October 31, 2019 | 4min read
The Potential of Neurofeedback—Interview with Aziz Kaddan of Myndlift
Wearable technology is taking over the market! According to Ericsson, 40% of users who purchase products from the wearable tech industry say that they feel naked when they’re not wearing their device. And that’s mostly smartwatches. Today, however, we wanted to focus on a different side of smart devices—the one that can play a big role in users’ mental health. A great example of combining wearable technology and positive tech.
Myndlift is a neurofeedback platform clinicians can use for their patients to help with different mental issues like ADHD, ADD, depression, anxiety, or PTSD. A wearable headset is also popular among musicians, athletes, and… gamers in Japan who, thanks to the solution, train their minds and increase attention to get more points in competitions.
When I was young my siblings used to take ADHD medications to improve their attention. The pills did their job, but the treatment came with some side effects. After researching this field for a few years, I found that there is an alternative solution—a type of training for your brain, called neurofeedback.
Aziz KaddanCEO,MyndliftMyndlift wants to be the leading brain health platform. Just like when you go to the gym to get fit, we want you to come to us whenever you need brain fitness.
Neurofeedback is a way of training specific brainwaves. First, you measure the waves and then condition them using the visual and auditory feedback. Unfortunately, it’s a costly and not easily accessible treatment. A patient usually has to go to a clinic for about 30-40 sessions. At the same time, as I was researching neurofeedback, I started to be aware of some new technologies emerging in the market. They would allow people to measure the brain activity on their own, with small sensors placed on the forehead. I thought, why not take the old-school brain training and use wearable technology to turn it into something more accessible.
After putting on a headset, EEG technology measures your electrical currents (coming from neurons in your brain). These measurements are then sent through Bluetooth to our mobile app. The app decomposes these signals in real-time into various brainwave frequencies. Each one of these frequencies can indicate a certain mental state you’re currently in. For example, if mid frequencies, like alpha, are getting higher in the amplitude, it means that a person is relaxed.
The app showcases videos or games based on these frequencies. Through games, we either present the user with positive or negative visual feedback. If the brain waves are indicating that the user is relaxed, he/she is doing better in the game (getting more points, going faster). When the user is anxious, they’re getting negative feedback—losing points, going slower. The mechanism conditions our brainwaves by providing visual stimulation and reward (or not). Eventually, with the help of one of our clinicians who guides the users through the training, their brain slowly learns how to balance itself.
We faced many challenges along the way. With EEG, for example, it’s important for the user to be able to place the headset correctly. If you’re not getting clean data then the brain training is not adequate.
Ideally, we would tell our users to put the headset on and start training. Sadly, it wasn’t that easy. If the headset is not tightened correctly or put in the right place, it can temper with the data. In order to solve this issue we first created a strict mechanism in the app with signal feedback indicating whether the headset is placed correctly or not. Not going to surprise you here—it didn’t work. Our users were not able to pass the signal check. So, we thought of another way—we hired a support team.
When users were not able to pass the signal quality check, they could press a button in the app, which would connect them directly with our support team, guiding them through the process. Obviously, it was not a scalable solution for the long run. During that time, we managed to record what were the most common issues with the process and how our support team was helping the users to solve them. Thanks to this we were able to improve the signal check process. Now, if the user can’t pass it within the first 20-30 seconds, we show a pop up instructing them on how to do it step-by-step.
This month we passed more than a million and a half minutes of training in the app. In just a year and a half, we gathered the number of EEG data a typical lab would need several years to collect! We’re very proud, especially because that data will make the Myndlift experience even better for our users.
Myndlift wants to be the leading brain health platform. Just like when you go to the gym to get fit, we want you to come to us whenever you need brain fitness. We hope for Myndlift to be the next frontier of the neurofeedback technology.
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