Title :
Analyzing Activity Behavior and Movement in a Naturalistic Environment Using Smart Home Techniques
Author :
Cook, Diane J. ; Schmitter-Edgecombe, Maureen ; Dawadi, Prafulla
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Washington State Univ., Pullman, WA, USA
Abstract :
One of the many services that intelligent systems can provide is the ability to analyze the impact of different medical conditions on daily behavior. In this study, we use smart home and wearable sensors to collect data, while (n = 84) older adults perform complex activities of daily living. We analyze the data using machine learning techniques and reveal that differences between healthy older adults and adults with Parkinson disease not only exist in their activity patterns, but that these differences can be automatically recognized. Our machine learning classifiers reach an accuracy of 0.97 with an area under the ROC curve value of 0.97 in distinguishing these groups. Our permutation-based testing confirms that the sensor-based differences between these groups are statistically significant.
Keywords :
biomechanics; body sensor networks; cognition; data analysis; diseases; learning (artificial intelligence); medical diagnostic computing; medical disorders; neurophysiology; pattern classification; sensitivity analysis; telemedicine; ubiquitous computing; Parkinson disease; ROC curve value; activity behavior; daily living; data analysis; data collection; intelligent systems; machine learning classifiers; machine learning techniques; medical conditions; movement analysis; naturalistic environment; permutation-based testing; sensor-based differences; smart home techniques; wearable sensors; Machine learning; Parkinson´s disease; Patient monitoring; Pervasive computing; Smart homes; Wearable sensors; Machine learning; Parkinson disease; Parkinson disease (PD); machine learning; mild cognitive impairment; mild cognitive impairment (MCI); pervasive computing;
Journal_Title :
Biomedical and Health Informatics, IEEE Journal of
DOI :
10.1109/JBHI.2015.2461659
