Insomnia is a common issue around the world. Anywhere from 25% to 40% of people in a given population deal with difficulty falling or staying asleep.
But Chinese scientists say they've found a way to use artificial intelligence (AI) to tell how well people have been sleeping from the way they walk.
Professor Zhu Tingshao and colleagues at the Institute of Psychology in Beijing have developed an accurate method of determining sleep quality through its impact on gait, with the help of a machine learning algorithm and a video game component, according to a paper published by online scientific journal PLOS One.
Zhu and his team found upper body parts " such as head and shoulders " betrayed more about a person's lack of sleep than lower parts like hips and legs.
The researchers claim their method could flag the number of people in a crowd who have had insufficient sleep, providing a low cost way for public health authorities to measure the scale of a growing health problem, leading to more timely and effective policies to address the issue.
Poor sleep quality has been linked to everything from bad temper to obesity, work accidents and heart attacks.
In China, about a quarter of the population has sleeping difficulties, according to a survey conducted by government hospitals last year. Other countries such as the US have reported similar or worse problems.
The soundness of sleep can be measured by wearing a smart watch or bracelet, donning a brainwave monitor or taking an MRI scan in the hospital.
These methods, however, require people's collaboration and cannot be used to monitor a population, especially when people are wide-awake.
Previous studies by other researchers suggested that inadequate sleep affected walking speed but the correlation had been too weak for practical use.
In contrast, the latest research paper suggests the system developed by Zhu and his team could monitor 360 types of movement taking place in all major joints of the human body.
More than 50 first-year postgraduate students from the University of the Chinese Academy of Sciences in Beijing took part in the training and testing of the system, completing a sleep quality questionnaire before walking in front of the camera.
Copyright (c) 2019. South China Morning Post Publishers Ltd. All rights reserved.