I-Care by RandomAIz

I-Care by RandomAIz (Team 077)

I-Care is an integrated self-care journaling mobile application that seeks to promote mental health well-being. It provides users with a safe space to express their emotions, whether it is through journaling or conversing with Charis, our conversational chatbot, allowing users to track their emotions and mental health progress over time. With integrated features such as an emotional tracker powered by Natural Language Processing, I-Care is able to identify potential depression and suicidal tendencies and directs users to seek the appropriate mental health assistance, whether it is connecting them with a mental health hotline or recommending them to a therapist.

Key features:

1. Journal with integrated capabilities

The journal provides users a safe space to express their emotions, to do a daily log of their activities, feelings and events. It is powered by NLP and can be linked to notification pop-ups as well as the emotional tracker. It is confidential and data is not shared with other users

2. Emotional tracker with motivational pop-ups
Powered by NLP to classify your general mood of the day based on the day’s journal entry - 6 simple categories of emotions: joy, sadness, anger, fear, love and surprise
This can be shared with the user’s linked support network for them to be aware of each other’s emotional state to better check in on each other.

3. Multi-Functional Conversational chatbot
Aids in forming emotional bonds with the user, especially during this period of COVID-19 where many feel increasing levels of isolation
Provides a safe space for people who are afraid to seek help or share their problems with others to do so
Powered by NLP & Machine Learning - chatbot learns from the users’ conversations to provide catered answers that seeks to help improve the users moods or help them with depression Notifications pop-ups to direct user to seek the appropriate help
Powered by NLP to classify potential depression or suicidal tendencies when certain trigger words are used in the journal or conversational chatbot, or if journal day-to-day entries or conversations with the chatbot records prolonged periods of sadness. The notifications can provide links to other articles, psychiatric hotlines.

4. Support network - 2 types
User is able to customize depending on the caree what type of support you would want to have
Carer-caree support network e.g. parent-child, in which the carer would receive the general emotions the caree is feeling
Mutual support network where each user sees the day-to-day emotional tracker of other users so that they can better follow-up or check in with each other.

Creative Use of ML/AI

Use of Natural Language Processing to conduct sentiment analysis. Sentiment analysis is a subfield of NLP which focuses on identifying and extract opinion from a group of text. The result of sentiment analysis is generally classified into positive, negative and neutral. The team has used sentiment analysis for emotional detection to classify app users into different categories based on their emotional states we predicted from our NLP model. Sentiment analysis allows us to provide real-time analysis and feedback to users based on the journal entries.

Impact of Solution

Preliminary quick diagnosis of Mental Health issue as it prompts individuals when negative emotions are detected, and provides support for the user
Timely assistance to individuals suffering from mental health issues as it provides a robust support network
Increased accessibility for mental health help as it provides an alternative avenue for people to express themselves and seek mental help, improving awareness of user’s mental health and emotions