Ambient assisted living framework for elderly care using Internet of medical things, smart sensors, and GRU deep learning techniques

2021 ◽  
pp. 1-19
Author(s):  
Liyakathunisa ◽  
Abdullah Alsaeeedi ◽  
Saima Jabeen ◽  
Hoshang Kolivand
Keyword(s):  
Deep Learning ◽  
Assisted Living ◽  
Healthy Aging ◽  
Elderly Care ◽  
Ambient Assisted Living ◽  
Age Related ◽  
Learning Techniques ◽  
Internet Of Medical Things ◽  
Gated Recurrent Unit ◽  
State Of Art

Due to the increase in the global aging population and its associated age-related challenges, various cognitive, physical, and social problems can arise in older adults, such as reduced walking speed, mobility, falls, fatigue, difficulties in performing daily activities, memory-related and social isolation issues. In turn, there is a need for continuous supervision, intervention, assistance, and care for elderly people for active and healthy aging. This research proposes an ambient assisted living system with the Internet of Medical Things that leverages deep learning techniques to monitor and evaluate the elderly activities and vital signs for clinical decision support. The novelty of the proposed approach is that bidirectional Gated Recurrent Unit, and Gated Recurrent Unit deep learning techniques with mutual information-based feature selection technique is applied to select robust features to identify the target activities and abnormalities. Experiments were conducted on two datasets (the recorded Ambient Assisted Living data and MHealth benchmark data) with bidirectional Gated Recurrent Unit, and Gated Recurrent Unit deep learning techniques and compared with other state of art techniques. Different evaluation metrics were used to assess the performance, findings reveal that bidirectional Gated Recurrent Unit deep learning techniques outperform other state of art approaches with an accuracy of 98.14% for Ambient Assisted Living data, and 99.26% for MHealth data using the proposed approach.

scholarly journals Improving Efficiency in Separating Blood Vessels from Retinal Images with Deep Learning Techniques

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3637-3640
Keyword(s):  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Macular Degeneration ◽  
Blood Vessels ◽  
Age Related Macular Degeneration ◽  
Retinal Images ◽  
Retinal Vessels ◽  
Age Related ◽  
Learning Techniques ◽  
Retinal Pathologies

Retinal vessels ID means to isolate the distinctive retinal configuration issues, either wide or restricted from fundus picture foundation, for example, optic circle, macula, and unusual sores. Retinal vessels recognizable proof investigations are drawing in increasingly more consideration today because of pivotal data contained in structure which is helpful for the identification and analysis of an assortment of retinal pathologies included yet not restricted to: Diabetic Retinopathy (DR), glaucoma, hypertension, and Age-related Macular Degeneration (AMD). With the advancement of right around two decades, the inventive methodologies applying PC supported systems for portioning retinal vessels winding up increasingly significant and coming nearer. Various kinds of retinal vessels segmentation strategies discussed by using Deep Learning methods. At that point, the pre-processing activities and the best in class strategies for retinal vessels distinguishing proof are presented.

Forecasting Trends in an Ambient Assisted Living Environment Using Deep Learning

2021 ◽  
Author(s):  
Guillaume Gingras ◽  
Mehdi Adda ◽  
Abdenour Bouzouane ◽  
Hussein Ibrahim ◽  
Clemence Dallaire
Keyword(s):  
Deep Learning ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Living Environment

scholarly journals Ambient Assisted Living: A Research on Human Activity Recognition and Vital Health Sign Monitoring using Deep Learning Approaches

2019 ◽  
Vol 8 (6S4) ◽  
pp. 531-540
Keyword(s):  
Deep Learning ◽  
Activity Recognition ◽  
Human Activity ◽  
Assisted Living ◽  
Independent Living ◽  
Ambient Assisted Living ◽  
The Elderly ◽  
Human Activity Recognition ◽  
Living Environment ◽  
Learning Approaches

The rise in life expectancy rate and dwindled birth rate in new age society has led to the phenomenon of population ageing which is being witnessed across the world from past few decades. India is also a part of this demographic transition which will have the direct impact on the societal and economic conditions of the country. In order to effectively deal with the prevailing phenomenon, stakeholders involved are coming up with the Information and Communication Technology (ICT) based ecosystem to address the needs of elderly people such as independent living, activity recognition, vital health sign monitoring, prevention from social isolation etc. Ambient Assisted Living (AAL) is one such ecosystem which is capable of providing safe and secured living environment for the elderly and disabled people. In this paper we will focus on reviewing the sensor based Human Activity Recognition (HAR) and Vital Health Sign Monitoring (VHSM) which is applicable for AAL environments. At first we generally describe the AAL environment. Next we present brief insights into sensor modalities and different deep learning architectures. Later, we survey the existing literature for HAR and VHSM based on sensor modality and deep learning approach used.

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 Human Detection in Video Surveillance

2021 ◽  
Vol 03 (01) ◽  
pp. 27-34
Author(s):  
Sushama Khanvilkar ◽  
◽  
Santosh Gupta ◽  
Hinal Rane ◽  
Calvin Galbaw ◽  
...  
Keyword(s):  
Deep Learning ◽  
Video Surveillance ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Human Detection ◽  
Fast Computation ◽  
Intelligent Surveillance ◽  
Fully Connected ◽  
Deep Learning Model ◽  
Naive Approach

Recognition of the human activities in videos has gathered numerous demands in various applications of computer vision like Ambient Assisted Living, intelligent surveillance, Human-Computer interaction. One of the most pioneering techniques for Human Detection in Video Surveillance based on deep learning and this project mainly focuses on various approaches based on that. This paper provides an idea of solution to use video surveillance more effectively, by detecting any humans present and notifying the concerned people. The deep learning model, preferred for fast computation, Convolution Neural Network is used by stacking 3 blocks of layers on fully connected layers. This provided an identification of humans and naïve approach to eliminate inanimate human like objects such as mannequins.

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.

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.

scholarly journals Deep learning-based ambient assisted living for self-management of cardiovascular conditions

2021 ◽  
Author(s):  
Maria Ahmed Qureshi ◽  
Kashif Naseer Qureshi ◽  
Gwanggil Jeon ◽  
Francesco Piccialli
Keyword(s):  
Deep Learning ◽  
Cardiovascular Diseases ◽  
Learning Strategies ◽  
Assisted Living ◽  
New Technologies ◽  
Ambient Assisted Living ◽  
World Health ◽  
Self Management ◽  
Ageing Population ◽  
Cloud Models

AbstractAccording to the World Health Organization, cardiovascular diseases contribute to 17.7 million deaths per year and are rising with a growing ageing population. In order to handle these challenges, the evolved countries are now evolving workable solutions based on new communication technologies such as ambient assisted living. In these solutions, the most well-known solutions are wearable devices for patient monitoring, telemedicine and mHealth systems. This systematic literature review presents the detailed literature on ambient assisted living solutions and helps to understand how ambient assisted living helps and motivates patients with cardiovascular diseases for self-management to reduce associated morbidity and mortalities. Preferred reporting items for systematic reviews and meta-analyses technique are used to answer the research questions. The paper is divided into four main themes, including self-monitoring wearable systems, ambient assisted living in aged populations, clinician management systems and deep learning-based systems for cardiovascular diagnosis. For each theme, a detailed investigation shows (1) how these new technologies are nowadays integrated into diagnostic systems and (2) how new technologies like IoT sensors, cloud models, machine and deep learning strategies can be used to improve the medical services. This study helps to identify the strengths and weaknesses of novel ambient assisted living environments for medical applications. Besides, this review assists in reducing the dependence on caregivers and the healthcare systems.

scholarly journals Ambient Assisted Living: A Review of Technologies, Methodologies and Future Perspectives for Healthy Aging of Population

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3549
Author(s):  
Grazia Cicirelli ◽  
Roberto Marani ◽  
Antonio Petitti ◽  
Annalisa Milella ◽  
Tiziana D’Orazio
Keyword(s):  
Quality Of Life ◽  
Assisted Living ◽  
Independent Living ◽  
Healthy Aging ◽  
Ambient Assisted Living ◽  
Comprehensive Analysis ◽  
Future Perspectives ◽  
New Challenges ◽  
Points Of View

Over the last decade, there has been considerable and increasing interest in the development of Active and Assisted Living (AAL) systems to support independent living. The demographic change towards an aging population has introduced new challenges to today’s society from both an economic and societal standpoint. AAL can provide an arrary of solutions for improving the quality of life of individuals, for allowing people to live healthier and independently for longer, for helping people with disabilities, and for supporting caregivers and medical staff. A vast amount of literature exists on this topic, so this paper aims to provide a survey of the research and skills related to AAL systems. A comprehensive analysis is presented that addresses the main trends towards the development of AAL systems both from technological and methodological points of view and highlights the main issues that are worthy of further investigation.

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