Novel accelerometer-based algorithm detects early signals of Alzheimer’s disease in everyday motion behavior
October 8, 2013
The projected substantial increase in Alzheimer’s disease due to the higher life expectancy in modern societies is one of the great future challenges of health care systems worldwide. Alzheimer’s disease leads to significant changes in the temporal structure of activities that impair everyday activities. Abnormal motion behavior and degeneration of the sleep-waking cycle are among the most severe behavioral symptoms. An early detection and even a prediction of these behaviors would allow a timely onset of interventions that aim to delay the manifestation or exacerbation of symptoms and reduce the need of institutionalized care.
An interdisciplinary joint study by the Medical Faculty and the Faculty for Computer Science and Electrical Engineering of Rostock University and the German Center for Neurodegenerative Diseases (DZNE) Rostock has now established a novel sensing algorithm that allows detecting the effect of Alzheimer’s disease in unconstrained everyday motion behavior. In a dyad study with n=46 subjects (23 diagnosed with Alzheimer’s dementia, 23 healthy controls), the method achieves an accuracy of 91% when labeling an unknown subject as “AD” or “healthy control”. The algorithm uses spectral features of motion signals that are obtained by unobtrusive accelerometers worn by the subjects during their normal everyday activities.
“The method shows a substantially higher sensitivity than established behavioral rating scales, such as Cohen-Mansfield Agitation Index” emphasizes Prof. Teipel, head of DZNE Rostock and responsible for the study design. “This means, we now have a more sensitive instrument for detecting changes in behavior that allows us to monitor disease progress and the efficacy of interventions.” He adds: “And the measure we obtain is objective, it does not require the assessment by a human observer.”
“It is fascinating that our approach is able to work with unconstrained everyday motion behavior,” says Prof. Kirste from the Computer Science Department, who has designed the analysis algorithm. “Considering the high variance of everyday activities, we think that the ability to detect the influence of Alzheimer’s disease on the temporal structure of this behavior is a very important result.” He remarks: “On a practical level this means we can use low-cost sensing devices and we do not require the patients to perform specific controlled activities. Prospectively, it might even be possible to use the data of established devices such as mobile phones or navigation support devices for this purpose.”
The results of this study will be presented in the paper “Detecting the Effect of Alzheimer’s Disease on Everyday Motion Behavior,” scheduled for publication in issue 38(1) of the Journal of Alzheimer’s Disease. An early online version of this paper is available at DOI: 10.3233/JAD-130272.
This study is part of a larger joint project that aims at establishing the effect of Alzheimer’s disease on the temporospatial structure of an individual’s Life Space. These effects will be used for both diagnostic purposes and for assistive interventions, such as supporting orientation in everyday activities.
Rostock University, Department of Computer Science
Prof. Dr. Thomas Kirste
Phone: +49 381 498-7510
Rostock University, Department of Psychosomatic Medicine
German Center for Neurodegenerative Diseases (DZNE)
Prof. Dr. Stefan Teipel
Phone: +49 381 494-9471
Rostock University, founded in 1419, is the oldest University in the Baltic region and the third eldest university in Germany. Nine faculties offer 100 fields of study to currently 15.000 students. Rostock University has a unique interdisciplinary faculty that supports interdisciplinary research in important areas such as alternative energies, assistive systems, biomedical technologies, laser optics, life sciences and regenerative medicine. Internationally, Rostock University has close cooperations with 53 universities on all continents.
The Journal of Alzheimer’s Disease (http://www.j-alz.com) is an international multidisciplinary journal to facilitate progress in understanding the etiology, pathogenesis, epidemiology, genetics, behavior, treatment and psychology of Alzheimer’s disease. The journal publishes research reports, reviews, short communications, book reviews, and letters-to-the-editor. Groundbreaking research that has appeared in the journal includes novel therapeutic targets, mechanisms of disease and clinical trial outcomes. The Journal of Alzheimer’s Disease has an Impact Factor of 4.17 according to Thomson Reuters’ 2012 Journal Citation Reports. It is ranked #22 on the Index Copernicus Top 100 Journal List. The Journal is published by IOS Press (http://www.iospress.com/).