Download Undergraduate Category: Engineering and Technology Degree Level: Bachelor of Science, Engineering

Undergraduate
Category: Engineering and Technology
Degree Level: Bachelor of Science, Engineering
Abstract ID# 1269
GlucoSense: A Portable, Non-Invasive Salivary Glucose Monitoring Device
Daniel LaBove, Christian Grenier, Matthew Stelma, Bradley Howe, Munachimso Ihionu
Faculty Advisor: Waleed Meleis, Ph.D.; Collaborators: Wenjun Zhang, Yunqing Du, Professor Ming L. Wang, Ph.D.
Abstract
Design
Results
A comparison between the sensor signal acquired by different circuits is examined
below in Figure 7. The plots shown in (a) are taken from the PhD students set-up, (b) is
our setup with no filtering, and (c) is a with our analog filtering. Figure 8 shows the
relative power of the acquired signals in the range of 0 to 10 Hz. The benefits of our
circuit’s analog filtering can be seen in Figure 7(c) and Figure 8(c). The GlucoSense
circuit performs better in both noise reduction and results in a faster settling time,
allowing our device to have higher signal accuracy and shorter measurement times.
The most common method of self-monitoring blood glucose levels for hundreds of millions of people
who suffer from diabetes requires invasive, painful finger pricking that can lead to bruising, loss of
sensitivity, and blood-borne infections. Due to these adverse effects, many patients do not take their
glucose measurement as often as they should, which can have dangerous repercussions. We present a
non-invasive method to monitor blood glucose levels that is accurate, affordable, and portable.
Our custom-designed device measures glucose concentration from a saliva sample detected by a
biosensor developed and patented by Northeastern professor Ming Wang and Ph.D. candidates
Wenjun Zhang and Yunqing Du. Our design features amperometric biasing and high signal-to-noise
ratio (SNR) amplification circuitry to obtain the signal from the biosensor reaction. Digital signal
processing is performed to obtain a salivary glucose concentration, which is then correlated to blood
glucose concentration. The blood glucose level is displayed in real-time on an LCD screen.
Figure 3: Block level Diagram of GlucoSense Analog System Architecture
Background
Our collaborators developed an electrochemical biosensor capable of detecting glucose in a solution at
much lower concentrations than traditional blood glucose sensors. This increased sensitivity makes it
viable for detection of glucose in saliva with precision comparable to that of today’s glucometers.
The biasing circuit in the bottom left of Figure 3 is what allows us to interface with the sensor and make the
measurement through amperometry. It applies a constant voltage across two of the electrodes to generate a
current from the third. This resulting current is detected by our circuit and can be seen in Figure 4 below.
Figure 7: Sensor signal acquired by
three different setups
Figure 4: Amperometric Measurement
Figure 1: Schematic diagram
of Electrochemical Sensor [1]
Figure 2: Correlation of signal
current to Glucose Concentration [1]
Figure 1 and 2 are from a publication in ELSEVIER submitted by the Ph.D. candidates in June of
2015 [2]. Figure 1 shows the common three-electrode structure of electrochemical strip sensors.
Figure 2 shows the correlation curve of signal current to salivary glucose concentration (mg/dL) for
the system the Ph.D. candidates currently use.
Figure 5: 0-10 Hz Power of Signal
The plot in Figure 5 shows that greater than 90% of signal power falls below 1Hz. The filter-amplifier
circuitry is comprised of 4 stages with a minimum total gain of 5*105 and an overall cutoff frequency of 1Hz.
The filter is a partial Bessel 4th order low pass filter with minimum distortion in the passband and 80
dB/decade attenuation outside it for excellent SNR. The last stage is an absolute value circuit that takes the
bipolar signal and makes it positive so it can be read by the Analog to Digital Converter (ADC). This circuit
is realized on the PCB shown below. Figure 6 below is a rendering of our custom PCB. The battery powered
and portable device is the culmination of many design iterations and is expected to increase SNR
significantly.
Our device boasts the same or better functionality and accuracy in a smaller, cheaper, and portable
package. The realization of electrode biasing circuitry and analog signal conditioning on one printed
circuit board (PCB) was essential to our goal. The sensor has high enough sensitivity to detect glucose
concentrations in the saliva, which are around 2 orders of magnitude lower than in the blood, but that
generates correspondingly small electrical signals on the order of 10-7 A). Thus, our design needed to
have excellent signal-to-noise ratio (SNR) in the frequency spectrum of interest.
Figure 8: Acquired sensor signal power,
0 to 10 Hz
Conclusion
Our device is capable of capturing the current signal (on the order of 10-7 A) from our collaborator’s
salivary glucose biosensor. Evaluating the power spectral density of the signal revealed that nearly all
of its energy is below 1 Hz. Our filter-amplifier circuitry, with its designed cutoff frequency of 1 Hz is
successful in attenuating undesired noise at 80 dB / decade. This filter design, along with careful
component selection, enables our device to attain its high signal to noise ratio as previously shown in
the results. In addition to the high SNR, our device allows the signal to settle more quickly. These two
components empower our device to be more accurate and have shorter measurement times compared
to the current evaluation equipment.
References
[1] Zhang, W., Wang, M. L. (2014). U.S. Patent No. 2014/0197042 A1. Washington, D.C: US Patent and Trademark
Office. http://www.google.com/patents/US20140197042
[2] Zhang, W., Du, Y., & Wang, M. (n.d.). Noninvasive glucose monitoring using saliva nano-biosensor. Sensing and BioSensing Research, 23-29.
Figure 6: PCB prototype