Final Draft of Research Paper 1

IOP Publishing Journal of Neural
Engineering
A Wireless Neural Interface Platform for
Epidural Spinal Cord Implants in Rats
Capstone Group E
Team members: Isaac Cassar, Trevor Davis, Ben Johnson, Kanav Saraf, Cory Schroeder,
Connor Sullivan
ABSTRACT
Objective. Spinal cord injuries result in damage of the spinal column, with the most severe cases
leading to paralysis. Treatments, such as epidural spinal cord stimulation, aim at restoring the
patients’ ability to regain motor and sexual control of their body. In this paper, we discuss the
development of a system for use in in vivo epidural spinal cord stimulation experiments that
provides wireless control over a spinal cord implant designed previously in Dr. Wentai Liu’s lab.
Our proposed system marks the next step in the miniaturization and mobilization of epidural spinal
cord stimulation therapy. Approach. Our system consists of: an android application, a WiFi
module, a microcontroller unit (MCU), a Differential Phase-Shift Keying (DPSK) circuit and
inductive power and data coils. Each of the components have been developed independently and
are now ready to be assembled into a composite system. Main result. Independent benchtop
circuitry has been developed that will be incorporated into the final completed system.
Significance. The implant that we have created this wireless interface for is the first implant that
allows for simultaneous stimulation and recording of spinal cord signals. In the future, our wireless
spinal cord implant interface platform can be expanded to include a bidirectional flow of data both
to and from the implant.
INTRODUCTION
A spinal cord injury (SCI) describes any injury or damage to the spinal column, with the most
severe SCI leading to paralysis [1]. Currently there are over 1,275,000 people living with SCI in
the United States, and an additional 12,500 new cases occur every year [2]. There are no
reparative treatments for SCI; instead current standard medical treatment is focused on
maintaining patient quality of life and reducing secondary complications from SCI such as blood
clots, faulty bladder control, and poor bowel management.
A novel technique being pioneered to restore function to SCI paralyzed patients is epidural Spinal
Cord Stimulation (SCS), where an electrode array is implanted on the spinal column that sends
pulsed electrical signals along the neurons [3, 4]. SCS was initially targeted at alleviating patient
pain. This was found to be successful as pain reduction was demonstrated across more than 61
peer-reviewed studies [5, 6]. In recent years SCS has also been shown to restore locomotion in
some patients. The first study that was able to demonstrate rhythmic stepping in paralyzed rats
during treatment with SCS was performed in 2005 in our collaborator Dr. Reggie Edgerton’s
laboratory at UCLA [7]. In the years since, SCS treatment on human patients has allowed patients
to regain full weight-bearing standing and initiate supine leg movements [8-9].

Although these initial results have been promising, current SCS treatment for the recovery of
locomotion is not without its limitations. Researchers using current systems run into complications
because they are not using them for their designed purpose, resulting in the FDA setting limits on
tests performed on human patients per week [8-9]. In addition, current neurostimulators are not
versatile enough to allow customization across different patients. These devices also lack the
ability to record signals from the spinal column, which is helpful in patient diagnosis and analysis
of device function. To provide versatility for patient treatment, a device should be capable of
controlling multiple electrodes with different parameters including: anodic/cathodic current
intensity, anodic/cathodic pulse width, start delays, interphase delays, waveform polarity, pulse
train size, and pulse train frequency.
In this paper, we detail the process of creating a neural interface platform that is capable of
incorporating new functionality specific to movement restoration. We discuss the creation and
debugging of each individual component of this platform. When assembled, the system powers
the implant wirelessly and enables wireless control with a user-friendly Graphical User Interface
(GUI). This GUI is in the form of an Android application and can control a variety of stimulation
parameters along with allowing for the incorporation of bidirectional data flow both to and from
the implant.
Our proposed system, which we call the uWalk Again, can be broken down into the three parts
seen in Figure 1. Part A consists of a user-friendly Android tablet application that controls (part B)
a Microcontroller Unit (MCU) placed in a jacket worn by the rat. The MCU modulates and transmits
power and data through the Class E circuit to the inductive coils housed in the jacket to inductive
coils implanted within the rat. The implant, part C, decodes these signals and initiates spinal cord
stimulation. The specific design parameters used when developing each individual component
are described in the paragraphs below.
Figure 1: A systematic overview of the three components of the uWalk Again. (A) shows the tablet in which
the researcher inputs testing parameters. (B) Shows the printed circuit board (PCB) that would be housed
on the jacket that contains the WiFi module, MCU, Battery, and power/data coils. (C) Shows the implant
that is placed right underneath the internal power and data coils.

METHODS
GUI Programming
One of the first tasks to address in overcoming the shortcomings of previous systems is to create
a versatile and user-friendly control interface. The GUI was designed for the Samsung Nexus 10
tablet running Android Lollipop 5.0.1. The programming was done using XML (Extensible Markup
Language) and Java on the Android Studio 1.0 software development kit (SDK) based on APK
21. The tablet application has been designed keeping in mind the Material Design guidelines put
forward by Google for Android Lollipop 5.0.1 in 2014. These guidelines address the appearance
of any application in order to make the layout intuitive for the user. Lastly, the WiFi transmission
java code is loosely based on a C-sharp code previously created in the lab of Dr. Wentai Liu [10].
This interface was combined with the WiFi transmission code on the program and the app was
downloaded on the tablet to serve as the master controller of the entire system.
The ergonomics of our application interface have been addressed in four main ways. Firstly, the
tablet application uses large button sizes and styles to avoid accidental-touches by the user.
Secondly, the selectable button layout for the electrode array mirrors the actual position of
electrodes on the implant. This eliminates the need for the user to memorize electrode labels, and
allows them to intuitively stimulate electrodes simply based on their positions in the button layout.
Thirdly, each group of electrodes is color coded on selection. Groups of electrodes with the same
parameters are assigned the same color, while different groups of electrodes have different colors
in order to provide a visual confirmation to the user that their electrode configurations have been
properly set up prior to stimulation. Finally, the application also takes advantage of tabbed layouts
to allow for the controls to be comfortably spaced out, yet still include all the necessary functions
on the same app-screen. These four stylistic choices are highlighted in Figure 2. Additionally, we
also compare this interface with the user-interface for a neurostimulator platform created by
Medtronic called N’Vision [11]. The usability of this interface is demonstrated later in the results.

Figure 2: The Graphical User Interface (GUI) is in the form of a tablet application. The application has
been designed in a way that makes the layout intuitive and easy-to-use for the clinician.

MCU Programming
A key intermediate between data representation on the tablet and the data acquisition from the
implant is the MCU. As such, we acquired an MCU (Microchip PIC24HJ128GP502) and coded it
in C language, using MPLAB X IDE as the programming software. Code was uploaded from
MPLAB to the MCU using a small printed circuit board (PCB) (Microchip Microstick II) as the
programming tool; this PCB connected to the computer through USB and has the capability to
connect to a breadboard, allowing for easy programming and testing of the MCU. A WiFi module
(Microchip RN-171 WiFly) was purchased in order to establish data communication between the
tablet and the MCU; the RN-171 runs at 2.4 GHz under IEEE 802.11 wireless local area network
specifications, which allows for local communication between devices. The RN-171
communicates using UART (Universal Asynchronous Receiver/Transmitter) technology, which
transmits information via packets of eight bits (one byte) for serial communication between a
transmitter and a receiver. Received data is outputted from the module serially. The WiFi module
facilitates the transmission of encoded binary data carrying information on the stimulation
parameters of the electrodes from the tablet to the MCU. An Arduino Yun was used to simulate
test data transmission between the WiFi module and MCU without programming the WiFi module
and establishing connection between the tablet and module. The Yun was connected to the MCU
via a breadboard, and sample binary data was sent from the Yun to the MCU using the same
UART format that the WiFi module follows. This data was read from the UART register within the
MCU and outputted at a frequency of 2 MHz to the Differential Phase-Shift Keying (DPSK) circuit.
In addition to this 2 MHz data signal, a 20 MHz frequency signal and a 2 MHz frequency clock
signal (out of phase with the data signal) were programmed and outputted by the MCU to the
DPSK circuit for use in digital modulation of a carrier wave to encode data.
Communication and Transmission of Data and Power to Implant
The MCU receives the full data in a 19-bit data binary form and will output that data to the implant.
This is done through a DPSK circuit. The data in 19-bit format is in simple binary code. In order
to communicate the ones and zeros to the implant, the DPSK circuit uses two different phase 20
MHz (one at 0° phase and one at 180°) signals to induce phase changes in the data coils. The
MCU is connected to the DPSK circuit and provides the circuit with the 20 MHz carrier signals, a
2 MHz clock signal and a 2 MHz data signal. The DPSK circuit is connected to the data coil Class
E circuit and providing it with a 20 MHz signal.
The data is transmitted by switching between the two 20 MHz signals. Every time a 1 is passed
to the DPSK circuit from the MCU, the DPSK circuit is set up to switch the phase of the signal,
which the implant then records as a 1. Anytime a 0 is sent from the MCU the DPSK circuit does
not change the phase and the implant recognizes the same signal and that there was not a change
during that time cycle and records a 0.
Power and Data Coil Construction
The designs of the power and data coils were carried out based on constraints such as voltages,
currents, and frequencies necessary for the implant, the size of the inner coils, and the spacing
between the inner and outer coils. The power coils were designed to maximize power transfer
efficiency, which required a high quality factor in the coils, and the data coils were designed to
maximize their bandwidth, which required a low quality factor. Based off of these constraints, the
coils were designed using the procedures outlined in [12-14] with their calculated parameters
presented in Table 1.

Table 1. Design Parameters for Power and Data Coils
Parameter Power Coil Data Coil
Induced Voltage 12 V 6 V
Induced Current 10 mA 4.75 mA
Frequency 2 MHz 20 MHz
Inner Coil (IC) Diameter 5 mm 5 mm
Outer Coil (OC) Diameter 30.4 mm 10 mm
IC Width 1.6 mm 1.6 mm
OC Width 2 mm 2 mm
Coil Separation 1.5 cm 1.5 cm
IC Number of Turns 15 10
OC Number of Turns 10 10
IC Inductance 1 μH 1 μH
OC Inductance 5 μH 1 μH
IC Quality Factor >75 5 – 15
OC Quality Factor >75 5 – 15
After determining the appropriate design parameters, cylindrical bobbins were printed on a
Makerbot 3D printer to provide the specified diameter for the coils. To assemble the power coils,
Litz wire was wrapped around the bobbins according to the calculated number of turns. The data
coils used 36 gauge copper wire wrapped around the bobbin. To secure coils for removal from
the bobbin, a Silicone Elastomer Kit (Dow Corning) was used to solidify a thin layer of silicone
between the coil turns. Coils were then removed from the bobbin and ready for further testing.
Orientation Effects of Power and Data Coils
Class E amplifier circuits were designed for both the power and data coils according to the
procedure outlined in [15]. After connecting the amplifiers to the coils, the ability of the coil
containing circuit to transfer power or data signal wirelessly to the implant-side circuitry was
analyzed by measuring the voltage output across both the primary-side and secondary-side
inductors with an oscilloscope. Class E circuit capacitance values were tuned with the addition or
removal of further capacitors until an optimum voltage amplitude was reached, shown in Table 2.

Table 2. Capacitors Used in Class E Amplifiers
Parameters Power Coil Data Coil
Cseries 1.25 nF 38 pF
Cshunt 32 nF 100 pF
Cresonance 5.8 nF 32 pF
Additionally, the effect of coil distance, axis alignment, and orientation angle on wireless power
and data transfer was investigated. In general, after implantation, coil alignment is not fixed
because the implant can slightly migrate along the rat’s spinal column. To determine the effects
of suboptimal alignment, an adjustable coil platform was designed in AutoCad and 3D printed
using a MakerBot Replicator 2. The coil platform held the primary side power and data coils
stationary while allowing for adjustment of the location and orientation of the secondary side coils.
The secondary side coil stand could be moved away from the primary side to alter the separation
of coils along the same axis. The coil platform also allowed for the lateral translocation of the
secondary coil at a fixed distance, chosen to mirror the relative separation of coils through the
rat’s skin. Additionally, the platform allowed for the rotation of the secondary-side coil at the same
fixed distance. In all tests, the amplitude of the secondary-side voltage was recorded to ensure
the implant would be supplied a minimum threshold voltage, enabling it to power itself and reliably
communicate data.
Composite System Performance
The composite system was first tested by incorporating the DPSK circuit with the Class E amplifier
and the data coils. Circuitry performance was tested by analyzing the signals received along
different portions of the circuitry using an oscilloscope. Successful tests entailed verification of
phase shift when a digital signal was sent.
RESULTS
GUI Usability
The GUI tab structure is shown in Figure 3. The first image shows the untouched main screen,
which is what a user would see upon opening the application. From there, the user can select
which electrodes they want to stimulate and input the desired parameters needed for versatile
stimulation. Next, the user would connect the tablet to the WiFi module on the motherboard with
all of the other hardware which is as simple as connecting to the internet. Lastly, the researcher
would select channels that he desired to record from and view them in the recording tab also
displayed in Figure 3. The system is designed to flow from tab to tab in the logical process of
connecting to, and stimulating the implant. It is also very simple to go back and correct any errors.
This application was designed to be very intuitive and much easier to use than other GUIs used
to control other neurostimulators.

Figure 3: (1) The home screen of the uWalk Again GUI that clinicians will interface with first. (2) The tab
where specific electrode parameters can be set for a variety of electrode groupings. Electrodes with
different parameters are shown with different colors. (3) Tab view where researchers will connect to the
WiFi module on the uWalk Again. (4) The tab where recorded data can be displayed.
In order to demonstrate the usefulness of this application, its interface is compared to that of
Medtronic’s N’Vision neurostimulator system [11] with the differences highlighted in Figure 4. This
programming device developed by Medtronic has many limitations. Firstly, Medtronic’s device is
only available through purchase from that company causing users decreased accessibility to the
device compared to the uWalk Again system which is available as an Android application on any
Android device. Secondly, the interface created by Medtronic is methodical, slow and prone to
accidental error. Aside from their GUI being difficult to understand at first glance, the main
limitation lies in the fact that clinicians can only change one parameter for one electrode at a time.
For example, there are separate tabs for the amplitude, pulse width and frequency for each
individual electrode causing programming to be slow. This keeps clinicians from being able to
view the entire electrode configuration at once and correcting input errors. Lastly, our system
allows multiple electrodes to be programmed at once and displays multiple parameters to allow
for programming to be faster. Our system also shows color coded buttons to serve as a visual
confirmation that specific electrodes don’t accidentally differ by one parameter.

Figure 4: A comparison between the uWalk Again user interface and the Medtronic N’Vision user interface
is shown above. Some of the main differences are shown in: (1) The uWalk Again is on a tablet, while the
N’Vision is a costly proprietary device, (2) The uWalk Again displays all electrodes with color coding at
once, while the N’Vision requires electrodes to be programmed one at a time, (3) The uWalk Again allows
multiple parameters for each electrode to be programmed at once, while the N’Vision dedicates one tab
per parameter.
MCU UART and Signaling Control
Sample UART data transmission from the Arduino Yun to the MCU consisted of sending two sets
of binary sequences; the first binary sequence was “101010” and the second sequence was
“11001100”. This data was received by the MCU and stored in an internal UART received data
register. The MCU was programmed to read the register once it received data, and then step
through the data bit-by-bit. An output port of the MCU was then set to equal the value of the data
bit being read (either one or zero), thus transmitting the received data. The 20 MHz signal was
produced by routing the internal MCU clock to an output port for continuous transmission of the
signal. The 2 MHz clock signal was produced by setting a timer that divided the 20 MHz clock by
ten and programming an output port to switch its value (from one to zero, zero to one, or no
change at all) every time the timer finished. An oscilloscope screenshot of the three signals

together for the “101010” sequence can be seen in Figure 5A. The data signal is in the green,
along with the 20 MHz signal in gold and the 2 MHz clock signal in purple. In Figure 5B, the data
signal is superimposed on the 2
MHz clock signal to show that the two signals are out of phase.
Figure 5: (A) 20 MHz carrier signal can be seen in gold. 2 MHz data signal can be seen in green (encoded
with a binary sequence of “101010”). 2 MHz clock signal can be seen in purple. (B) 20 MHz carrier signal
can be seen in gold. Data signal (green) and 2 MHz clock signal (purple) are the same signals from (A).
The signals can clearly be noted to be out of phase from each other.
DPSK Circuit Data Signal Encoding
For the test code given (“11001100” at 2 MHz) the
DPSK circuit will switch the phase of the 20 MHz
signal every time it is passed a 1 and will not
change the signal when passed a 0. This is shown
when you compare the Gold and Green signals in
Figure 7, with the Green being the output. The
implant does not gain any info from the 20 MHz
signal except when it changes phase. You can see
that when 1 is passed the Green is switched to
“high” and when another 1 is passed right after the
first it is changed again.
Figure 6: The four signals shown are from the DPSK
circuit. The Gold is a data signal sending
“110011001100” at a 2 MHz frequency. The Green is
indicating which phase 20 MHz signal is being sent (high
is the 180° and low is the 0°). The purple is a mid-circuit
coded signal that the DPSK circuit creates in conjunction
with the pink 2 MHz clock signal to code the Green
signal.

Orientation Effects of Power and Data Coils
To verify the efficacy of power and data transfer after implant in rats, the orientation effects of the
primary-side coils on the secondary-side coils were analyzed. First, the power coils were attached
to the adjustable coil platform and distance was measured starting with a coil separation of 5 mm
and systematically increased using a 5 mm step-size until a separation of 40 mm was reached.
The maximum induced DC voltage, which occurred at a 5 mm separation, was 10.9 V. Voltage
decreased relatively linearly with increasing distance. Next, the effects of off-axis alignment were
observed by moving the secondary-side coil laterally at a fixed distance of 10 mm. Off-axis
alignment measurements were centered at 0 mm off-axis; negative moves off-axis represented a
movement of the coil to the left while a positive off-axis move indicates the secondary-side coil
was moved to the right. Induced voltage in the secondary-side stayed relatively constant at
approximately 10V. However, as the secondary coil was moved outside of the area of the primary
coil, voltage dropped significantly. This indicates that at a fixed distance the induced voltage will
remain relatively constant, provided the secondary-side coil remains within the area of the
primary-side coil. Finally, the secondary-side coil was centered within the primary coil area at a
distance of 10 mm and then rotated so that the normal vectors to the coil area were no longer
aligned. Induced secondary-side voltage was measured at 0°, 30°, 45°, 60°, and 90°. With
increasing angle measurement, the induced voltage dropped.
Figure 7: Graph showing the effect of the relative orientation of the power coils on the induced DC voltage
that will be provided to the implant. (A) a design schematic of the adjustable coil platform and the axis that
were investigated (B) a graph of the effects of primary-side and secondary-side coil separation on power
transfer (C) a graph of the effect of off-axis alignment on secondary-side induced voltage. (D) A graph of

the effect of altering the angle of the normal vectors to the coil area. All experiments were performed at 2
MHz with a 7.2 V DC voltage source.
After completing test to determine the orientation effects of the power coil inductive transfer, the
data coil circuitry was similarly tested. Since the primary-side data coil is smaller and has a lower
quality factor than the primary-side power coil, smaller step-sizes were used for both the distance
and the distance-off-axis measurements. When the data coils are separated by a distance of 6
mm, secondary-side induced voltage is approximately 1 V. Further separation to 8 mm drops the
induced voltage closer to 0.5V. Off-axis effects on the data coil were analyzed at a distance of 6
mm. Between -2 mm and 2 mm, secondary-side induced voltage was maintained above 0.5 V.
Outside of this range, the induced voltage dropped off rapidly. The investigation into angle effects
on data transfer was also performed at 6 mm. Data coil voltage transfer follows a similar pattern
to power transfer with an increasing angle between coil area vectors. Like the power coils, data
coils drop off with increasing angle orientation.
Figure 8: Graph showing the effect of the relative orientation of the data coils on the induced AC peak-to-
peak voltage that will be provided to the implant. (A) a plot showing the decrease in secondary-side voltage
with increasing distance (B) a graph of the effect of off-axis alignment on secondary-side induced voltage.
(C) A graph of the effect of altering the angle of the normal vectors to the coil area. All experiments were
performed at 20 MHz with a 3.6 V DC voltage source.
Composite System Performance
To test the composite system performance, we ran an experiment observing the data coils as
they received “11001100” 20 MHz signals from the DPSK circuit. In Figure 9 the four signals
shown are in sync with each other. The Green DPSK signal is putting out a “low” when transmitting
the 0° 20 MHz signal and a “high” for the 180° signal. It can clearly be seen when the 0° signal
switch phases to the 180° signal when the Green signal changes from “low” to “high” or vice versa.
This output then modulates the Purple and Pink signals. These are the data coil signals and an
obvious phase change can be seen in the picture when the Green DPSK signal changes from
“low” to “high” and back again. This is what the implant will see and this shows the proper signaling
of data through the DPSK circuit and Class E amplifier from the MCU to the coils.

Figure 9: The Gold signal represents the output 20 MHz signal from the DPSK circuit to the coils. The
Green is the same signal from Figure 6 and is the DPSK signal to change the phase of the 20 MHz signal.
The Purple and Pink signals on the bottom are the coil signals. With this information we can see correct
data transmission and a strong transmission connection between the data coils.
DISCUSSION
The uWalk Again design advances the field of epidural spinal cord stimulation research. The
layout of the GUI has been shown to be logical and intuitive in its operation. It is also much more
versatile and ergonomic compared to other programming devices on the market today. As such,
the uWalk Again will allow for and promote an increase in the volume of epidural spinal cord
stimulation research being performed simply as a result of its increase in usability.
Figures 8 and 9 show the successful transmission of data from the MCU to the implant wirelessly.
This is a key step in making spinal cord injury treatment plausible. This capability minimizes the
amount of hardware implanted into the patient while still including those components necessary
to accomplish the required versatility of stimulation. Reducing the amount of implanted hardware
promotes the longevity of the system. Furthermore, because of wireless communication, most of
the system components lie outside the body - which makes it easy to add or remove different
hardware components in the future to allow for system simplification or enhancement. Another
benefit of this external motherboard is seen in the ability to do simple tasks like change or
recharge the systems batteries. We have further reason to believe this system to be successful
because similar systems such as retinal prosthetics have also capitalized on the benefits of
wireless communication to control the implant from outside the body and demonstrated effective
treatment or therapy [16, 17].
In addition to wireless communication, the results from our coil dislocation studies are indicative
of successful future function of power and data transfer using the uWalk Again. When considering
power transfer, the implant-side circuitry must be supplied enough power to control all circuit

elements and to stimulate the spinal column with a sufficient current when commanded to do so.
From the design of the implant created by the Liu lab, this entails inducing a DC voltage of at least
10 V. Our data suggests that a secondary-side voltage of 10 V is reached at a distance of 10 mm.
Rat’s skin can range in depth from 6 mm to 12 mm, and as such, the fact that this voltage is
maintained while at a distance mirroring that found in future application suggests that power will
be adequately transferred through that depth. Furthermore, analysis of the distance-off-axis graph
suggests that this 10 V induced DC voltage will be maintained regardless of whether the coil axes
are centered. When moved to both the left and the right of center, induced voltage remained
around 10 V until the secondary-side coil began to overlap with the edge of the primary-side coil.
Thus, after implantation when the coil migrates away from its original implantation position, it
should still be capable of providing sufficient voltage to the implant given that the smaller 5 mm
diameter secondary-side coil remains within the larger 30.4 mm diameter primary side coil. Angle
effects do seem to provide a significant obstacle to sufficient power transfer to the implant side.
After rotating the axis only 30°, induced voltage had already dropped such that it was only 70%
of its value when the axes were aligned. As such, when implanting into rats, special consideration
needs to be given to ensuring proper angle alignment. The coil should be aligned such that the
normal vector to its area runs parallel with the normal vector from the rat’s skin. One possible way
to ensure this alignment is by placing the implant so that it rests along the rat’s rib cage. Using
this alignment, the secondary-side power coil would rest upon a hard surface that would prevent
axis rotation, and hence optimize our power transfer efficiency.
Successful data transfer alludes to future success of the composite uWalk Again system in vivo.
To adequately transfer data signals, the induced voltage must be significant enough to be greater
than any noise picked up by the secondary-side data coil. Experimentally, the signal must be
above the threshold noise limit of 100 mV. As long as the secondary-side induced voltage
surpasses 100 mV, data signals can be decoded. The induced voltage is greater than 200 mV
over the range from 4 mm separation to 10 mm separation, allowing the potential for data to be
transferred over that range. Next, the data coils axis alignment was shifted from 10 mm left of the
coil to 10 mm right of the coil. Induced voltage surpassed the threshold voltage from -6 mm to 6
mm, indicating the potential for data transfer over this range. Unlike the power coils, the data coils
do not plateau at a fixed voltage during this experiment. This makes sense intuitively as the data
coils were designed to have a low quality factor and high bandwidth, and as such are more prone
to have inhomogeneities in the induced magnetic field and the subsequent induced current within
the secondary-side coil. Finally, the data coils shared a similarly patterned decrease in voltage
with increasing angle as the power coils. Threshold voltage was surpassed for the data coils,
provided the secondary-side coil was not rotated greater than 45°. As such, the data coils would
benefit from the same surgical alignment necessitated by the power coils. This will not hinder
device function as both the power and data coils are intended to be used coaxially. This approach
has already been applied in the case of retinal prosthetics [16, 17].
CONCLUSION
The uWalk again is designed as a neural engineering platform that makes it easier for researchers
to perform effective and efficient experiments in spinal cord injury therapy on rats. We have
finished the design of a GUI that is superior in functionality to those that are currently on the
market. Secondly, we have designed power and data coils capable of providing the required
voltage to communicate with and power the implant. Lastly, we have assembled a composite
system that modulates the phase of a 20 MHz signal to effectively transmit data.
In our future work, our first goal is to create a printed circuit board (PCB) of the system that
incorporates the entire composite circuitry into a single PCB design. Next, we aim to assemble

the final system into a jacket that will carry this PCB. Finally, we aim to use this compiled system
for in vivo testing, where paralyzed rats will undergo epidural spinal cord stimulation controlled by
the uWalk Again. In this testing researchers will be able to use the implant for stimulation therapy
and collect recorded data from the rats wirelessly. The aim of this system is to make it easy for
the researcher to handle more than a few implants at the same time, and hence increase the
efficiency of spinal cord research. If conducting research is easier, there will be larger amounts of
data for the spinal cord injury research database. An ever expanding database can bring us one
step closer to finding out a cure for lifelong paralysis.
We anticipate the development of a more comprehensive program for the MCU to incorporate a
“closed loop” system so no actual adjustments are needed from a user would allow a more
realistic use of our system in the real world. Our work here gives a strong basis for all these
advancements and allows researchers to take modern technology further than has been seen
before.
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