Project

# Title Team Members TA Documents Sponsor
18 Acoustic Stimulation to Improve Sleep
 Bakry Abdalla
John Ludeke
Sid Gurumurthi
 Mingrui Liu design_document1.pdf
proposal1.pdf
 Sound Sleep
# Acoustic Stimulation to Improve Sleep

Team Members:
- Abdalla, Bakry (bakryha2)
- Gurumurthi, Sid (sguru2)
- Ludeke, John (jludeke2)

# Problem

Certain people experience poor quality sleep as they age or develop sleep disorders because they do not spend enough time in slow wave sleep (SWS). While there are data-first solutions currently available to the public, they are expensive.

# Solution

Closed-loop auditory simulation has been shown through research to amplify the oscillations of SWS. When it is time to sleep, users will put a wearable device on their head. The device will consist of an EEG headband with dry electrodes to measure brain activity which will be connected to an all-purpose, custom PCB that integrates the EEG front-end, microcontroller, audio driver, and power management circuitry.

The processor detects slow wave sleep and identifies slow wave oscillations. When these waves are detected, the system delivers short, precisely timed bursts of pink noise through an integrated speaker. Data insights about the user’s sleep patterns are delivered via a user-facing application.

All of this while being cheaper than what is currently available.

# Solution Components

## Subsystem 1 – EEG Headband

We will be using a commercially available EEG Headband, the OpenBCI EEG Headband Kit. This includes the headband, electrodes, and cables carrying the analog signal.

Components:
- OpenBCI EEG Headband: https://shop.openbci.com/products/openbci-eeg-headband-kit
- Ag-AgCl Electrodes
- Earclip & snap cables

## Subsystem 2 – Signal Processor

Takes in analog signals, denoises and amplifies, digitally processes, and then outputs.
The signal processing subsystem is responsible for performing the core functionality of a commercial EEG interface such as the OpenBCI Cyton, but at a lesser cost. It receives raw analog EEG signals from the headband electrodes and converts them into digitized, clean EEG data suitable for downstream analysis. It would perform amplification of weak analog electric signals followed by analog filtering to limit bandwidth to EEG-relevant bands and prevent aliasing before analog-to-digital conversion. Following digitization, the subsystem performs digital signal processing, including bandpass and notch filtering, for noise and artifact reduction. An accelerometer would be incorporated to remove spikes and noise in EEG data at significant motion events.

Components:
- Analog front end: Texas Instruments ADS1299
- Microcontroller: PIC32MX250F128B
- Wireless transmission of data: RFduino BLE radio module (RFD22301)
- Triple-Axis Accelerometer: LIS3DH
- Resistors: COM-10969 (ECE Supply Store)
- Capacitors: 75-562R5HKD10, 330820 (ECE Supply Store)
- JFET Input Operational Amplifier: TL082CP (ECE Supply Store)
- Standard Clock Oscillators 2.048MHz: C3291-2.048

## Subsystem 3 – Audio Output

After receiving the processed audio signals from the signal processor's subsystem, this subsystem will provide the data as input to an algorithm which decides whether or not to play a certain frequency of noise through the preferred audio output device (default will be speaker). The algorithm makes this decision by detecting whether the brain signals indicate short wave sleep is occurring.

Components:
- A special algorithm to detect short wave sleep (https://pubmed.ncbi.nlm.nih.gov/25637866/)
- One small integrated speaker (665-AST03008MRR)

## Subsystem 4 – Power Delivery

To provide power for the entire system, a power circuit is integrated into the PCB. This circuit manages battery charging and voltage regulation while minimizing heat dissipation for user comfort.

Components:
- 2 AAA batteries: EN92
- Voltage regulator: LM350T
- Capacitors: 75-562R5HKD10
- On/off switch: MULTICOMP 1MS3T1B1M1QE
- Power jack: 163-4013

## Subsystem 5 – User-Facing Application

To improve usability, the User-Facing Application will give the end user insights into their sleep using standard sleep metrics. Specifically, it will tell the user their time spent not sleeping, in REM sleep, light sleep, and deep sleep.

We can use a React Native frontend for compatibility with Android and iOS. We can run a lightweight ML model on-device with Python to determine the state of sleep (using libraries like FFT and bandpower). For the backend, Firebase can be used to store our data, which will come in via Bluetooth.

Components:
- React Native
- Firebase

# Criterion For Success

- Headset remains comfortable (4/5 people would be okay wearing the device to sleep)
- Signal Processor successfully amplifies and denoises signal
- Signal Processor successfully converts the analog signal into a digital one
- Audio Output gives audio in phase with EEG waves to maximize effectiveness
- Audio Output correctly adjusts audio in correspondence to the input signal from the Signal Processor
- Power Delivery gives enough battery power for the device to last at least 10 hours
- Power Delivery remains cool and comfortable for sleep
- User-Facing Application is intuitive (4/5 people would download the app)
- User-Facing Application shows accurate, historical data from the user’s headband
- User-Facing Application correctly classifies phases of the user’s sleep
- The entire system is easy to use (a new user can figure it out without instruction)
- The entire system works seamlessly

Tesla Coil Guitar Amp

David Mengel, Griffin Rzonca

Featured Project

# Tesla Coil Guitar Amp

Team Members:

* Griffin Rzonca (grzonca2)

* David Mengel (dmengel3)

# Problem:

Musicians are known for their affinity for flashy and creative displays and playing styles, especially during their live performances. One of the best ways to foster this creativity and allow artists to express themselves is a new type of amp that is both visually stunning and sonically interesting.

# Solution:

We propose a guitar amp that uses a Tesla coil to create a unique tone and dazzling visuals to go along with it. The amp will take the input from an electric guitar and use this to change the frequency of a tesla coil's sparks onto a grounding rod, creating a tone that matches that of the guitar.

# Solution Components:

## Audio Input and Frequency Processing -

This will convert the output of the guitar into a square wave to be fed as a driver for the tesla coil. This can be done using a network of op-amps. We will also use an LED and phototransistor to separate the user from the rest of the circuit, so that they have no direct connection to any high voltage circuitry. In order to operate our tesla coil, we need to drive it at its resonant frequency. Initial calculations and research have this value somewhere around 100kHz. The ESP32 microcontroller can create up to 40MHz, so we will use this to drive our circuit. In order to output different notes, we will use pulses of the resonant frequency, with the pulses at the frequency of the desired note.

## Solid-state switching -

We will use semiconductor switching rather than the comparably popular air-gap switching, as this poses less of a safety issue and is more reliable and modifiable. We will use a microcontroller, an ESP 32, to control an IR2110 gate driver IC and two to four IGBTs held high or low in order to complete the circuit as the coil triggers, acting in place of the air gap switch. These can all be included on our PCB.

## Power Supply -

We will use a 120V AC input to power the tesla coil and most likely a neon sign transformer if needed to step up the voltage to power our coil.

## Tesla Coil -

Consists of a few wire loops on the primary side and a 100-turn coil of copper wire in order to step up voltage for spark generation. Will also require a toroidal loop of PVC wrapped in aluminum foil in order to properly shape the electric field for optimal arcing. These pieces can be modular for easy storage and transport.

## Grounding rod -

All sparks will be directed onto a grounded metal rod 3-5cm from the coil. The rest of the circuit will use a separate neutral to further protect against damage. If underground cable concerns exist, we can call an Ameren inspector when we test the coil to mark any buried cables to ensure our grounding rod is placed in a safe location.

## Safety -

Tesla coils have been built for senior design in the past, and as noted by TAs, there are several safety precautions needed for this project to work. We reviewed guidelines from dozens of recorded tesla coil builds and determined the following precautions:

* The tesla coil will never be turned on indoors, it will be tested outside with multiple group members present using an outdoor wall outlet, with cones to create a circle of safety to keep bystanders away.

* We will keep everyone at least 10ft away while the coil is active.

* The voltage can reach up to 100kV (albeit low current) so all sparks will be directed onto a grounding rod 3-5cm away, as a general rule of thumb is each 30kV can bridge a 1cm gap.

* The power supply (120-240V) components will be built and tested in the power electronics lab.

* The coil will have an emergency stop button and a fuse at the power supply.

* The cable from the guitar will use a phototransistor so that the user is not connected to a circuit with any power electronics.

# Criterion for Success:

To consider this project successful, we would like to see:

* No safety violations or injuries.

* A tesla coil that produces small visible and audible 3-5cm sparks to our ground rod.

* The coil can play several different notes and tones.

* The coil can take input from the guitar and will play the corresponding notes.

Project Videos