Meditation & AI: Creating a Customized Relaxation Experience
It seems these days you can’t scroll a website or a social network without being touched by at least one mental health message. It’s not just you. It’s something everyone can benefit from and given the added stresses of this current constant state of change, companies are tapping into that need with smart technology that can add a little bit of calm to your day.
Meditation is the exercise of breathing and emptying one’s mind. Once something reserved for those of spirituality, meditation and mindfulness is now a commonplace ritual—and not one that requires training or any kind of equipment. In fact, artificial intelligence is making it easier than ever to relax.
Meditation apps have become increasingly popular in recent years, many of which are powered by data and artificial intelligence. AI is leveraged to customize a person’s experience in these apps by analyzing user data in real time, delivering near instant results and personalized suggestions to each user. Good Housekeeping created a list of the 13 best meditation apps, based on a variety of factors. Calm won best overall, while Headspace was recognized for best audio selection, and Waking Up is the most beginner friendly.
One thing all these apps have in common, in addition to their status as top mediation applications, is their reliance on robust, unbiased, scalable data to train their AI models to deliver quality results to users.
The Health Benefits of Meditation
Maintaining balance through this constant state of change, work, family, social interactions, exercise, etc. can be taxing. According to Heathline, one of the most common reasons for people to try meditating is for stress and anxiety reduction benefits. Data shows us that stress and anxiety are more prevalent than ever. A 2020 study showed that anxiety increased from 5.12% in 2008 to 6.68% in 2018 among adult Americans, the 18-25 age group had a 6.69% increase during that time. This was further exacerbated by the pandemic which caused reported anxiety cases to increase by 25% according to the World Health Organization. Simple lifestyle changes can combat stress and help improve your quality of life.
In addition to lowering stress and anxiety, mediation yields other benefits such as improved focus and memory capacity. Numerous studies have been conducted emphasizing the effects of meditation on improvements in focus and memory. One study conducted in 2013, Mindfulness training improves working memory capacity and GRE performance while reducing mind wandering, showed that the effects of improved memory and focus were noticeable after 2 weeks of mindfulness training courses were completed.
Meditation Apps Powered by Data and Artificial Intelligence
So where does AI play a part in something largely focused on breathing and relaxing one’s mind? By powering customized experiences for the many different meditation apps that make a moment of relaxation accessible and attainable.
Each person’s mediation journey is as unique as they are, and machine learning (ML) is used to account for these personalized factors when recommending exercises to the user. The models are first trained by data indicating the type of exercise a person selects when looking for a specific topic, goal, or have a certain piece of data entered. ML models then learn to recommend the activities that are commonly selected. To further enhance the user experience, the models are also taught to not list the same recommendations repeatedly and suggest alternative exercises that can achieve the same goal. This ensures that the user doesn’t get bored of the app.
With more than 10 million downloads in the Google Play Store, Calm is one of the most popular mobile mediation apps on the market. Leveraging a data-fueled machine learning model, Calm saw in-app engagement grow by 3.4% in 2021.
What really sets this experience apart from a simple computer program designed to list results based on what’s entered into the search bar, is personalization. AI models learn in real time and change their recommendations based on if a user completes an exercise or if several days have passed since a user opened the app. A generic computer program would continue to recommend the same exercise on repeat.
The Data Health Benefits of Working with Appen to Power your Meditation AI
If you think having an app customized to your unique preferences is as cool as it sounds, you’re right. If you’ve ever opened an app, and noticed that the longer you use it, the more customized the ads and content recommendations are, then the app is benefiting from machine learning. Customization doesn’t happen overnight; it takes some time and data for the model to learn your unique preferences.
These customized in-app experiences don’t just learn from what you interact with, they also learn through search relevance. We mentioned earlier than some meditation apps utilize models that are first trained off what type of exercise a person typically picks when looking for a specific topic. This falls under the branch of search relevance as you want the accuracy of the results displayed to be highly relevant to the topic searched. No one wants to search for an item and have the results be something completely irrelevant with the only match being the name. It’s like searching for Apple to go to their website to buy a product and then the only search results displayed are those of apples as food.
Search relevance is one of the seven core use cases we excel in at Appen, and when combined with other AI training data, like image and video classification, we ensure that the user experience is truly unique as the person using it. Sourcing, collecting and annotating data to power machine learning models for meditation apps is a lot of work, and we’re happy to take that item off your agenda—giving you some time back to do things like relax…even meditate.
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