Big Data

5 Ways Big Data Is Being Used to Improve Sleep


Even before the coronavirus pandemic flipped the world on its head and brought a wave of anxiety, it was estimated that less than 65% of Americans got enough sleep. For some, the pandemic has allowed for better rest schedules, but for others, it can be difficult to feel tired after simply being home all day. Even those who had office jobs that involved 8 hours of computer time still had to leave home, deal with traffic, get lunch, etc., all things that burn some calories and add to fatigue.

Ultimately, not too many people are upset about not having to deal with traffic, but according to health data, a lack of a good night’s sleep can result in poor performance at work, higher stress levels, and even family issues. Luckily, that same data industry has been focusing on improving sleep, and here are 5 ways they are doing so.

Understanding Genetics

Before science fixes issues, science studies issues for understanding. When it comes to sleep data, scientists and analysts work together to pinpoint differences in genomics, proteomics, and other data related to a sample group of sleepers. These studies are the backbone of discoveries of information such as narcolepsy being related to an immune system deficiency, and things of the like. Understanding genetic issues that cause sleep, the same way doctors use genes to determine likeliness of disease, can help individuals determine if their habits are to blame for a poor night’s sleep, or something deeper that may require medication.

Understanding Activities

Beyond genetics, big data is also the bread and butter for analyzing information that is collected by things like Fitbits and sleep aid applications on smartphones. Utilizing the data from a given patient’s device or app and comparing it to a group of patients who may sleep well on a regular basis is another opportunity to point out discrepancies and understand why someone is having trouble catching Zs.

Improvements Based on Genetics

The data sets mentioned above do, indeed, point to more genetic or chemical issues in poor sleep habits that previously believed, so it also allows for increases in treatment efficacy for these issues. Tracking patients who have shown to have a genetic issue relating to their sleep allows for even more data to be collected, ultimately allowing for tweaks and changes in treatment. Development of better drugs and therapies also stems from studying patients and analyzing the data surrounding them.

Improvements Based on Materials

Outside of drugs and personal improvements, big data in the mattress world has also helped people get a better night’s sleep. Though there are no patient vitals to measure on a mattress, there are many other things like firmness, materials, size, etc., and setting up studies not all that different from those that measure human reactions, scientists can analyze data on what styles of mattresses offer the best odds for curing your sleep habits, based on people who came before you with those same bad habits.

Machine Learning

A part of artificial intelligence that is making major differences in people’s lives (especially data scientists) is machine learning. As the name suggests, machine learning is a given machine’s ability to analyze data and make changes in how it works, without having to be programmed to do so. For mattresses, for instance, this could be as simple as feeling the weight of someone and determining which person has gotten into the bed and adjusting firmness automatically. When it comes to apps and devices measuring vitals, the possibilities are quite boundless with how AI can take that information and help you change your habits accordingly, to ultimately get you a better night’s sleep.


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