Project

# Title Team Members TA Documents Sponsor
47 Pitched Project (Professor Manuel Hernandez): Smart Cognitive-Motor Rehabilitation Mat for Remote Exercise Monitoring
 Adithya Balaji
Jashan Virdi
Scott Lopez
 Michael Gamota design_document1.pdf
final_paper1.pdf
grading_sheet1.pdf
presentation1.pptx
proposal1.pdf
video
Team Members:
- Adithya Balaji (abalaji5)
- Scott Lopez (slope22)
- Jashan Virdi (jvird2)

# Problem
Many older adults don’t have access to rehabilitation for Multiple Sclerosis compared to people of younger age groups. During the previous semester a group was able to create a prototype for a square stepping mat that provides useful feedback to a user in order to aid in rehabilitation; however, this prototype has some flaws that need to be addressed such as the (1) voltage from each square is interfering with others which reduces the accuracy of step detection and for (2) computers needing a USB connection for data transfer which reduces the portability of the mat.

# Solution
Our project proposes to enhance the existing rehabilitation mat by focusing on two key areas:
Optimizing and increasing step detection accuracy through improved sensor integration and signal processing.
Developing a wireless, low-power system for operation, using relevant communication protocols and energy-efficient components.
# Solution Components

## Sensing Subsystem
Pressure-sensitive sensors (e.g., Velostat-based) for detecting step position and timing.
The main work here will be to iterate on and develop signal conditioning circuitry for improved step detection accuracy. Additionally, an area of research will be to explore the usage of materials other than copper strips to prevent voltages from each square interfering with other squares.

## Microcontroller subsystem
Microcontroller (ESP32-S2-mini-1) to manage sensor data and process step events. This specific microprocessor is used because it has an integrated WiFi antenna for WiFi communications with mobile devices. The microprocessor enables real-time control of visual and auditory feedback for the user.

## Power Management subsystem
The power management subsystem will send and regulate power to the microcontroller and sensing subsystems, and the LEDs on the mat.

## Wireless Communication Subsystem
Integration of Wi-Fi or Bluetooth Low Energy (BLE) module for wireless data transmission.
Low-latency data transfer protocol for real-time communication. Currently, they have data transfer locally using LAN but using wired connections, which is why we will be introducing BLE to reduce wired connections and improve portability.

## Custom PCB
Custom PCB integrating the microcontroller, sensor interfaces, and power management circuits to ensure compact and reliable operation. The main focus here will be to accommodate the wireless module that will be implemented for this project.

# Criterion For Success
Achieve a step detection accuracy of at least 95% (larger than previous prototype aim of 90%), taking into account unexpected variances due to variations in step styles and uneven pressure applications on the mat
Wireless communication module with low latency for remote operation to eliminate the need for wired data transfer
Successful data processing and feedback delivery from the smart mat during cognitive-motor exercise routines

Automatic Piano Tuner

Joseph Babbo, Colin Wallace, Riley Woodson

Automatic Piano Tuner

Featured Project

# Automatic Piano Tuner

Team Members:

- Colin Wallace (colinpw2)

- Riley Woodson (rileycw2)

- Joseph Babbo (jbabbo2)

# Problem

Piano tuning is a time-consuming and expensive process. An average piano tuning will cost in the $100 - $200 range and a piano will have to be retuned multiple times to maintain the correct pitch. Due to the strength required to alter the piano pegs it is also something that is difficult for the less physically able to accomplish.

# Solution

We hope to bring piano tuning to the masses by creating an easy to use product which will be able to automatically tune a piano by giving the key as input alongside playing the key to get the pitch differential and automatically turning the piano pegs until they reach the correct note.

# Solution Components

## Subsystem 1 - Motor Assembly

A standard tuning pin requires 8-14 nm of torque to successfully tune. We will thus need to create a motor assembly that is able to produce enough torque to rotate standard tuning pins.

## Subsystem 2 - Frequency Detector/Tuner

The device will use a microphone to gather audio measurements. Then a microprocessor processes the audio data to detect the pitch and determine the difference from the desired frequency. This can then generate instructions for the motor; direction to turn pegs and amount to turn it by.

## Subsystem 3 - User Interface/Display Panel

A small but intuitive display and button configuration can be used for this device. It will be required for the user to set the key being played using buttons on the device and reading the output of the display. As the device will tune by itself after hearing the tone, all that is required to display is the current key and octave. A couple of buttons will suffice to be able to cycle up and down keys and octaves.

## Subsystem 4 - Replaceable Battery/Power Supply

Every commercial product should use standard replaceable batteries, or provide a way for easy charging. As we want to develop a handheld device, so that the device doesn’t have to drag power wires into the piano, we will need a rechargeable battery pack.

# Criterion For Success

The aim of the Automatic Piano Tuner is to allow the user to automatically tune piano strings based on a key input alongside playing a note. We have several goals to help us meet this aim:

- Measure pitch accurately, test against known good pitches

- Motor generates enough torque to turn the pegs on a piano

- Tuner turns correctly depending on pitch

- Easy tuning of a piano by a single untrained person

Project Videos