Efforts are underway in Japan to develop artificial intelligence-based tools that will help detect dementia at an early stage, including one that analyzes how people walk. Those tools are expected to lower risks of elderly people roaming around or failing to notice that they have the condition and see a doctor early, easing concerns of those people and their families. Since February, Ridgelinez, a Fujitsu unit that offers consulting services, has been working with the National Cerebral and Cardiovascular Center and AI startup Noel to develop a system that will detect characteristics seen in the way people with dementia walk.

Dementia can make it hard for a person to focus and remain alert -- two things that are really important for road safety. Being able to identify when someone is experiencing early signs of cognitive impairment could be key to saving lives on the road -- unfortunately, it's not always easy to notice these early signs. Now, machine learning could make it easier to detect dementia. The innovation: A team led by researchers at Columbia University has developed machine learning models that detect early and mild cognitive impairment in older drivers with 88% accuracy. The opportunity: By analyzing driving behavior, these machine learning algorithms can help identify when a driver might be exhibiting early indicators of dementia and mild cognitive impairment.

A new study uses machine learning and senior driving data to detect dementia. Diagnosing a condition like dementia can be difficult under the best circumstances. But, sometimes, if it goes undiagnosed or ignored, something terrible can happen, particularly if the afflicted person is behind the wheel of a car. Thankfully, scientists are working on ways to help diagnose dementia earlier, and one of the ways that are being investigated is using machine learning combined with driving data, according to a recent report published by New Atlas. The study takes vehicle data, including trip length, time of trip from point A back to point A, and how many times a driver brakes hard during the trip and plugs it into an algorithm that helps detect signs of dementia or mild cognitive impairment.

Researchers at a Japanese university have devised an artificial intelligence (AI) based test to help detect early signs of dementia in patients. It is hoped that the new clinical system will lead to better treatments of the disease earlier, as it doesn't involve invasive medical imaging. Currently, scans are used in conjunction with cognitive function tests, such as the Mini-Mental State Examination (MMSE) – a combination that can be expensive, time-consuming, and distressing for some patients. However, an ageing population means that more people are developing the disease, hence the need to pursue faster, smarter, and easier-to-use tests. Helping patients to identify problems sooner may also help them stave off the effects of some conditions, and manage them more effectively.

Japanese scientists say they have developed a novel machine-learning technique that can detect dementia with over 90 per cent accuracy from conversations between humans and avatars on a computer. This technique developed by a team from Osaka University and Nara Institute of Science and Technology involves learning characteristics of sounds of elderly people who answer easy questions. Dementia could be distinguished by combining features of the disorder, such as delay in response to questions from avatars depending on the content of questions, intonation, articulation rate of the voice, and the percentage of nouns and verbs in utterance. An avatar is the graphical representation of the user or a character in an internet forum. "If this technology is further developed, it will become possible to know whether or not an elderly individual is in the early stages of dementia through conversation with computer avatars at home on a daily basis," said researcher Takashi Kudo.