Role: Frontend Development
Timeline: May-November 2022
Introduction
Depression is a common mental disorder, which can happen to anyone at any stage of life. In most cases, it is not recognizable even by the person suffering from it. The main goal of this project is to detect whether a person is depressed or not and then identify the level of depression the person is suffering from.
Background
More than 280 million individuals of all ages (or around 3.5% of the world's population) suffer from depression, a mental condition characterized by low mood and aversion to action. Depression, which is categorized medically as a mental and behavioral condition, has an impact on a person's motivation, thoughts, behavior, feelings, and sense of well-being. Anhedonia, which describes a loss of interest or pleasure in those things that ordinarily bring individuals delight, is considered to be the primary sign of depression.
The recent increase in sadness and anxiety that accompanied the start of the pandemic has been influenced by elements like the weakening economy, virus-related anxiety, and social alienation.
The Why: To prevent unfavorable events, it is crucial to recognize a person's mental state (such as stress, worry, or despair). Hence, developing an interface for its detection and prevention is of utmost importance.
The Goals: The goal is to provide assistance to medical practitioners with the analytics for the behavioral understanding of the potential patient suffering from depression using the multi-modular approach, taking into consideration the Audio, Video, and Textual features of the person. This project's major objective is to determine a person's level of depression before determining whether or not they are depressed.
Methodology
The project flow is interdependent between each module, which would be responsible for various work at different project stages, where output from one module may be input for another, and so on. Still, the final output is presented on the front end.
Flow of the whole Depression Detection Project
Technological Stack
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Flask
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HTML
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CSS
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JavaScript
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React
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Angular Framework
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SQL commands
Flow Charts
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Data Flow Diagrams
Flow of the project on both the frontend and backend side
Concepts
Results
Adding a profile picture to personal details
Patients Upload Dashboard
Functionalities added:
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Number of upload files
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Search box for uploaded files
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Date of uploaded files
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Progress bars
Schedule Appointments
Patient & Doctor Book Appointment Page
Three tasks were performed on the patient and doctor book appointment page:
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Added the search bar functionality so doctors could search a patient using the patient’s email ID.
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Added the Sort by User interface so that users can be sorted on the basis of 3 months, 6 months, 1 year, and 2 years.
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Also, added the choose patient area for the doctor using the list component in react.js.
On the Book an Appointment page, using the CSS property many functionalities include:
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Changed the border color of the selected boxes and un-selected boxes on click by the doctor.
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Added the “Continue” button functionality or changed the Continue button's color in react.js using array and use state.
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Integrated the API: The data is fetched from this API and integrated into fields like Name of the patient, Location, Last appointment with the doctor, and About the patient.
Appointment Dashboard
In this task, the frontend team made dashboard screens for doctors and patients.
Appointment dashboard for doctors
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Timeline of today’s appointments
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Tabs for filtering out the appointments :
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All the appointments
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Appointment invites sent by the doctor
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Appointment request sent by the patient
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All the Done appointments
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Different card designs for :
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Completed Appointments
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Missed Appointments
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Invites Sent Appointments
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Requests Sent Appointments
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Response Pending Appointments
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Rejected Appointments
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Count of scheduled appointments
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Tabs for filtering out the appointments:
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Upcoming appointments
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Missed appointments
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Done appointments
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Attendance Chart made using chart.js
Personal Details Page
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Users can enter, edit, and update their data
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Takes into account different physiological parameters.
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Creates a profile using the user’s personal information.
To-do list
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Allows users to list out all the tasks.
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Plan their day.
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Alarms and notifications remind the user about tasks.
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Links to the task chart to visualize data.
Task Chart
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The bar graph indicates the number of tasks completed.
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Helps visualize and graph out the Depression Detection data.
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Gives a pictorial view of the user’s schedule.
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Helps to understand the user in a detailed way
Chatbot
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Chat helps streamline tasks and activities.
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Manage a stable connection between the application and the patient.
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Connects with the user and helps with completion of the tasks
Summary
By creating such an interface, we were able to provide our users with a platform on which they could express their desires openly without any kind of repercussions. This platform provides voices to those individuals who would much rather stay quiet and bear the pain of it all.
We believe that the creation of such new methods to recognise at-risk people, could help in allowing those who are depressed to be identified and treated as soon as feasible in order to alleviate them of any further trouble and pain that Depression might otherwise cause them.
To conclude, a fully automated system was created that aids medical professionals in their efforts to investigate behavioral abnormalities brought on by depression. This end-to-end system is being created as both a web application and a mobile application because it is anticipated that practically all types of users would be able to use it.
View the live project here: Mental depression – Sabudh
Thank you
Find me
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Instagram
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