When David Graham wakes up in the morning, the flat white box that's Velcroed to the wall of his room in Robbie's Place, an assisted living facility in Marlborough, Massachusetts, begins recording his every movement. It knows when he gets out of bed, gets dressed, walks to his window, or goes to the bathroom. It can tell if he's sleeping or has fallen. It does this by using low-power wireless signals to map his gait speed, sleep patterns, location, and even breathing pattern. All that information gets uploaded to the cloud, where machine-learning algorithms find patterns in the thousands of movements he makes every day.
Artificial intelligence is slowly, but surely, showing potential in improving modern healthcare. In the UK, researchers recently used four AI algorithms that beat doctors in predicting heart attacks. Moreover, Google's DeepMind is fighting blindness with machine learning. Lately, medical science is seeing potential in the ability of AI systems to find meaning in datasets that are too complicated for us to process. This potential is perfectly applicable in modern healthcare practices.
Doctors could use artificial intelligence to diagnose dementia more accurately and give better treatment, scientists say. Researchers have invented a computer algorithm which can analyse MRI brain scans and learn how to recognise different types of dementia. They say that although many types of the brain-destroying condition have similar symptoms, they respond differently to treatment. Being able to correctly identify which type someone has means patients could be helped earlier on in their illness or given more targeted therapy. Experts say the research is'pioneering' and has'huge potential' in the future of treating dementia, expected to affect one million Britons by 2025.
The way that doctors monitor breathing, detect falls, track movement and gait in patients with Parkinson's or MS or analyze sleep requires invasive sensors and often needs to be done in a specialized setting. Other signs are simply too difficult to monitor so patients must write in a diary instead. MIT professor Dina Katabi's group has developed a prototype wireless device much like a WiFi router that uses a combination of radio signals and machine learning algorithms to monitor these physiological signs without wires--even through walls. In a presentation at last week's EmTech MIT conference, Katabi described how the system works and some of the potential applications. "We are all swimming in a sea of wireless signals, and every movement changes that electromagnetic field" because our bodies are primarily made of water and reflect these signals, Katabi said.
As many as one in five people age 65 or older experience "mild cognitive impairment" -- a condition marked by a slight decline in memory, language, or thought. Affected individuals may be prone to forgetting appointments or losing the thread of conversations. They also have a higher-than-average risk of developing the more pronounced cognitive decline of Alzheimer's disease. Yet for the majority of people, symptoms do not progress. In fact, in some instances, the symptoms can be temporary or reversible.