Project

# Title Team Members TA Documents Sponsor
89 Screentime Habit Correction Headband
 Colin Moy
Jake Chen
Zhiyuan Chen
 Weijie Liang proposal1.pdf
# Screentime Habit Correction Headband

Team Members:
- Jake Chen (jakezc2)
- Colin Moy (colincm2)
- Zhiyuan Chen (zc67)

# Problem

With the majority of people having more and more access to screens, many people spend a large amount of time in front of a desktop computer. After some time, their posture deteriorates into slouching and they can end up sitting too close to the screen. With poor posture, the neck and back can be strained and can be detrimental to long term health. Additionally, when sitting too close to the screen, the eyes can get dry from not blinking enough and get strained. Even if you have good posture and distance, sitting at the screen for too long can also strain your eyes and back.

# Solution

Our Screentime Habit Correction Headband will allow the user to track their habits during screentime and correct bad habits. By using a headband with two sensors, the device will be able to track the posture of the user based on the calibration done when the device is powered on, as well as the distance between the user and the screen they are looking at. The device will send feedback to the user using vibrations, a speaker, and a LED when the user’s posture deteriorates or they get too close to the screen. In addition, the device will also send feedback to the user if they have been sitting in front of the screen for too long. The headband will be lightweight and will be wired to a box that contains the bulk of the electronics as well as the rechargeable battery for the device. In addition to the physical device, there will also be an app that can track screentime and posture data from the device using Bluetooth.

# Solution Components

## Power

Our power subsystem will contain a Lithium-Polymer battery with a TP4056 charging module. It will also be able to regulate and step down voltages using an LDO and buck converters and send them to all the other components in the device.

Lithium Polymer battery,
TP4056,
LDL1117-3.3


## Sensors

There are two sensors on the device. The first sensor is the ICM-42670-P, which is an IMU that is able to sense position and orientation in order to tell the MCU to send feedback when the user’s posture is bad. The second sensor is the VL53L0X Time-of-Flight Sensor, which is able to detect the distance from the user to a screen. This sensor will tell the MCU to send feedback when the user is too close to their screen.

ICM-42670-P,
VL53L0X


## Feedback

The feedback subsystem consists of a vibration motor (Mini ERM), speaker (Piezoelectric Buzzer), and two LEDs. There are two cases when the feedback subsystem will activate. One case is when the user is either slouching or too close to the screen. The other case is when the user has been sitting in front of the screen for too long. Each case will have their own dedicated LED, while both cases will activate the vibration motor and speaker.

Coin vibration motor,
Piezoelectric Buzzer,
2 LEDs


## Processing

The processing system consists of the microcontroller. The MCU that we will be using is the ESP32. It will use sensor data as well as its own timer to determine when to send feedback to the user based on time of exposure to a screen, distance to a screen, and posture. The MCU will also manipulate the sensor data so the two cases won’t interfere with each other. In addition, the MCU will have Bluetooth capabilities that will be able to communicate with the app and allow it to track data.

ESP32-S3


## App

The app will measure a lot of data from the sensors using Bluetooth. The app will display the time it takes before the user’s posture deteriorates or the screen gets too close to the user, the amount of times this occurs, and the general data such as daily screentime. The app will also have a graph of all these statistics that it can track over the course of a week.


## Design
The headband will have a switch that is used to turn the device on and off, with device calibration when switched on. The headband also will only contain the two sensors and the vibration motor, and the headband will be wired to a separate box, meant to be placed on the desk. The box will hold everything else, from the LEDs, speaker, microcontroller, and power subsystem.


# Criterion For Success

## Headband:


Accurate distance measurements from headband to screen transmitted to stationary module (±0.5 in)

Lightweight (weight limit of 100g)

Alarm activates when distance to screen is less than 12 inches

Alarm activates when IMU detects the user’s head looking down at an angle of over 15 degrees for 3 seconds or when IMU detects it has been lowered by at least 2 inches for 3 seconds

Alarm activates when user has been sitting for at least 60 minutes

Alarm is turned off when user fixes posture to ±0.5 inches of normal position and is further than 12 inches from the screen

Fast calibration for posture (Under 15 seconds)

Switch can power the device off and on, as well as calibrate when switched on

Device operates for at least 2 hours on a single battery charge

## App:


Values displayed on the app match the values output by the microcontroller (average time from initial screen exposure to unsafe screen distance, average time from initially sitting down to bad posture)

Previous recorded values can be displayed in a graph

## Box:

Battery is chargeable by USB-C

Bracelet Aid for deaf people/hard of hearing

Aarushi Biswas, Yash Gupta, Anit Kapoor

Bracelet Aid for deaf people/hard of hearing

Featured Project

# PROJECT TITLE: Bracelet Aid for deaf people/hard of hearing

# TEAM MEMBERS:

- Aarushi Biswas (abiswas7)

- Anit Kapoor (anityak3)

- Yash Gupta (yashg3)

# PROBLEM

We are constantly hearing sounds around us that notify us of events occurring, such as doorbells, fire alarms, phone calls, alarms, or vehicle horns. These sounds are not enough to catch the attention of a d/Deaf person and sometimes can be serious (emergency/fire alarms) and would require the instant attention of the person. In addition, there are several other small sounds produced by devices in our everyday lives such as washing machines, stoves, microwaves, ovens, etc. that cannot be identified by d/Deaf people unless they are observing these machines constantly.

Many people in the d/Deaf community combat some of these problems such as the doorbell by installing devices that will cause the light in a room to flicker. However, these devices are generally not installed in all rooms and will also obviously not be able to notify people if they are asleep. Another common solution is purchasing devices like smartwatches that can interact with their mobile phones to notify them of their surroundings, however, these smartwatches are usually expensive, do not fulfill all their needs, and require nightly charging cycles that diminish their usefulness in the face of the aforementioned issues.

# SOLUTION

A low-cost bracelet aid with the ability to convert sounds into haptic feedback in the form of vibrations will be able to give d/Deaf people the independence of recognizing notification sounds around them. The bracelet will recognize some of these sounds and create different vibration patterns to catch the attention of the wearer as well as inform them of the cause of the notification. Additionally, there will be a visual component to the bracelet in the form of an OLED display which will provide visual cues in the form of emojis. The bracelet will also have buttons for the purpose of stopping the vibration and showing the battery on the OLED.

For instance, when the doorbell rings, the bracelet will pick up the doorbell sound after filtering out any other unnecessary background noise. On recognizing the doorbell sound, the bracelet will vibrate with the pattern associated with the sound in question which might be something like alternating between strong vibrations and pauses. The OLED display will also additionally show a house emoji to denote that the house doorbell is ringing.

# SOLUTION COMPONENTS

Based on this solution we have identified that we need the following components:

- INMP441 (Microphone Component)

- Brushed ERM (Vibration Motor)

- Powerboost 1000 (Power subsystem)

- 1000 mAh LiPo battery x 2 (hot swappable)

- SSD1306 (OLED display)

## SUBSYSTEM 1 → SOUND DETECTION SUBSYSTEM

This subsystem will consist of a microphone and will be responsible for picking up sounds from the environment and conducting a real-time FFT on them. After this, we will filter out lower frequencies and use a frequency-matching algorithm to infer if a pre-programmed sound was picked up by the microphone. This inference will be outputted to the main control unit in real-time.

## SUBSYSTEM 2 → VIBRATION SUBSYSTEM

This subsystem will be responsible for vibrating the bracelet on the wearer’s wrist. Using the vibration motor mentioned above, we should have a frequency range of 30Hz~500Hz, which should allow for the generation of a variety of distinguishable patterns. This subsystem will be responsible for the generation of the patterns and control of the motor, as well as prompting the Display subsystem to visualize the type of notification detected.

## SUBSYSTEM 3 → DISPLAY SUBSYSTEM

The Display subsystem will act as a set of visual cues in addition to the vibrations, as well as a visual feedback system for user interactions. This system should not draw a lot of power as it will be active only when prompted by user interaction or by a recognized sound. Both of these scenarios are relatively uncommon over the course of a day, which means that the average power draw for our device should still remain low.

## SUBSYSTEM 4 → USER INTERACTION SUBSYSTEM

This subsystem is responsible for the interaction of the user with the bracelet. This subsystem will include a set of buttons for tasks such as checking the charge left on the battery or turning off a notification. Checking the charge will also display the charge on the OLED display thus interacting and controlling the display subsystem as well.

## SUBSYSTEM 5 → POWER SUBSYSTEM

This subsystem is responsible for powering the device. One of our success criteria is that we want long battery life and low downtime. In order to achieve this we will be using a power boost circuit in conjunction with two rechargeable 1000 mAh batteries. While one is charging the other can be used so the user doesn’t have to go without the device for more than a few seconds at a time. We are expecting our device to use anywhere from 20-50mA which would mean we get an effective use time of more than a day. The power boost circuit and LiPo battery’s JST connector allow the user to secure and quick battery swaps as well.

# CRITERION FOR SUCCESS

- The bracelet should accurately identify only the crucial sounds in the wearer’s environment with each type of sound having a fixed unique vibration + LED pattern associated with it

- The vibration patterns should be distinctly recognizable by the wearer

- Should be relatively low cost

- Should have prolonged battery life (so the power should focus on only the use case of converting sound to vibration)

- Should have a small profile and a sleek form factor

Project Videos