scholarly journals IoT Wearable Sensors and Devices in Elderly Care: A Literature Review

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2826 ◽  
Author(s):  
Thanos G. Stavropoulos ◽  
Asterios Papastergiou ◽  
Lampros Mpaltadoros ◽  
Spiros Nikolopoulos ◽  
Ioannis Kompatsiaris
Keyword(s):  
Assisted Living ◽  
Elderly Care ◽  
Wearable Sensors ◽  
Ambient Assisted Living ◽  
Fall Detection ◽  
Individual Case ◽  
Current State ◽  
Sensing Technology ◽  
Promising Solution ◽  
Global Population

The increasing ageing global population is causing an upsurge in ailments related to old age, primarily dementia and Alzheimer’s disease, frailty, Parkinson’s, and cardiovascular disease, but also a general need for general eldercare as well as active and healthy ageing. In turn, there is a need for constant monitoring and assistance, intervention, and support, causing a considerable financial and human burden on individuals and their caregivers. Interconnected sensing technology, such as IoT wearables and devices, present a promising solution for objective, reliable, and remote monitoring, assessment, and support through ambient assisted living. This paper presents a review of such solutions including both earlier review studies and individual case studies, rapidly evolving in the last decade. In doing so, it examines and categorizes them according to common aspects of interest such as health focus, from specific ailments to general eldercare; IoT technologies, from wearables to smart home sensors; aims, from assessment to fall detection and indoor positioning to intervention; and experimental evaluation participants duration and outcome measures, from acceptability to accuracy. Statistics drawn from this categorization aim to outline the current state-of-the-art, as well as trends and effective practices for the future of effective, accessible, and acceptable eldercare with technology.

scholarly journals Contactless Interactive Fall Detection and Sleep Quality Estimation for Supporting Elderly with Incipient Dementia

2020 ◽  
Vol 6 (3) ◽  
pp. 388-391
Author(s):  
Roman Siedel ◽  
Tobias Scheck ◽  
Ana C. Perez Grassi ◽  
Julian B. Seuffert ◽  
André Apitzsch ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Fall Detection ◽  
Quality Estimation ◽  
Emergency Situations ◽  
People With Dementia ◽  
Affected Person ◽  
Development State ◽  
Current Behaviour

AbstractIn recent years, the demographic change in conjunction with a lack of professional caregivers led to retirement homes reaching capacity. The Alzheimer Disease International stated that over 50 million people suffered from dementia in 2019 worldwide and twice the amount will presumably be effected in 2030. The field of Ambient Assisted Living (AAL) tackles this problem by facilitating technical system-aided everyday life. AUXILIA is such an AAL system and does not only support elderly people with dementia in an early phase, but also monitors their activities to provide behaviour analysis results for care attendants, relatives and physicians. Moreover, the system is capable of recognizing emergency situations like human falls. Furthermore, sleep quality estimation is employed to be able to draw conclusions about the current behaviour of an affected person. This article presents the current development state of AUXILIA.

A robust multimodal fall detection method for ambient assisted living applications

2010 ◽  
Author(s):  
Hande Ozgur Alemdar ◽  
Yunus Emre Kara ◽  
Mustafa Ozan Ozen ◽  
Gokhan Remzi Yavuz ◽  
Ozlem Durmaz Incel ◽  
...  
Keyword(s):  
Assisted Living ◽  
Detection Method ◽  
Ambient Assisted Living ◽  
Fall Detection

scholarly journals IndoorCare: Low-Cost Elderly Activity Monitoring System through Image Processing

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6051
Author(s):  
Daniel Fuentes ◽  
Luís Correia ◽  
Nuno Costa ◽  
Arsénio Reis ◽  
José Ribeiro ◽  
...  
Keyword(s):  
Low Income ◽  
Assisted Living ◽  
Rural Areas ◽  
Low Cost ◽  
Elderly Care ◽  
Ambient Assisted Living ◽  
The Elderly ◽  
Case Scenario ◽  
Care Services ◽  
Socially Excluded

The Portuguese population is aging at an increasing rate, which introduces new problems, particularly in rural areas, where the population is small and widely spread throughout the territory. These people, mostly elderly, have low income and are often isolated and socially excluded. This work researches and proposes an affordable Ambient Assisted Living (AAL)-based solution to monitor the activities of elderly individuals, inside their homes, in a pervasive and non-intrusive way, while preserving their privacy. The solution uses a set of low-cost IoT sensor devices, computer vision algorithms and reasoning rules, to acquire data and recognize the activities performed by a subject inside a home. A conceptual architecture and a functional prototype were developed, the prototype being successfully tested in an environment similar to a real case scenario. The system and the underlying concept can be used as a building block for remote and distributed elderly care services, in which the elderly live autonomously in their homes, but have the attention of a caregiver when needed.

scholarly journals Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4227 ◽  
Author(s):  
Andres Sanchez-Comas ◽  
Kåre Synnes ◽  
Josef Hallberg
Keyword(s):  
Activity Recognition ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Fall Detection ◽  
Research Field ◽  
Health Security ◽  
Assistive Robots ◽  
Road Map ◽  
The People

Activity recognition (AR) from an applied perspective of ambient assisted living (AAL) and smart homes (SH) has become a subject of great interest. Promising a better quality of life, AR applied in contexts such as health, security, and energy consumption can lead to solutions capable of reaching even the people most in need. This study was strongly motivated because levels of development, deployment, and technology of AR solutions transferred to society and industry are based on software development, but also depend on the hardware devices used. The current paper identifies contributions to hardware uses for activity recognition through a scientific literature review in the Web of Science (WoS) database. This work found four dominant groups of technologies used for AR in SH and AAL—smartphones, wearables, video, and electronic components—and two emerging technologies: Wi-Fi and assistive robots. Many of these technologies overlap across many research works. Through bibliometric networks analysis, the present review identified some gaps and new potential combinations of technologies for advances in this emerging worldwide field and their uses. The review also relates the use of these six technologies in health conditions, health care, emotion recognition, occupancy, mobility, posture recognition, localization, fall detection, and generic activity recognition applications. The above can serve as a road map that allows readers to execute approachable projects and deploy applications in different socioeconomic contexts, and the possibility to establish networks with the community involved in this topic. This analysis shows that the research field in activity recognition accepts that specific goals cannot be achieved using one single hardware technology, but can be using joint solutions, this paper shows how such technology works in this regard.

Multi-sensing Monitoring and Knowledge-driven Analysis for Dementia Assessment

2015 ◽  
Vol 6 (4) ◽  
pp. 77-92 ◽  
Author(s):  
Thanos G. Stavropoulos ◽  
Georgios Meditskos ◽  
Efstratios Kontopoulos ◽  
Ioannis Kompatsiaris
Keyword(s):  
Assisted Living ◽  
Common Knowledge ◽  
Wearable Sensors ◽  
Ambient Assisted Living ◽  
Semantic Interpretation ◽  
Sensor Data ◽  
End User ◽  
People With Dementia ◽  
Service Oriented ◽  
Assessment And Monitoring

DemaWare is a Service-Oriented platform that aids in the timely assessment and monitoring of people with dementia in an Ambient Assisted Living context. This work presents in detail the underlying modules integrated in DemaWare, providing both software and hardware services. The system coordinates the retrieval of raw sensor data from a variety of sources, such as ambient and wearable sensors, and their processing into a common knowledge base. The semantic interpretation performed afterwards reasons upon collected knowledge and infers higher level observations. Finally, all knowledge is presented in suitable end-user applications that support various scenarios, e.g. lab assessment trials and monitoring in nursing home environments.

scholarly journals Designing a Cyber-Physical System for Ambient Assisted Living: A Use-Case Analysis for Social Robot Navigation in Caregiving Centers

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 4005
Author(s):  
Luis V. Calderita ◽  
Araceli Vega ◽  
Sergio Barroso-Ramírez ◽  
Pablo Bustos ◽  
Pedro Núñez
Keyword(s):  
Assisted Living ◽  
Physical System ◽  
Cognitive Rehabilitation ◽  
Elderly Care ◽  
Cognitive Architecture ◽  
Ambient Assisted Living ◽  
Physical World ◽  
Primary Objective ◽  
Cyber Physical System ◽  
Digital Twin

The advances of the Internet of Things, robotics, and Artificial Intelligence, to give just a few examples, allow us to imagine promising results in the development of smart buildings in the near future. In the particular case of elderly care, there are new solutions that integrate systems that monitor variables associated with the health of each user or systems that facilitate physical or cognitive rehabilitation. In all these solutions, it is clear that these new environments, usually called Ambient Assisted Living (AAL), configure a Cyber-Physical System (CPS) that connects information from the physical world to the cyber-world with the primary objective of adding more intelligence to these environments. This article presents a CPS-AAL for caregiving centers, with the main novelty that includes a Socially Assistive Robot (SAR). The CPS-AAL presented in this work uses a digital twin world with the information acquired by all devices. The basis of this digital twin world is the CORTEX cognitive architecture, a set of software agents interacting through a Deep State Representation (DSR) that stored the shared information between them. The proposal is evaluated in a simulated environment with two use cases requiring interaction between the sensors and the SAR in a simulated caregiving center.

scholarly journals Social-aware Event Handling within the FallRisk Project

2017 ◽  
Vol 56 (01) ◽  
pp. 63-73 ◽  
Author(s):  
Jan Van den Bergh ◽  
Sven Coppers ◽  
Shirley Elprama ◽  
Jelle Nelis ◽  
Stijn Verstichel ◽  
...  
Keyword(s):  
Assisted Living ◽  
Ambient Assisted Living ◽  
Fall Detection ◽  
Smart Devices ◽  
Accurate Analysis ◽  
Fall Incident ◽  
Detection Systems ◽  
Event Handling ◽  
Current Guidelines ◽  
The Internet Of Things

SummaryObjectives: With the uprise of the Internet of Things, wearables and smartphones are moving to the foreground. Ambient Assisted Living solutions are, for example, created to facilitate ageing in place. One example of such systems are fall detection systems. Currently, there exists a wide variety of fall detection systems using different methodologies and technologies. However, these systems often do not take into account the fall handling process, which starts after a fall is identified or this process only consists of sending a notification. The FallRisk system delivers an accurate analysis of incidents occurring in the home of the older adults using several sensors and smart devices. Moreover, the input from these devices can be used to create a social-aware event handling process, which leads to assisting the older adult as soon as possible and in the best possible way.Methods: The FallRisk system consists of several components, located in different places. When an incident is identified by the FallRisk system, the event handling process will be followed to assess the fall incident and select the most appropriate caregiver, based on the input of the smartphones of the caregivers. In this process, availability and location are automatically taken into account.Results: The event handling process was evaluated during a decision tree workshop to verify if the current day practices reflect the requirements of all the stakeholders. Other knowledge, which is uncovered during this workshop can be taken into account to further improve the process.Conclusions: The FallRisk offers a way to detect fall incidents in an accurate way and uses context information to assign the incident to the most appropriate caregiver. This way, the consequences of the fall are minimized and help is at location as fast as possible. It could be concluded that the current guidelines on fall handling reflect the needs of the stakeholders. However, current technology evolutions, such as the uptake of wearables and smartphones, enables the improvement of these guidelines, such as the automatic ordering of the caregivers based on their location and availability.

Biomedical Engineering and Elderly Support

2013 ◽  
Vol 2 (2) ◽  
pp. 21-37 ◽  
Author(s):  
Antonis S. Billis ◽  
Evdokimos I. Konstantinidis ◽  
Vicky Zilidou ◽  
Kush Wadhwa ◽  
Aristea Kyriaki Ladas ◽  
...  
Keyword(s):  
Assisted Living ◽  
Independent Living ◽  
Elderly Care ◽  
Ambient Assisted Living ◽  
Modern Society ◽  
Public Health Services ◽  
Physical Health Problems ◽  
Senior Population ◽  
Funded Project ◽  
Mental And Physical Health

The undoubted growing percentage of senior population (age 65+) has been obvious in the modern society during the last few decades. Ambient Assisted Living (AAL) technologies arise as a promising means of elderly care, thereby reducing both carers’ workload and public health services costs. LongLastingMemories, an EU funded project, aimed at alleviating senior people mental and physical health problems by integrating state of the art computer-aided technology and prolonging their independent living by providing a smart home solution. Five rounds of multicentric pilots were planned and conducted in order to test that objectives such as accessibility, user acceptance and perceived effectiveness of the service were met by the final LLM prototype. A questionnaire survey was conducted after each pilot with several stakeholders, such as senior subjects and formal careers, proving the wide acceptance of our service and its applicability in the domain of elderly healthcare.

Sign in / Sign up

Export Citation Format

Share Document