A well-known fact, that sleep is one of the important factors that determine human health, and therefore, humans have been recommended to have a peaceful sleep for seven hours a day. But a study done by the Centres for Disease Control and Prevention in 2016 found that one-third of the adults in the United States get insufficient sleep that is much lesser than the recommended hours of sleep per day.
There have been constant efforts from the experts and various research teams to ascertain the reasons for the behavioral changes and health problems. One such research conducted proved that commitment to mistakes and loss of jobs are some problems caused by lack of sleep. The problems caused by reduced hours of sleep are quite large and it needs to be quickly resolved. This gave rise to finding out different ways to solve the issue of sleeplessness and Big Data is one such boon for sleep science which can be used as an alternate to Polysomnography.
Big Data, when used instead of Polysomnography, has many advantages because of its simplicity and cost reduction nature. Modern-day sleep data can be collected with much ease on a large scale using the benefits of Big Data. Today, since much technologically improvised, new technologically well-equipped tools are invented to collect data.
Wearable sensors deliver Real-Time Data (RTD) on tracking various attributes that would affect an individual’s sleep. Sensor inbuilt wearables like headbands, watches, finger rings and mattresses would help impeccably in collecting sleep data. The new sources for collecting the sleep data contributed a huge amount i.e. very huge amount of data. Some organizations provide huge datasets acquired from various examples and studies through different methods.
Big data applications in sleep science are now diverse, ranging from solely healthcare-focused applications to various industrial applications.
- Big Data in sleep science helps clinicians make significant progress in diagnosing and treating sleep disorders. A wireless multisensory suite was found by a team in 2013 to predict sleep disorder episodes. This would help to adjust the CPAP airflow to prevent the disorder episodes.
- Can be used to detect the sleeping habits of patients in new medication therapies and patients of the post-surgical recovery process.
- Smart beds and pillows are for sale, which collects the sleep patterns of the users. This is, in fact, one of the applications that are highly effective as these beds and pillows automatically change temperature, the postures of the sleeping person, and sense the best time to wake the person up.
Big Data and its contribution stand varied because of its wider application in various fields like healthcare, agriculture, banking sector, cloud computing, marketing, and so on. Big Data in sleep science has shown its excellence in detecting various sleep problems like sleep apnea, RLS, and sleep paralysis in such a cost-effective and less arduous manner. There is no doubt that Big Data will become more powerful in the future, taking into account its contribution to the modern world.