Project

# Title Team Members TA Documents Sponsor
14 PocketScope
Aaron Holl
Caleb Peach
Rohan Nagaraj
Lukas Dumasius design_document1.pdf
final_paper1.pdf
photo1.jpg
presentation1.pptx
proposal1.pdf
video
# Team Members:
- Rohan Nagaraj (rohan14)
- Aaron Holl (amholl2)
- Caleb Peach (calebrp2)

# Problem

Most signal generators and oscilloscopes are limited to large laboratory instruments. They are also very costly and usually reserved for universities and company labs. Currently, there is no cheap, pocket-sized, convenient, and compact signal generator/oscilloscope designed for electricians, hobbyists, and engineers to use in the field while troubleshooting electrical problems.

# Solution

With advancements in microcontroller technology (specifically cheaper, smaller, and more powerful devices) our team can create a handheld, pocket-sized, two-in-one oscilloscope and signal generator. It will include an OLED screen to display a user interface with a time-versus-voltage/current plot, options for generated signals, and other features for quick measurements such as a voltmeter and ohmmeter. It will also include software based analysis tools such as FFT, curve-fitting, and the ability to export data as a CSV to a computer.

Software, ADC, and DAC functionality can be handled through an ESP32 or a similar microcontroller. Basic circuit design using op-amps and voltage dividers can be used to scale larger input signals down to ranges acceptable for the microcontroller’s ADC. The user interface software can be implemented using C and Python.

# Solution Components

## Subsystem 1: Voltage and Current vs Time

This subsystem will take a real-world signal ranging from [-20 V, 20 V] and scale it down to a 0 to 3.3 V range since this is the typical input range for a microcontroller’s ADC. We can easily do this mathematically by dividing the function by a scaling factor (implemented in a circuit with a voltage divider) and adding an offset (using an op-amp adder circuit) to get it in the suitable range. We will use a LM741 op amp to do this since it is one of the most popular and widely used op-amps in circuit design.

Our microcontroller will be an ESP-32 or STM-32 since it has an onboard ADC that can read voltages in the 0 to 3.3 V range. It also has the computing ability for small scale graphics for the waveforms vs time and can handle other DSP intensive threads.

## Subsystem 2: LCD Touchscreen

This subsystem will display our application code written in C, Python, and possibly Arduino. It will display the voltage/current waveforms, show menus for signal generation, display spectrogram readings, show analysis tool details, and provide major control over the device. We will use a LCD capacitive touch bare display which communicates with our microcontroller over SPI. Adafruit provides a suitable display (https://www.adafruit.com/product/2090) that can be used for this.

## Subsystem 3: USB-C Charging and Computer Exportability
- USB-C PCB mount on our custom PCB will allow for microcontroller programming, battery re-charging, and allow the microcontroller to export a .CSV file to a connected computer
- USB-C will support USB 2.0 at 12 Mbps since this is fast enough to import CSV data and machine code data to the microcontroller without having to worry about impedance controlled traces on D+ and D- lines.
- The UJ20-C-H-C-4-SMT-TR (USB-C PCB mount) will allow us to have this connectivity
- USB-C also natively supports a 5V power supply over the VBUS terminal, so we can use this to charge a rechargeable lithium ion battery that allows the device to be mobile

## Subsystem 4: Time varying FFT (Spectrogram) of input signal
- In software, we will implement a short time Fourier Transform algorithm to show a real-time spectrogram of the input signal
- We do this by sampling the signal in short windows and taking the FFT of the instantaneous waveform, displaying it, and then repeating the process in real time such that the user can accurately see how the frequency components of the signal change over time

## Subsystem 5: Waveform Signal Generation
User will be able to choose between the following pre defined waveform shapes we support:
- Rectangle Wave
- Triangle Wave
- Sine Wave
- Sawtooth Wave
- Pulse Signal
- Gaussian Noise function

This will be generated by the microcontroller (ESP-32 or STM32) via PWM through a GPIO pin and amplified to a 0 to 5 V range through an op-amp amplifier (again using the LM741). The frequency, phase, duty cycle, and amplitude of the waveforms can be fully customizable by the user.

## Subsystem 6: Machine Learning Algorithm for Input Waveform Analysis
- Implement a machine-learning-based parameter estimation algorithm using gradient descent to fit mathematical models to measured input waveforms
- We will base our algorithm on a Nth order polynomial fit (where N is a parametrized by the user, giving more accuracy on the fit)
- This can be used to characterize transient behavior, dynamic response, and system properties related to impulse and frequency response

# Criterion For Success
- The device needs to be portable such that the entire structure can fit comfortably in your hand and ideally within a pants or jacket pocket.
- The device needs to have a battery system that can support at least a couple hours of use, in order to serve the needs of the users who may be unable to plug the device into an outlet while using it.
- The device needs to be able to read any arbitrary signal within a -20 V to +20 V range and display them accurately on the screen.
- The screen needs to be easy to read and the interface must be concise and unobtrusive. Also the screen should be sturdy enough to be used frequently without fear of damage.
- The device needs to have an overvoltage protection system that prevents the circuits from burning out if a high voltage signal is put across the input pins.
- The metal pins that read the voltage signal must be adjustable in gap width and/or compatible with a set of detachable probes that can be placed on any two points of a target circuit.

# Alternatives
Small oscilloscopes have already been implemented and manufactured. Our solution is unique as we will implement our ideas in a cost efficient, energy efficient, space efficient manner for low voltage inputs, which is not currently available (current solutions are too big, too expensive, or too energy efficient for low voltage systems).

https://www.digikey.com/en/products/detail/owon-technology-lilliput-electronics-usa-inc/HDS1021M-N/10667422?gclsrc=aw.ds&gad_source=1&gad_campaignid=20228387720&gbraid=0AAAAADrbLlg8c4vRvwakbVmhST4aZ3Gqw&gclid=Cj0KCQiA4eHLBhCzARIsAJ2NZoIiJi_xpcOgqdLhCqINMhACTyUvaBxYUS1mqWpOtyJXAPze3dIfL64aAkQHEALw_wcB

STRE&M: Automated Urinalysis (Pitched Project)

Gage Gulley, Adrian Jimenez, Yichi Zhang

STRE&M: Automated Urinalysis (Pitched Project)

Featured Project

Team Members:

- Gage Gulley (ggulley2)

- Adrian Jimenez (adrianj2)

- Yichi Zhang (yichi7)

The STRE&M: Automated Urinalysis project was pitched by Mukul Govande and Ryan Monjazeb in conjunction with the Carle Illinois College of Medicine.

#Problem:

Urine tests are critical tools used in medicine to detect and manage chronic diseases. These tests are often over the span of 24 hours and require a patient to collect their own sample and return it to a lab. With this inconvenience in current procedures, many patients do not get tested often, which makes it difficult for care providers to catch illnesses quickly.

The tedious process of going to a lab for urinalysis creates a demand for an “all-in-one” automated system capable of performing this urinalysis, and this is where the STRE&M device comes in. The current prototype is capable of collecting a sample and pushing it to a viewing window. However, once it gets to the viewing window there is currently not an automated way to analyze the sample without manually looking through a microscope, which greatly reduces throughput. Our challenge is to find a way to automate the data collection from a sample and provide an interface for a medical professional to view the results.

# Solution

Our solution is to build an imaging system with integrated microscopy and absorption spectroscopy that is capable of transferring the captured images to a server. When the sample is collected through the initial prototype our device will magnify and capture the sample as well as utilize an absorbance sensor to identify and quantify the casts, bacteria, and cells that are in the sample. These images will then be transferred and uploaded to a server for analysis. We will then integrate our device into the existing prototype.

# Solution Components

## Subsystem1 (Light Source)

We will use a light source that can vary its wavelengths from 190-400 nm with a sampling interval of 5 nm to allow for spectroscopy analysis of the urine sample.

## Subsystem2 (Digital Microscope)

This subsystem will consist of a compact microscope with auto-focus, at least 100x magnification, and have a digital shutter trigger.

## Subsystem3 (Absorbance Sensor)

To get the spectroscopy analysis, we also need to have an absorbance sensor to collect the light that passes through the urine sample. Therefore, an absorbance sensor is installed right behind the light source to get the spectrum of the urine sample.

## Subsystem4 (Control Unit)

The control system will consist of a microcontroller. The microcontroller will be able to get data from the microscope and the absorbance sensor and send data to the server. We will also write code for the microcontroller to control the light source. ESP32-S3-WROOM-1 will be used as our microcontroller since it has a built-in WIFI module.

## Subsystem5 (Power system)

The power system is mainly used to power the microcontroller. A 9-V battery will be used to power the microcontroller.

# Criterion For Success

- The overall project can be integrated into the existing STRE&M prototype.

- There should be wireless transfer of images and data to a user-interface (either phone or computer) for interpretation

- The system should be housed in a water-resistant covering with dimensions less than 6 x 4 x 4 inches

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