## Inspiration

One of our team members, Ahmed subluxated his shoulder and weakened his rotator cuff muscles severely in a basketball injury. Physiotherapy was difficult to make time for with school and there were few resources online to help. This inspired us to create a healthcare hack that targets physiotherapy and treatment for any afflicted patients.

## What it does

Our hack uses the technology of the Myo Armband to sense micro-movements in muscles and their spatial location relative to the body. The high sensitivity permits detection and distinction of any movements using the arm, hands, and fingers. A patient would take a diagnostics test using the armband and judging by their results, they would be assigned a strengthening and treatment routine specific to them. Their results would be tracked and stored in FireBase's database to see their progress.

## How we built it

Hacking the Myo Armband gave us several javascript functions associated with each type of movement. This was harnessed and coded to recognize the specific exercises we would want a patient to perform and how well they performed them. We used html and css to form the front end of our web app and used Flask and FireBase to launch our site and store/retrieve data.

## Challenges we ran into

Part of using the Myo Armband came with the difficulty of retrieving signal information. This is because the Myo Armband offered a plethora of functions that provided different variable types worth of data. Eventually we decided to go with a string only output as it made the debug console a lot cleaner and easier to work with for a demo. Similarly, while creating our front end, we ran into a problem communicating the data received over time between 2 different parts of the same webpage.

## Accomplishments that we're proud of

We are extremely proud of the fact that we managed to use the Myo Armband and actually receive multiple values based on our own custom actions. By the end of the hacking phase we had 4 different functions working for 4 different therapeutic treatments. Similarly, we are extremely proud of how our user interface works and our attractive yet simple home webpage.

## What we learned

We learnt how to use a motion sensing device and change the internal capabilities based on its original source code provided. Using hardware is always a long process as there is a lot of testing and troubleshooting required. This was new for us and we found it very enjoyable and enlightening. Once we managed to get our hardware to do exactly what we wanted, the feeling of success was fantastic.

## What's next for FortiFlex

We want to keep adding more types of therapeutic treatments. In addition, we feel that some simulations and video examples would make using the Myo Armband and our web interface a lot smoother and easier to use. Eventually once this application starts to help a lot the users with their treatments, a large demand for new treatments and options would be required. This means regular updates and maintenance is also needed. Hopefully, this idea will spark even more creative ideas in the future because it is really enjoyable when you can create something meaningful for society.
## Inspiration

Learning how to to be fit is challenging and often, more times than not, quite intimidating for the average beginner. Not only are many people afraid of going to the gym, but many also don't find it feasible to hire a personal trainer who can guide them through the fitness process. Myo Lift was created to help users gain a thorough understanding of fitness in the comfort of their own homes by using the Myo arm band to track the users' movements.

## What it does

Myo Lift is an app that allows users to customize their fitness journey, track their form and compare it to an Augment Reality version of a personal trainer featured on the app.

## How we built it

We built Myo Lift using Visual Studio, Xcode, and Invision. Visual Studio was used to connect data retrieved from the Myo armband and track movements, Xcode was used to implement AR, and Invision was used to create a prototype of the mobile app.

## Challenges we ran into

As AR is still a growing component that developers are choosing to use nowadays, the types of tools and options Xcode offers are still limited. For instance, the group had to stick to using the back camera instead of the front camera because of the limited resources available to enable object recognition.

Another challenge we experience was the lack of documentation of Myo Armband. As Myo Armband was a recently developed item, and not many developers have used it, there is a lack of code available for reference and understanding how to use the Myo Armband SDK. We decided to base our SDK on the "Hello Myo" SDK that Myo provides.

## Accomplishments that we're proud of

We are proud to have created an application that tackles an issue that not only a limited group of people can relate to, but rather, a problem that majority of us have gone through at some point in our lives.

Through this short period of time, we challenged ourselves to dig into other components that we were unfamiliar with such as Augmented Reality, Myo Armband connections, and specific API usage. Essentially, we wanted to maximize the user's experience as much as possible.

## What we learned

We learned how to implement AR into an IOS app, retrieve data from the Myo armband movements, and develop a product using the Myo armband. All of us had never developed anything with the Myo armband or with AR before.

## What's next for Myo Lift

Since the Myo armband can only track upper body exercises, we're hoping to create a device that will enable users to track their lower body and leg workouts. Furthermore, but we are looking to use 3D object recognition with AR tools in order to outline the shape of the user and properly process if their fitness form is fundamentally correct. When the application identifies the position that the user is in, it will be able to compare the data to its pre-existing knowledge of what a proper workout form should look out and inform the user if they are doing the motion correctly or not.
## 📚🙋‍♂️Domain Name📚🙋‍♂️

**DOMAIN.COM: AUTINJOY-WITH.TECH**

## 💡Inspiration💡

Parents know that travelling can be an eye-opening experience for kids, but they also know that travelling even with one kid can be overwhelming, involving lots of bathroom stops and needing to manage boredom, motion sickness, and more.

When parents have an autistic kid, it means they have to consider additional factors when travelling. Because when places with sensory overload, closed spaces, or constant movement stress out an autistic child, the child can have what's called an "autistic meltdown", which is very difficult to manage temper tantrums.

So what if they had an app that could help them avoid triggering these meltdowns?

## ❓What it does❓

For parents and the caring adults they trust like a babysitter, the app allows them to:

* journal when autistic meltdowns happen and how they manifested
* visualize this data in a structured way to understand when and how meltdowns happen
* find whether businesses and attractions they plan to visit are unexpectedly crowded or have areas to look out for that could trigger meltdowns
* contact destinations like airports, hotels, and museums in advance in case accommodations can be made

For kids, the app helps them:

* communicate their needs; and
* journal their thoughts and feelings

For businesses, the app allows them to:

* alert users when they unexpectedly have large crowds when users search for them
* proactively inform users of areas with potential triggers like sensory overload from loud noises or bright lights; and
* receive feedback anonymously from users when kids have a meltdown and any relevant environmental factor so that they might decide to put a sign up to caution visitors or indicate this info somewhere

## 🏗️How we built it🏗️

We built our app using HTML, CSS, and JavaScript for the dashboard and Figma for the mobile app.

1. We Use HTML/CSS/JS for building the dashboard.
2. We Use Auth0 as the login and Signup page.
3. We Use Twilio for Multi-factor Authentication and Connecting SMS from Doctors or Social Groups.
4. We Use FIGMA for Mobile Application.
5. We use Google Maps for Localization and Addressing Restaurants or Stoppages of the Journey.
6. We use Google Cloud for the deployment of the Dashboard

## 🚧Challenges we ran into🚧

* Managing a team in different time zones
* Limited coding ability on the team

## 🏅🏆ACCOMPLISHMENTS THAT WE ARE PROUD OF🏅🏆

We worked on an idea that has real-world application! We are happy to have devised a solution to a critical problem that affects such a vast number of people with no available methods or resources to assist them. We learned a lot while working on the project not just technically but also in time management. We are proud we could complete the project and deliver a beautiful fully functional Hack this weekend.

## 📚🙋‍♂️What we learned📚🙋‍♂️

We learned so much about HTML and CSS Design while completing Dashboard. Implementing UI/UX to the fullest of our Capabilities using FIGMA to make it look Aesthetic and Attractive for users. We were able to manage the time well and Implement the ideas we had brainstormed. We also learnt the critical use of Backend Services like Twilio and Auth0 for authentication. Google Maps and Google Cloud made the application more userfriendly and helped us learn about deployment. The themes of the website tried to make it as visually attractive as possible for the Autistic Kids to like and Enjoy.

## 💭What's next for Autinjoy💭

1. User testing and feedback by real-time Users
2. Deployment at a large scale for Social Good & Travel ease
3. Auto-generating the travel itinerary using AI & Machine Learning
4. Making a Weekly schedule for Management of Therapy Sessions