شماره ركورد كنفرانس
4767
عنوان مقاله
Feature-Based Elderly Behavior Detection and Prediction in Smart Homes
عنوان به زبان ديگر
Feature-Based Elderly Behavior Detection and Prediction in Smart Homes
پديدآورندگان
Erfanmanesh Malihe m.erfanmanesh@shirazu.ac.ir Department of Computer Science and Engineering and IT Shiraz University, Shiraz, Iran , Tahayori Hooman tahayori@shirazu.ac.ir Department of Computer Science and Engineering and IT Shiraz University, Shiraz, Iran , Visconti Andrea Universita degli Studi di Milano Milano, Italy
تعداد صفحه
1
كليدواژه
activity recognition , machine learning , classification , behavior prediction , smart home
سال انتشار
1398
عنوان كنفرانس
اولين كنفرانس ملي فناوري ها و سيستم هاي محاسباتي مراقبت از سلامت
زبان مدرك
انگليسي
چكيده فارسي
One of the capabilities of smart home in the healthcare domain is helping elderly to live independently. This demands for detecting and monitoring their normal activities of daily living (ADLs). By considering changes in the occurrence of these normal activities we can decide about declining the health status of the elderly. Hence, the possibility of preventive care for some elderly people would be partly provided. In this paper, we propose a method for detection and prediction of elderly activities by extracting several features from available information. Obtained results reveal that the proposed features are more effective for detection and prediction of elderly behavior.
چكيده لاتين
One of the capabilities of smart home in the healthcare domain is helping elderly to live independently. This demands for detecting and monitoring their normal activities of daily living (ADLs). By considering changes in the occurrence of these normal activities we can decide about declining the health status of the elderly. Hence, the possibility of preventive care for some elderly people would be partly provided. In this paper, we propose a method for detection and prediction of elderly activities by extracting several features from available information. Obtained results reveal that the proposed features are more effective for detection and prediction of elderly behavior.
كشور
ايران
لينک به اين مدرک