Among the behavioral symptoms of Alzheimer's, one of the most prominent is a change in the "temporal structure of activities" – in other words, the amount of time that it takes the patient to do things. With that in mind, German scientists have developed a new early detection method that involves attaching accelerometers to patients, in order to assess their movements.
In a collaboration between Rostock University and the German Center for Neurodegenerative Diseases, an algorithm was developed to detect such changes in peoples' everyday activities around the home. To test it, 46 subjects were each fitted with an ankle-mounted 3-axis accelerometer – 23 of those people had been diagnosed with Alzheimer's, while the other 23 constituted a healthy control group.
When the algorithm was used to assess the accelerometer data, it had a 91 percent rate of accuracy when determining which group each subject belonged to.
Although that's still not 100 percent, the researchers claim that it is more accurate than traditional behavioral rating scales, which are very much subject to observer bias. Additionally, patients can just go about their regular activities while being assessed, instead of having to perform specific tasks.
Down the road, it may even be possible for the accelerometer in the patient's own smartphone to take the place of the stand-alone accelerometers currently in use.
A paper on the research was recently published in the Journal of Alzheimer’s Disease.
Source: IOS PressShare
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