High Performance Activity Recognition Framework for Ambient Assisted Living in the Home Network Environment

2014 ◽  
Vol E97.B (9) ◽  
pp. 1766-1778 ◽  
Author(s):  
Konlakorn WONGPATIKASEREE ◽  
Azman Osman LIM ◽  
Mitsuru IKEDA ◽  
Yasuo TAN
Keyword(s):  
Activity Recognition ◽  
Assisted Living ◽  
High Performance ◽  
Ambient Assisted Living ◽  
Home Network ◽  
Network Environment

Activity Recognition for Ambient Assisted Living Using Off-the-shelf Motion Sensing Input Devices

2019 ◽  
Author(s):  
Elena Cebanov ◽  
Ciprian Dobre ◽  
Alexandru Gradinaru ◽  
Radu-Ioan Ciobanu ◽  
Valeriu-Daniel Stanciu
Keyword(s):  
Activity Recognition ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Motion Sensing ◽  
Input Devices

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 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.

Data Segmentation Methods for Activity Recognition in Ambient Assisted Living

2021 ◽  
Author(s):  
Yuyan Zhao ◽  
Haibao Chen ◽  
Ting Zhao ◽  
Jie Chen ◽  
Siying Li ◽  
...  
Keyword(s):  
Activity Recognition ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Data Segmentation ◽  
Segmentation Methods
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