Researchers at the University of Oxford noticed that our genes determine the time spent while doing activities. It was the largest study based on 91,105 participants who wore an activity monitor on their wrists for a week. The scientists have instructed machines for identifying the behavior and monitoring a huge amount of data. They noticed time spent by activities such as sitting, moving, and sleeping.
Researchers combined data collected from machines with existing information to reveal regions connected with physical activities. This research paves the way to make understanding the connectivity with their physical activities and consequences on health. This study proved for the first time that increasing physical activities could reduce blood pressure.
Physical inactivity is a great threat to health, which usually leads to obesity, heart diseases, and high risks of diabetes. Fluctuations in sleeping duration can negatively effect on the heart and metabolic diseases and numerous disorders. This study on genetic analysis proved that it effects on mental health and brain structure. In addition, it shows that physical activities a play a key role in the effective working of central nervous systems.
Use of intelligent machines for analyzing huge datasets in healthcare is important as it gear-up the speed of the process.
Dr. Karl Smith-Byrne, one of the lead researcher working on the study said that machine-learning model played a vital role. The machine-learning model impressively taught how to analyze complex data on physical activities. This model provided some new details on human behavior and movement. Especially, this study provided some exciting data based on a half million people.