While we were researching potential hackathon ideas, one of our fellow lovely members stated that people who suffer from Bell’s Palsy may undergo functional electrical stimulation (FES) treatment to enable the patient to feel and move their facial muscles. These people as well are usually given physical therapy exercises to try and move their muscles on their own by physically moving their faces into different emotional states.
That’s when we realized something. Feelings can range from sad, afraid, happy, and excited. Our personal emotions allow other people to understand us better and learn the ways to respond to our actions. However, more than 1 million children suffer from autism globally, and are unable to communicate their facial expressions as well. With these selected people in mind, our team aspires to combat this problem through technology.
Introducing TherAssist! It is a web app that can be used by occupational therapists or parents when guiding children who suffer from autism. It could detect the facial expression of the user based on their face using machine learning. Through this app, they can start teaching the children to evaluate, assess and associate their facial expressions with the proper emotions.
- Our team faced difficulties in communicating with each other due to time zone differences. With the time zone difference, some of us had to compromise by sacrificing our sleeping schedules.
- In addition, sometimes the internet connection sucks. It’s difficult to be working on a project during a call with a bad internet connection.
- However, we did not want time zone differences, sleep deprivation and a bad internet connection to hold us back from participating at DefHacks 2020.
- Further, implementing machine learning into our project was something that stopped us in our tracks. We weren't quite sure how to get started or where to even look, but we pushed through and were able to create something that excited us.
- Completing a project that is really applicable and solves real world problem
- Learning about building apps in python
- Learning about computer vision
- Learning about machine learning and creating a working app that uses trained models
- Haar cascades are limited in what they are able to detect but run extremely faster than CNN models making it easier to make Haar cascades live which would be useful for webcam applicaitons.
- Applying the models that come from machine learning isn't as dificult as we initially thought
- Allowing other areas of study as well (eg. learning alphabets)
- Reports generated by therapist to show parents how sessions went
- Ability to assign homework to the patients (having a patient side app)
- Better UI and front-end