitted by the LED, that modulate it with

on-off keying (OOK). Then, VNA compares the signal emitted

with the one received, and measure the S parameters of the

network, specifically the insertion loss (in dB).

The set-up consists on a LED driver connected to the channel

1 of VNA and a PIN driver in series with an amplifier, with a

gain of 20 dB, connected to the channel 2 of VNA. The

transmitter and receiver are separated by 5 mm, and hold by an

acrylic support, in which the biological sampled is placed –

Fig. 8. Different LEDs were used, in order to register the

frequency response of the optical signal received for different

emission peak wavelengths, through the different specimens.

The technical specifications of the LEDs used, are presented in

Table III.

For the receiver, was used a Si PIN, which has an effective

area of 13 mm2 (Thorlabs FDS100).

TABLE III – LEDS SPECIFICATIONS

Denom. Reference Wavelength

(nm)

Radiant

Intensity

Divergence

angle (º)

B Multicomp

MCL034SBLC 472 1,45 cd 36

Y Optek Technology

OVLFY3C7 595 4,00 cd 30

W Lumex

SLX-LX3054UWC 550 (typ.) 3,30 cd 30

IR 1 Kingbright

L-53SF4C 880 15 mW/Sr 20

IR 2 Kingbright L-53F3C

940 30 mW/Sr 20

In Fig. 9, is presented an example of frequency responses

compilation of direct incidence and three specimens analysis,

for the blue monochromatic LED (472 nm) case.

Fig. 9 analysis, confirms the possibility of transmitting an

optical signal through a skin layer, even for the specimen 3

whose thickness is 2.5 mm, with no deformation of the

frequency responses up to about 10 MHz. Moreover, there is an

emission bandwidth of about 3 MHz to direct incidence, and

that will not change significantly in any of the specimens.

Therefore, dispersive effects are not detected in the transdermal

channel. These results demonstrate communication capabilities

that enables rates higher than the one used in transdermal model

simulation (1 Mbps).

Fig. 8. Picture of the transdermal system set-up

Fig. 9. Frequency response of optical radiation incidence of a blue

monochromatic LED (472 nm) to direct incidence and through the specimens

1, 2 and 3.

B. Data Analysis

After the description of experimental implementations set-

up, the attenuation coefficients of each specimen was

determined. In each of the experiments described, a reference

scenario of direct incidence was recorded to enable

computation of the attenuation coefficient of each specimen

relatively to that reference.

The data of the attenuation coefficients determined for each

experiment were collected in Fig. 10. The results are presented

with the reported attenuation coefficient for the transdermal

channel model (Fig. 2) in order to be compared.

Fig. 10 shows that the closest results to the reported

attenuation coefficient, are the obtained from the spectral

attenuation analysis data. However, the discrepancy between

the curve obtained in the spectral attenuation analysis and the

reported attenuation coefficient increases in the spectrum. This

increasing discrepancy could be mainly explained by the

biological differences between the specimen 1 (pork ham) and

human skin.

Regarding to the obtained data from transfer function

frequency response analysis, it is observed a satisfactory

approximation of the specimen 1 attenuation coefficient,

experimentally obtained, relatively to the reported one, on blue

spectral region and on near infrared one. In fact, for the white

LED and yellow one (595 nm), there is a considerably larger

discrepancy (may reach a maximum error of 30%).

Furthermore, the discrepancies observed for the specimens 2

and 3, are even greater, relatively to reported attenuation

coefficient, wherein the pork skin has the lowest values

recorded for the attenuation. These results can be explained by

systematic experimental errors, namely: i) mechanical

problems of alignment between the transmitter and the receiver,

and maintenance of the fixed distance between the transmitter

and the receiver (5 mm); ii) imperfect measuring of biological

samples thickness.

Moreover, the biological differences between human dermis

and specimen considered impose their natural differences in

their optical radiation attenuation coefficients.

However, the trend in the attenuation coefficient in the

spectrum is maintained, in which there is a general decrease in

its value with the increasing of the emission wavelength.

Nevertheless, in the specimens 1 and 2 for the infrared LED

with a peak emission on 940 nm, and in all specimens in white

LED, the trend is different from the reported. In the infrared

LED, a possible explanation for the results is related to its

optical beam, which is invisible to the human eye, making it

even more susceptible to alignment errors between the

transmitter and the receiver. In the white LED, the measured

attenuation is an average of their emission peaks, which

explains the constant attenuation coefficient observed.

Therefore, despite the differences observed mainly for

specimens 2 and 3, relative to the reported attenuation

coefficient, the decreasing of its value in the spectrum for

wavelengths studied, it is experimentally confirmed for most of

the cases. Thus, communication is particularly advantageous,

as greater the emission wavelength emission in the tested

spectral region, which is consistent with the obtained results of

the transdermal model simulation (section IV). Furthermore, it

is shown that the pork ham specimen can provide an acceptable

approximation to the attenuation coefficient of the human

dermis, and can be used to experimental implementations in

order to simulate human skin.

Hence, the obtained results complement the model in this

work, showing communication capabilities for a transdermal

low cost system.

VI. CONCLUSIONS

In the first part of this work it was carried out a

research on the most relevant reported studies on transdermal

optical communications field.

Based on the mentioned studies, a model of a

transdermal optical link was established for a connection

between a transmitter outside the body and an implanted

receiver. The main factors that influence the power loss and

degradation of the optical signal in the communication

channel, were identified: the transmittance of the skin,

influence of background illumination and the various types

of misalignment between the transmitter and the receiver.

The constructed model was simulated in MATLAB

environment for a 1 Mbps signal, with a direct intensity

modulation (OOK) in an NRZ scheme. The transmitter and

the receiver are based, respectively, on commercials LED

and PIN.

The simulation was performed for a range of skin

thicknesses and emission wavelengths, in three illumination

environments (sunlight illumination, darkness, white LED(s)

indoor illumination), in order to evaluate the several factors

that affect signal degradation. The simulation results

confirmed that the environment exposed to sunlight is the

most harmful to the communication. The scenario

illuminated by white LED(s), with a typical indoor

illuminance (500 lux), can be compared to a darkness

environment in terms of received data signal quality. On the

other hand, the sunlight exposure environment is the one that

provides greatest energy harvesting capabilities. Thus, it was

identified the spectral region between 1100 and 1300 nm,

Fig. 10. Attenuation coefficients experimentally obtained, and compared with the reported one (green line). Red line represents the data obtained from spectral

attenuation analysis. Points are related to the data obtained from frequency response

analysis. Full points – monochromatic LEDs (B, Y, W, IR 1 and IR 2). Empty points – white LED (W).

that simultaneously maximizes the quality of communication

and the average electric current level generated in the

receiver. It was also concluded that the increase of

photodiode’s effective area may cause a saturation of the

optical signal quality factor from a given amount of received

current. It was identified average levels of electrical current

received in the order of μA, depending on the thickness of

the skin and photodiode’s effective area considered. These

values may be relevant to enhance durability of low energy

consumption IMDs, such as pacemakers.

Finally, an experimental implementation was carried

out with the purpose of complementing the transdermal

model addressed. The analysis results of the response

frequency demonstrate communication capabilities through

all specimens addressed. On the other hand, there are no

differences reported in the emission bandwidth on frequency

responses of the different specimens, compared with the

direct incidence transmission. Therefore, no dispersive

effects was identified on the transdermal channel. The final

results show a general decrease of the attenuation coefficient

with increasing of wavelength in the observed spectrum,

which is consistent with the proposed model. It is verified

that in the visible spectral region, there are communication

advantages to the higher wavelengths. In the near-infrared

spectral region, it is demonstrated that up to 980 nm,

communication becomes even more reliable regarding the

visible light transmission, in terms of attenuation of the

optical signal.

REFERENCES

[1] F. Nebeker, “50 Years of the IEEE Engineering in Medicine and

Biology Society and the Emergence of a New Discipline,” pp. 17–

47, 2002.

[2] J. Abita and W. Schneider, “Transdermal optical communications,”

Johns Hopkins APL Tech. Dig., vol. 3, pp. 261–268, 2004.

[3] W. H. Ko, “Early History and Challenges of Implantable Electronics,” ACM J. Emerg. Technol. Comput. Syst., vol. 8, no. 2,

pp. 1–9, Jun. 2012.

[4] U. Lakshmanadoss, P. Chinnachamy, and J. P. Daubert,

“Electromagnetic interference on pacemakers,” Indian Pacing Electrophysiol. J., vol. 2, no. 3, pp. 74–8, Jan. 2011.

[5] D. B. Kramer, M. Baker, B. Ransford, A. Molina-Markham, Q. Stewart, K. Fu, and M. R. Reynolds, “Security and privacy qualities

of medical devices: An analysis of FDA postmarket surveillance,” PLoS One, vol. 7, no. 7, pp. 1–7, 2012.

[6] S. L. Pinski and R. G. Trohman, “Interference in implanted cardiac devices, Part I,” Pacing Clin. Electrophysiol., vol. 25, no. 9, pp.

1367–1381, 2002.

[7] Y. Gil, N. Rotter, and S. Arnon, “Feasibility of retroreflective

transdermal optical wireless communication,” Appl. Opt., vol. 51, no. 18, p. 4232, 2012.

[8] T. Liu, U. Bihr, S. M. Anis, and M. Ortmanns, “Optical transcutaneous link for low power, high data rate telemetry.,” Conf.

Proc. IEEE Eng. Med. Biol. Soc., vol. 2012, pp. 3535–8, Jan. 2012.

[9] N. K. Pagidimarry and V. C. Konijeti, “A High Efficiency Optical

Power Transmitting System to a Rechargeable Lithium Battery for All Implantable Biomedical Devices,” in IFMBE Proceedings,

2007, vol. 15, pp. 533–537.

[10] S. Ayazian and A. Hassibi, “Delivering optical power to

subcutaneous implanted devices,” Proc. Annu. Int. Conf. IEEE Eng.

Med. Biol. Soc. EMBS, pp. 2874–2877, 2011.

[11] J. C. Jarvis and S. Salmons, “A family of neuromuscular stimulators

with optical transcutaneous control.,” J. Med. Eng. Technol., vol. 15, no. 2, pp. 53–57, 1991.

[12] J. A. Miller, G. Belanger, I. Song, and F. Johnson, “Transcutaneous

optical telemetry system for an implantable electrical ventricular

heart assist device,” Med. Biol. Eng. Comput., vol. 30, no. 3, pp. 370–372, 1992.

[13] M. Sawan, K. Arabi, and B. Provost, “Implantable volume monitor and miniaturized stimulator dedicated to bladder control.,” Artif.

Organs, vol. 21, no. 3, pp. 219–222, Mar. 1997.

[14] N. Kudo, K. Shimizu, and G. Matsumoto, “Fundamental study on

transcutaneous biotelemetry using diffused light.,” Front. Med. Biol. Eng., vol. 1, no. 1, pp. 19–28, Jan. 1988.

[15] B. C. Larson, “An Optical Telemetry System For Wireless Transmission Of Biomedical Signals Across The Skin,”

Massachusetts Institute of Technology, 1999.

[16] E. Okamoto, Y. Yamamoto, Y. Inoue, T. Makino, and Y. Mitamura,

“Development of a bidirectional transcutaneous optical data transmission system for artificial hearts allowing long-distance data

communication with low electric power consumption.,” J. Artif.

Organs, vol. 8, no. 3, pp. 149–53, Jan. 2005.

[17] R. Anderson and J. Parrish, “The optics of human skin,” J. Invest.

Dermatol., vol. 77, no. 1, pp. 13–19, 1981.

[18] D. M. Ackermann, “High Speed Transcutaneous Optical Telemetry Link,” Case Western Reserve University, 2007.

[19] S. Parmentier, R. Fontaine, and Y. Roy, “Laser diode used in 16 Mb/s, 10 mW optical transcutaneous telemetry system,” 2008 IEEE

Biomed. Circuits Syst. Conf., pp. 377–380, 2008.

[20] F. A. Duck, Physical Properties of Tissues: A Comprehensive

Reference Book. Cambridge, Great Britain: Academic Press Inc., 1990.

[21] a N. Bashkatov, E. a Genina, V. I. Kochubey, and V. V Tuchin,

“Optical properties of human skin, subcutaneous and mucous tissues

in the wavelength range from 400 to 2000 nm,” J. Phys. D. Appl. Phys., vol. 38, no. 15, pp. 2543–2555, Aug. 2005.

[22] J. Vitasek, E. Leitgeb, T. David, J. Latal, and S. Hejduk, “Misalignment Loss of Free Space Optic Link,” in 16th

International Conference on Transparent Optical Networks

(ICTON), 2014, pp. 1–5.

[23] J. Poliak, P. Pezzei, E. Leitgeb, and O. Wilfert, “Analytical expression of FSO link misalignments considering Gaussian beam,”

Proc. 2013 18th Eur. Conf. Netw. Opt. Commun. NOC 2013 2013

8th Conf. Opt. Cabling Infrastructure, OC I 2013, pp. 99–104, 2013.

[24] J. Poliak, P. Pezzei, E. Leitgeb, and O. Wilfert, “Link budget for high-speed short-distance wireless optical link,” in Proceedings of

the 2012 8th International Symposium on Communication Systems,

Networks and Digital Signal Processing, CSNDSP 2012, 2012, pp. 1–6.

[25] S. R. Z. Ghassemlooy, W. Popoola, Optical Wireless

Communications System and Channel Modelling with MATLAB.

2013.

[26] T. Komine and M. Nakagawa, “Fundamental analysis for visible-light communication system using LED lights,” IEEE Trans.

Consum. Electron., vol. 50, no. 1, pp. 100 – 107, 2004.

[27] H. Chun and S. Rajbhandari, “Effectiveness of blue-filtering in

WLED based indoor Visible light communication,” 3rd Int. Work.

Opt. Wirel. Commun., pp. 60–64, 2014.

[28] P. Butala, H. Elgala, P. Zarkesh-ha, and T. D. C. Little, “Multi-Wavelength Visible Light Communication System Design,” in

Globecom 2014 Workshop on Optical Wireless Communications,

2014, no. December, pp. 1–10.

[29] ETAP, “European Lighting Standard EN 12464-1.” 2011.

[30] S. L. Rumyantsev, S. Sawyer, N. Pala, M. S. Shur, Y. Bilenko, J. P.

Zhang, X. Hu, A. Lunev, J. Deng, and R. Gaska, “Low frequency noise of light emitting diodes,” Noise Devices Circuits III, vol.

5844, pp. 75–85, May 2005.

[31] G. P. Agrawal, Fiber-optic communication systems, Fourth Edi.

Rochester, New York: John Wiley & Sons, Inc., 2010.