Recognition of Activities of Daily Living from Topic Model
نویسندگان
چکیده
منابع مشابه
Recognition of Activities of Daily Living from Topic Model
Research in ubiquitous and pervasive technologies have made it possible to recognise activities of daily living through non-intrusive sensors. The data captured from these sensors are required to be classified using various machine learning or knowledge driven techniques to infer and recognise activities. The process of discovering the activities and activity-object patterns from the sensors ta...
متن کاملADL™: A Topic Model for Discovery of Activities of Daily Living in a Smart Home
We present an unsupervised approach for discovery of Activities of Daily Living (ADL) in a smart home. Activity discovery is an important enabling technology, for example to tackle the healthcare requirements of elderly people in their homes. The technique applied most often is supervised learning, which relies on expensive labelled data and lacks the flexibility to discover unseen activities. ...
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Introduction: One of the most popular methods for evaluating old people’s health condition is to assess their functional practice. The aim of this study was to assess the status of daily living activities among the older people of Maku, Iran. Methods: The present cross-sectional study was accomplished among 216 older people in Maku via simple random sampling. Participant’s subj...
متن کاملHealth Promotion Behaviours and Level of Activities of Daily Living and Instrumental Activities of Daily Living Among Elderly People in West Region of Tehran: A Cross-Sectional Survey
Objectives: As individuals live longer, health promotion behaviors get even more important, particularly with regard to maintaining functional independence and improving quality of life. The purpose of this study was to explore the relationship between health promotion behaviors and level of Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) among elderly people...
متن کاملAn Improved Elman Neural Network for Daily Living Activities Recognition
One of the main issues regarding the monitoring of persons in a smart home environment is the accuracy of the daily control of the person, the health prevention and the timely prediction of abnormal situations. To tackle this problem, this work proposes the use of an improved version of the Elman Neural Network (Elman-NN). In order to minimize the error between inputs and desired outputs, we op...
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ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2016
ISSN: 1877-0509
DOI: 10.1016/j.procs.2016.09.007