scholarly journals An ambient assisted living system for dementia patients

2019 ◽  
Vol 27 (3) ◽  
pp. 2361-2378
Author(s):  
Özgün YILMAZ
Keyword(s):  
Assisted Living ◽  
Ambient Assisted Living ◽  
Living System ◽  
Dementia Patients

scholarly journals Context Awareness Technology Using Parallel Mining for Ambient Assisted Living System

2018 ◽  
Vol 7 (2.19) ◽  
pp. 52
Author(s):  
J Vivek ◽  
Gandla Maharnisha ◽  
Gandla Roopesh Kumar ◽  
Ch Karun Sagar ◽  
R Arunraj
Keyword(s):  
Health Care ◽  
Big Data ◽  
Knowledge Discovery ◽  
Assisted Living ◽  
Context Awareness ◽  
Health Care Services ◽  
Ambient Assisted Living ◽  
Living System ◽  
Health Condition ◽  
Parallel Mining

In  this  paper,  context  awareness  is  a  promising  technology  that  provides  health care services and a niche  area of big data paradigm. The   drift  in  Knowledge  Discovery  from  Data  refers  to  a  set  of  activities  designed  to refine and  extract  new knowledge from complex  datasets.  The   proposed  model  facilitates  a  parallel  mining  of  frequent item sets for Ambient Assisted Living (AAL) System [a.k.a. Health  Care [System]  of  big  data that  reside   inside  a  cloud  environment.  We  extend  a  knowledge  discovery framework for  processing  and  classifying  the  abnormal  conditions of patients having fluctuations in Blood Pressure (BP) and Heart Rate(HR) and storing  this data  sets  called  Big data  into Cloud to access from  anywhere   when  needed.   This   accessed data is used to compare the new data with it, which helps to know the patients health condition.  

Reliability of IoT-Aware BPMN Healthcare Processes

2020 ◽  
pp. 793-821 ◽  
Author(s):  
Dulce Domingos ◽  
Ana Respício ◽  
Ricardo Martinho
Keyword(s):  
Business Process ◽  
Assisted Living ◽  
Process Model ◽  
Ambient Assisted Living ◽  
Living System ◽  
Biomedical Sensors ◽  
Language Extension ◽  
Healthcare Process ◽  
Healthcare Processes ◽  
Electronic Tags

BPMN (Business Process Model and Notation) has become the de-facto business process modelling language standard. Healthcare processes have been increasingly incorporating participants other than humans, including Internet of Things (IoT) physical devices such as biomedical sensors or patient electronic tags. Due to its critical requirements, IoT-aware healthcare processes justify the relevance of Quality of Services aspects, such as reliability, availability, and cost, among others. This chapter focuses on reliability and proposes to use the Stochastic Workflow Reduction (SWR) method to calculate the reliability of IoT-aware BPMN healthcare processes. In addition, the chapter proposes a BPMN language extension to provide processes with reliability information. This way, at design time, modellers can analyse alternatives and, at run time, reliability information can be used to select participants, execute services, or monitor process executions. The proposal is applied to an Ambient Assisted Living system use case, a rich example of an IoT-aware healthcare process.

scholarly journals Behavioral Biometrics in Assisted Living: A Methodology for Emotion Recognition

2016 ◽  
Vol 6 (4) ◽  
pp. 1035-1044
Author(s):  
S. Xefteris ◽  
N. Doulamis ◽  
V. Andronikou ◽  
T. Varvarigou ◽  
G. Cambourakis
Keyword(s):  
Risk Assessment ◽  
Neurodegenerative Diseases ◽  
Facial Expressions ◽  
Assisted Living ◽  
Service Oriented Architecture ◽  
Ambient Assisted Living ◽  
Living Environment ◽  
Emotional Status ◽  
Behavioral Biometrics ◽  
Dementia Patients

Behavioral biometrics aim at providing algorithms for the automatic recognition of individual behavioral traits, stemming from a person’s actions, attitude, expressions and conduct. In the field of ambient assisted living, behavioral biometrics find an important niche. Individuals suffering from the early stages of neurodegenerative diseases (MCI, Alzheimer’s, dementia) need supervision in their daily activities. In this context, an unobtrusive system to monitor subjects and alert formal and informal carers providing information on both physical and emotional status is of great importance and positively affects multiple stakeholders. The primary aim of this paper is to describe a methodology for recognizing the emotional status of a subject using facial expressions and to identify its uses, in conjunction with pre-existing risk-assessment methodologies, for its integration into the context of a smart monitoring system for subjects suffering from neurodegenerative diseases. Paul Ekman’s research provided the background on the universality of facial expressions as indicators of underlying emotions. The methodology then makes use of computational geometry, image processing and graph theory algorithms for the detection of regions of interest and then a neural network is used for the final classification. Findings are coupled with previous published work for risk assessment and alert generation in the context of an ambient assisted living environment based on Service oriented architecture principles, aimed at remote web-based estimation of the cognitive and physical status of MCI and dementia patients.

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