## Inspiration

Smart watches have centered around the health of their users for over a decade. Fitness apps have provided the ability to track calorie burning and heart rate for athletes, and those pursuing the ideal physique. At the other end of the spectrum, medical apps provide the ability for diabetes patients and the elderly to track and detect concerning medical phenomena. However, both these use cases miss the major demographic between them: middle class and blue collar workers. For construction workers, contractors, farmers, and millions of other manual laborers, the extreme highs and lows of biological tracking are not necessary, yet these apps are incapable of keeping them safe and healthy in their physically demanding workplaces. Clock In provides an answer.

## What it does

The moment a worker *"Clocks In"* at the start of their day, they can open our app on their watch to start tracking them. Clock In tracks several health and safety risk factors throughout the work day, and detects any major hazards or accidents that could affect the user. It tracks personal factors, such as heart rate, blood oxygen level, physical trauma via an accelerometer, atrial fibrillation, and arrhythmia. It also tracks environmental factors, such as temperature and humidity.

Typically, Clock In will invalidate and delete this data after a few hours, but the moment that a workplace hazard or accident strikes, **Clock In takes a snapshot of the user's working conditions** at the time of the incident and in the hours leading up to it. In this way, Clock In acts like a *dash cam for the body*, freezing the data surrounding an incident for later investigation.

Clock In provides workers with the ability to record unsafe or inhumane working conditions, providing numerical, indisputable evidence in the case of mistreatment by their employer. In the case of a severe accident, this data can provide valuable proof of mistreatment by an employer, assisting the worker's case.

## How we built it

Using Zepp's OS and the vast array of sensors on the Amazfit Smart-Watch, we monitor and protect against 3 kinds of trigger events.

**immediate triggers**

* High-speed impact
* Loud Noise
* Self-Recorded Emergency

**short term triggers**

* Abnormal Heart Rate
* Low VO2 max

**long term triggers**

* Unsafe temperatures
* Unsafe altitudes

## Challenges we ran into

Use of an unfamiliar API with mixed documentation and a foreign framework. Luckily, the Zepp dev team gave us 24-hour support, constantly helping with documentation and hardware issues.

## Accomplishments that we're proud of

Our technology will improve safety accountability in the workplace by ensuring all sides are held accountable for workplace mishaps.

We are proud of the high-speed impact detection. A user can unnaturally jerk their arm and the watch immediately responds.

We are also proud of our ability complete a project despite arriving late to the hackathon and having other obligations during the event.

## What we learned

## What's next for Clock In

**Workplace injuries no more**

Suppose an employee was injured. There is little certainty that their medical bills will be

We hope to implement preventative measures to stop workplace injuries before they happen. By notifying workers when they are susceptible to stroke, drowsiness, and immune system failure we can prevent a hospital visit that is both expensive to the employee and the employer.

In the future, we hope to add more trackable factors to our product, such as air quality and elevation.
## Inspiration

In the United States, every 11 seconds, a senior is treated in the emergency room for a fall. Every 19 minutes, an older adult dies from a fall, directly or indirectly. Deteriorating balance is one of the direct causes of falling in seniors. This epidemic will only increase, as the senior population will double by 2060. While we can’t prevent the effects of aging, we can slow down this process of deterioration. Our mission is to create a solution to senior falls with Smart Soles, a shoe sole insert wearable and companion mobile app that aims to improve senior health by tracking balance, tracking number of steps walked, and recommending senior-specific exercises to improve balance and overall mobility.

## What it does

Smart Soles enables seniors to improve their balance and stability by interpreting user data to generate personalized health reports and recommend senior-specific exercises. In addition, academic research has indicated that seniors are recommended to walk 7,000 to 10,000 steps/day. We aim to offer seniors an intuitive and more discrete form of tracking their steps through Smart Soles.

## How we built it

The general design of Smart Soles consists of a shoe sole that has Force Sensing Resistors (FSRs) embedded on it. These FSRs will be monitored by a microcontroller and take pressure readings to take balance and mobility metrics. This data is sent to the user’s smartphone, via a web app to Google App Engine and then to our computer for processing. Afterwards, the output data is used to generate a report whether the user has a good or bad balance.

## Challenges we ran into

**Bluetooth Connectivity**
Despite hours spent on attempting to connect the Arduino Uno and our mobile application directly via Bluetooth, we were unable to maintain a **steady connection**, even though we can transmit the data between the devices. We believe this is due to our hardware, since our HC05 module uses Bluetooth 2.0 which is quite outdated and is not compatible with iOS devices. The problem may also be that the module itself is faulty. To work around this, we can upload the data to the Google Cloud, send it to a local machine for processing, and then send it to the user’s mobile app. We would attempt to rectify this problem by upgrading our hardware to be Bluetooth 4.0 (BLE) compatible.

**Step Counting**
We intended to use a three-axis accelerometer to count the user’s steps as they wore the sole. However, due to the final form factor of the sole and its inability to fit inside a shoe, we were unable to implement this feature.

**Exercise Repository**
Due to a significant time crunch, we were unable to implement this feature. We intended to create a database of exercise videos to recommend to the user. These recommendations would also be based on the balance score of the user.

## Accomplishments that we’re proud of

We accomplished a 65% success rate with our Recurrent Neural Network model and this was our very first time using machine learning! We also successfully put together a preliminary functioning prototype that can capture the pressure distribution.

## What we learned

This hackathon was all new experience to us. We learned about:

* FSR data and signal processing
* Data transmission between devices via Bluetooth
* Machine learning
* Google App Engine

## What's next for Smart Soles

* Bluetooth 4.0 connection to smartphones
* More data points to train our machine learning model
* Quantitative balance score system
## Inspiration

Members of our team know multiple people who suffer from permanent or partial paralysis. We wanted to build something that could be fun to develop and use, but at the same time make a real impact in people's everyday lives. We also wanted to make an affordable solution, as most solutions to paralysis cost thousands and are inaccessible. We wanted something that was modular, that we could 3rd print and also make open source for others to use.

## What it does and how we built it

The main component is a bionic hand assistant called The PulseGrip. We used an ECG sensor in order to detect electrical signals. When it detects your muscles are trying to close your hand it uses a servo motor in order to close your hand around an object (a foam baseball for example). If it stops detecting a signal (you're no longer trying to close) it will loosen your hand back to a natural resting position. Along with this at all times it sends a signal through websockets to our Amazon EC2 server and game. This is stored on a MongoDB database, using API requests we can communicate between our games, server and PostGrip. We can track live motor speed, angles, and if it's open or closed. Our website is a full-stack application (react styled with tailwind on the front end, node js on the backend). Our website also has games that communicate with the device to test the project and provide entertainment. We have one to test for continuous holding and another for rapid inputs, this could be used in recovery as well.

## Challenges we ran into

This project forced us to consider different avenues and work through difficulties. Our main problem was when we fried our EMG sensor, twice! This was a major setback since an EMG sensor was going to be the main detector for the project. We tried calling around the whole city but could not find a new one. We decided to switch paths and use an ECG sensor instead, this is designed for heartbeats but we managed to make it work. This involved wiring our project completely differently and using a very different algorithm. When we thought we were free, our websocket didn't work. We troubleshooted for an hour looking at the Wifi, the device itself and more. Without this, we couldn't send data from the PulseGrip to our server and games. We decided to ask for some mentor's help and reset the device completely, after using different libraries we managed to make it work. These experiences taught us to keep pushing even when we thought we were done, and taught us different ways to think about the same problem.

## Accomplishments that we're proud of

Firstly, just getting the device working was a huge achievement, as we had so many setbacks and times we thought the event was over for us. But we managed to keep going and got to the end, even if it wasn't exactly what we planned or expected. We are also proud of the breadth and depth of our project, we have a physical side with 3rd printed materials, sensors and complicated algorithms. But we also have a game side, with 2 (questionable original) games that can be used. But they are not just random games, but ones that test the user in 2 different ways that are critical to using the device. Short burst and hold term holding of objects. Lastly, we have a full-stack application that users can use to access the games and see live stats on the device.

## What's next for PulseGrip

* working to improve sensors, adding more games, seeing how we can help people

We think this project had a ton of potential and we can't wait to see what we can do with the ideas learned here.

## Check it out

<https://hacks.pulsegrip.design>

<https://github.com/PulseGrip>