Safe And Sound

It was another rough night. My son had a seizure shortly after going to bed and at least three the next morning. Fortunately, he was sleeping in our bed. It’s easier to catch the seizures and take care of him when he is with us.

Lately, he started doing this thing where, after he has a seizure, he’ll sit up and try to climb out of bed. He’s not awake, it’s more of an electrical impulse that triggers the circuits in his brain that signal him to move. We comfort him during the seizure and then perform early morning Aikido and redirect his impulse to move in the direction of his pillow. Within a few seconds, he is back asleep.

I went through the process for two of his seizures that morning. Comfort, Aikido, sleep. After the last one, I laid in bed with my eyes open and stared at the ceiling. My mind drifted to the question that I still can’t face.

What would happen if we weren’t there? Who would be there to comfort him? Who would be there to keep him safe?

The idea of him doing this alone seems impossible. The idea of him never being able to be on his own is heartbreaking. The thought that I will someday not be here to take care of him, to keep him safe, and to comfort him is what keeps me awake.

The early morning mind is cruel. It is also calculating. It takes advantage of my incoherence to pose unanswerable questions when my defenses are down. It plants unanswerable questions and then sits back to watch the show.

The two solutions I usually come up with are curing epilepsy or becoming immortal. One is just as likely as the next but neither is likely be to solved in my lifetime. And so I am left with the fear of the future. Not for my sake, but for his. Because I was supposed to be the one that took care of him, that showed him how to be a good man and sent him into the world to make his own way.

But I don’t know how to do that when I watch his body seize over and over. The more seizures he has, the more impossible it seems that he’ll be able to make his own way. I’m fighting back the inevitable reality that no matter what I do, I may fail.

I hope I’m wrong.

But even if I’m not, I’ll never stop fighting.

Invisible In Plain Sight

I stepped on to the street on my way to work. As I joined the flow of foot traffic, I saw a young man walking quickly ahead of me. I say “walking”, but he was bouncing more than he was walking. I didn’t see any of the earphones that I and most of my fellow pedestrians were wearing, but he was moving as if he had a soundtrack playing in his head that lightened his steps.

I noticed him because he was so different from everyone else on the street. He was a tall, young African American teen wearing a bright blue t-shirt surrounded by an army of mostly white business people dressed in muted black, brown, or blue. He head was up as he looked at the world around him while that world was looking down at their feet or at their phones.

When he stopped at a crosswalk, I got close enough to see that he would sometimes raise his hands and sign to no one in particular. It was as if he was signing the lyrics to the song in his head. Like when the chorus of a really good song comes on and you find yourself singing along, even if only in your head. From half a block away, this young man looked like joy personified walking up the street.

The light turned green before I could catch up to him. He danced through the intersection and on his way. As he did, I saw that he would occasionally wave to people passing in the opposite direction. Even from my distance, I could see a big smile on his face. But no one that he waved to reacted. They kept their head down. They looked at their phones. They looked the other way.

Maybe they didn’t see him. Maybe they were busy. Maybe they were really interested in whatever was on their screen. Maybe they were scared. Or maybe they just couldn’t be bothered. We live in a big city and I see people ignoring the world around them and everyone in it all the time.

I thought that maybe the young man had a disability because he was signing. Or maybe he was just different than, in color and age and general attitude, the other people on the street. But watching how the young man was being ignored made me think of my son.

Epilepsy is often called an “invisible” condition because it lacks physical markers, but there can be signs. We’ve had more than a few people ask us politely “Is there something wrong with him?” after they spend time with our son. He’s noticeably different in a self-centered world that doesn’t seem to have a place for people that are different. We talk about diversity and inclusion but we look the other way when it is our turn to act…when it is our turn to accept someone who is different from us.

I watched the world look away from that young man on the street. I saw the world unwilling to acknowledge another human being. I don’t want that for my son but I don’t know what to do about it. I wish I could change the world. I wish I could make it more accepting, more forgiving, more tolerant, more open, more aware. But we’re heading in the wrong direction. I fear that the only thing that I can do is prepare my son for the road ahead.

But then I turned my attention back to the young man. I could see, as he waved to the next person, that he was smiling. Even with the world ignoring him, he was walking with a bounce in his step and smiling. He would wave at another person. And then another. And he would keep smiling. I watched him not slow down, not shy away, and keep moving forward. I thought of my son then, too, because he has that same persistence, the same drive to bring joy to the world. And for a brief moment, I felt hope.

I never caught up to him, but I wish I could tell that young man that he brightened at least one person’s morning that day.

Seizure Detection And Prediction

This post is part of the Epilepsy Blog Relay™ which will run from March 1 through March 31, 2018. Follow along and add comments to posts that inspire you!

As the parent of a child with epilepsy, I rarely sleep through the night. Instead, I periodically wake to check in on my son. We use a wireless camera that has an app that we run on an iPad that I prop up beside our bed. I can see in to his room, even at night, and hear any activity or seizures. For the most part, it’s a good setup. But occasionally a wireless issue will cause the connection to drop. I’ll wake up facing a dark screen, wondering if I missed a seizure as I fumble in the dark to restart the app.

That scenario repeats a few times a month, which is why the news that the FDA approved the Empatica Embrace as a medical device was so exciting. The Embrace is a wearable device that detects generalized tonic-clonic seizures and sends an alert to caregivers. Devices like the Embrace will provide a piece of mind to many people with seizures and those that care for them.

Unfortunately for us, we haven’t yet found a device that can reliably detect my son’s seizures. His seizures are short and without much movement, making them harder to detect. Generally, the longer a seizure is and the more activity it generates, the more likely it will be detected. But with new sensors and smarter algorithms, these devices will continue to improve. They’ll have a higher sensitivity to detect shorter and more subtle seizures. Instead of relying on my own eyes and ears to catch every seizure, I’m hopeful that these devices will work for my son someday, too.

Since the theme this week is technology and epilepsy, I thought I would spend some time talking about the magic behind these devices.

Detection versus Prediction

Detection

First, I wanted to differentiate between detection and prediction. Devices like the Embrace focus on seizure detection. Detection figures out when a seizure is happening. The device monitors activity from embedded sensors and runs it through an algorithm. The algorithm has been trained to look for patterns that look like seizure activity. Once it is confident enough that a seizure is occurring, it will send out an alert.

Prediction

Seizure prediction tries to figure out when a seizure is likely to happen. Some people have auras or other cues that let them know that a seizure is coming. Imagine a device that could provide that same warning to everyone. This is a hard but achievable goal. The clues may be more subtle and harder to see. We may need more data or new sensors, but we’re well on our way to developing them. When we figure it out, the warning it provides cold allow a person about to have a seizure to go sit down or get to a safe area. It could alert caregivers ahead of time so that they provide help before or during the seizure.

Training an Algorithm

Both seizure detection and seizure prediction use much of the same data but for different goals. The techniques used to learn the algorithm are similar, too. Data is collected from a group of people wearing different sensors. The data includes both seizure and non-seizure activity and it’s fed in to a computer with a label such as “seizure” or ”no seizure.” The computer learns the difference between the two and creates a model that can be used to look at new data to classify it as a “seizure” or ”not a seizure.” The more examples the algorithm sees, the better it gets at identifying the common traits in the data that are associated with a seizure.

The process is similar to teaching an algorithm to identify a cat. You feed the system a bunch of examples of cats and it identifies that a cat has two eyes, to ears, a nose, and whiskers. It generalizes traits using a technique called induction. Once it generalizes the traits, it can use them to identify a cat that it has never seen before using those traits. This is called deduction.

The same approach happens with seizures. People and seizures are different. If we trained a model to look for a specific heart rate, it wouldn’t be useful because that would differ for everyone. Instead, we train a model to associate common changes that happen during a seizure. Then, when it sees the data coming in from sensors in a device, it looks for those similar markers to decide how to classify the data.

No Algorithm Is Perfect

As in the cat example, there are an infinite number of combinations of data points necessary to always get it right. We can’t practically train a model by showing it every angle of every cat that might exist. And we can’t give it data reflecting every possible seizure for every person. But we don’t have to. The magic of these algorithms is that they can do a pretty good job using subsets of the data. But that does mean they can make mistakes.

There are two types of mistakes that are the most common: false positive and false negative. In the case of seizure detection, a false positive is when the algorithm said there was a seizure but there wasn’t. A false negative would be when the algorithm didn’t think there was a seizure but there was.

These two error types present different challenges. In seizure detection, a false positive means that a caregiver might have been alerted. This can be annoying, especially if it happens too much, like The Boy Who Cried Wolf. Too many false positives means people may turn off the notification feature or stop wearing the device altogether.

In seizure detection, the false negative is a much more severe problem because it means a seizure occured but the algorithm missed it. That means no notification was sent to alert a caregiver. If that is the primary purpose for the device then it can’t be relied on and won’t be used.

Making Things Better

The good news is that algorithms can learn from their mistakes and get better. We can use the times it was right and wrong to retrain the algorithm so that it can get better. That’s what Google, Facebook, and every other company that uses data does to make their products better. A popular concept in the world of machine learning and AI products is the Virtuous Circle of AI.

We create products and give them to customers. The customers use the product and generate more data. The data is used to make the product better by making the algorithms better or adding new features. This is how Alexa gets better at understanding what you’re asking for, how Google gives you better search results, and how music and movie recommendations today are many times more accurate than even a few years ago. In the same way, as more devices like the Embrace find their way on to the market and more people use them, these products will use the data to get better, too.

NEXT UP: Be sure to check out the next post tomorrow by Joe Stevenson at epilepticman.com for more on epilepsy awareness. For the full schedule of bloggers visit livingwellwithepilepsy.com.

Don’t miss your chance to connect with bloggers on the #LivingWellChat on March 31 at 7PM ET.