User-Centered Design and Fast Prototyping of an Ambient Assisted Living System for Elderly People

Author(s):  
Suzanne Kieffer ◽  
Jean-Yves Lionel Lawson ◽  
Benoît Macq
Author(s):  
Karolina Bezerra ◽  
José Machado ◽  
Vitor Carvalho ◽  
Filomena Soares ◽  
Bruno Silva ◽  
...  

From Ambient Assisted Living (AAL) perspective it is important to have information regarding the type of care needed by bedridden elderly people (BEP) living in their homes, in order to support independence, autonomy and maximize their quality of life. Some basic tasks as eating, taking a bath and the hygiene cares may be difficult to execute, regarding that almost always the main caregiver is the other element of the couple (husband or wife). Following this trend, the development of mechatronic devices is of upmost importance in creating solutions to facilitate these tasks. This paper presents the conceptual design of a mechatronic system especially devoted to the assistance during the bath of BEP. Issues as reducing the number of caregivers to only one to assist the bath and reducing the system’s handling complexity (because most of the time it will be used by an aged person) are considered. Visits to rehabilitation centers and hospitals, and respective working meetings, are considered in the development of the proposed mechatronic system.


2018 ◽  
Vol 7 (2.19) ◽  
pp. 52
Author(s):  
J Vivek ◽  
Gandla Maharnisha ◽  
Gandla Roopesh Kumar ◽  
Ch Karun Sagar ◽  
R Arunraj

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.  


2020 ◽  
pp. 793-821 ◽  
Author(s):  
Dulce Domingos ◽  
Ana Respício ◽  
Ricardo Martinho

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.


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