Human Behavior Recognition Based on Motion Data Analysis

2019 ◽  
Vol 34 (09) ◽  
pp. 2056005 ◽  
Author(s):  
Zhenzhen Huang ◽  
Qiang Niu ◽  
Shuo Xiao
Keyword(s):  
Human Behavior ◽  
The Elderly ◽  
Recall Rate ◽  
Daily Activities ◽  
Smart Devices ◽  
Human Beings ◽  
Time Data ◽  
Motion Data ◽  
Low Pass ◽  
Human Behavior Recognition

The development of sensor technologies and smart devices has made it possible to realize real-time data acquisition of human beings. Human behavior monitoring is the process of obtaining activity information with wearables and computer technology. In this paper, we design a data preprocessing method based on the data collected by a single three-axis accelerometer. We first use Butterworth filter as low-pass filtering to remove the noise. Then, we propose a KGA algorithm to remove abnormal data and smooth them at the same time. This method uses genetic algorithm to optimize the parameters of Kalman filter. After that, we use a threshold-based method to identify falls that are harmful to the elderly. The key point of this method is to distinguish falls from people’s daily activities. According to the characteristics of human falls, we extract eigenvalues that can effectively distinguish daily activities from falls. In addition, we use cross-validation to determine the threshold of the method. The results show that in the analysis of 11 kinds of human daily activities and 15 types of falls, our method can distinguish 15 types of falls. The recognition recall rate in our method reaches 99.1%.

scholarly journals Interconnecting IoT Devices to Improve the QoL of Elderly People

2020 ◽  
pp. 148-165
Author(s):  
Daniel Flores-Martin ◽  
Alejandro Pérez-Vereda ◽  
Javier Berrocal ◽  
Carlos Canal ◽  
Juan M. Murillo
Keyword(s):  
Elderly People ◽  
Population Aging ◽  
The Elderly ◽  
Daily Activities ◽  
Smart Devices ◽  
Specific Situation ◽  
Iot Devices ◽  
Lock In ◽  
Elderly Living

The rate at which the internet is growing is unstoppable due to the large number of connected smart devices. Manufacturers often develop specific protocols for their own devices that do not usually follow any standards. This hinders the interconnection and coordination of devices from different manufacturers, limiting the number of daily activities that can be supported. Some works are proposing different techniques to reduce this barrier and avoid the vendor lock-in issue. Nevertheless, this interconnection should also depend on the context. In this chapter, the authors propose a system to dynamically identify the interconnections required each specific situation depending on the context. This proposal has been tested in case studies focused on elderly people with the aim of automating their daily tasks and improving their quality of life. Further, in a world with an accelerated population aging, there is an increasing interest on developing solutions for the elderly living assistance through IoT systems.

scholarly journals Pro-Environmental Behavior in an Aging World: Evidence from 31 Countries

2021 ◽  
Vol 18 (4) ◽  
pp. 1748
Author(s):  
Yan Wang ◽  
Feng Hao ◽  
Yunxia Liu
Keyword(s):  
Linear Models ◽  
Population Change ◽  
Population Aging ◽  
Environmental Behavior ◽  
National Level ◽  
The Elderly ◽  
Human Beings ◽  
Individual Level ◽  
Contemporary World ◽  
The Individual

Population change and environmental degradation have become two of the most pressing issues for sustainable development in the contemporary world, while the effect of population aging on pro-environmental behavior remains controversial. In this paper, we examine the effects of individual and population aging on pro-environmental behavior through multilevel analyses of cross-national data from 31 countries. Hierarchical linear models with random intercepts are employed to analyze the data. The findings reveal a positive relationship between aging and pro-environmental behavior. At the individual level, older people are more likely to participate in environmental behavior (b = 0.052, p < 0.001), and at the national level, living in a country with a greater share of older persons encourages individuals to behave sustainably (b = 0.023, p < 0.01). We also found that the elderly are more environmentally active in an aging society. The findings imply that the longevity of human beings may offer opportunities for the improvement of the natural environment.

3D Human behavior recognition based on binocular vision and face–hand feature

Optik ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4712-4717 ◽  
Author(s):  
Qing Ye ◽  
Junfeng Dong ◽  
Yongmei Zhang
Keyword(s):  
Human Behavior ◽  
Binocular Vision ◽  
Behavior Recognition ◽  
Human Behavior Recognition

Based on spatio-temporal graph convolution networks with residual connection for intelligence behavior recognition

2021 ◽  
pp. 002072092199660
Author(s):  
Yinong Zhang ◽  
Shanshan Guan ◽  
Cheng Xu ◽  
Hongzhe Liu
Keyword(s):  
Human Behavior ◽  
Behavior Recognition ◽  
Convolutional Network ◽  
Skeleton Model ◽  
Basic Technology ◽  
Temporal Model ◽  
Temporal Graph ◽  
Spatio Temporal ◽  
Human Behavior Recognition ◽  
Behavior Characteristics

In the era of intelligent education, human behavior recognition based on computer vision is an important branch of pattern recognition. Human behavior recognition is a basic technology in the fields of intelligent monitoring and human-computer interaction in education. The dynamic changes of human skeleton provide important information for the recognition of educational behavior. Traditional methods usually use manual information to label or traverse rules only, resulting in limited representation capabilities and poor generalization performance of the model. In this paper, a kind of dynamic skeleton model with residual is adopted—a spatio-temporal graph convolutional network based on residual connections, which not only overcomes the limitations of previous methods, but also can learn the spatio-temporal model from the skeleton data. In the big bone NTU-RGB + D dataset, the network model not only improved the representation ability of human behavior characteristics, but also improved the generalization ability, and achieved better recognition effect than the existing model. In addition, this paper also compares the results of behavior recognition on subsets of different joint points, and finds that spatial structure division have better effects.

scholarly journals The perception of the elderly about suffering related to frailty

2018 ◽  
Vol 21 (2) ◽  
pp. 215-222
Author(s):  
Daniel Rocha Silveira ◽  
Karla Cristina Giacomin ◽  
Rosângela Correa Dias ◽  
Josélia Oliveira Araújo Firmo
Keyword(s):  
Life Experiences ◽  
The Elderly ◽  
Elderly Persons ◽  
Human Beings ◽  
Analysis Model ◽  
Frailty Phenotype ◽  
Network Database ◽  
Data Collection And Analysis ◽  
Urban Security ◽  
Belo Horizonte

Abstract Objective: To understand how elderly persons perceive subjective aspects linked to current and other life experiences related to the process of becoming frail. Method: A qualitative study, anchored in interpretative anthropology, was performed. The elderly were selected from the FIBRA Network database from those classified as robust or pre-frail, according to the frailty phenotype of Fried et al., in Belo Horizonte, Minas Gerais, Brazil in 2009. We interviewed 15 elderly people of different genders, ages, income, religion and functional status, in 2016. In data collection and analysis, the "signs, meanings and actions" analysis model was used, which allows the understanding of the elements that are significant for a population to read a given situation and to position themselves in relation to it. Results: From the analysis the following categories emerged: a) suffering throughout life and b) suffering and the resources to deal with them. Conclusion: The interviewees described sufferings of different aspects that constitute their life, from birth to aging, according to experiences related to pain, loss and learning. The perception of current frailty refers to their life history, marked by physical or mental suffering, whether insidious or temporary - as well as illnesses, how they manifest themselves today, and a lack of financial resources and urban security. The narratives bring us closer to the perception of frailty as being constitutive of human beings, who can easily break.

scholarly journals Physical activity and stress coping in the elderly

2010 ◽  
Vol 8 (4) ◽  
pp. 419-422 ◽  
Author(s):  
Fernando de Andréa ◽  
Fernanda Varkala Lanuez ◽  
Adriana Nunes Machado ◽  
Wilson Jacob Filho
Keyword(s):  
Physical Activity ◽  
Exercise Program ◽  
The Elderly ◽  
Physical Activity Program ◽  
Daily Activities ◽  
Stress Coping ◽  
Coping Capacity ◽  
Positive Effects ◽  
Supervised Exercise ◽  
Activity Program

ABSTRACT Objective: To analyze the value of a physical activity program on stress coping of the elderly. Methods: Intervention study with a group of 18 elderly people referred by the Geriatric Service of the Hospital das Clinicas of the Universidade de Sao Paulo, who attended a supervised exercise program, evaluated by the human activity profile and the coping questionnaire. Results: In the coping and functional performance scales, increased stress coping capacity and improvement of daily activities were found after exposure to a physical activity program. Conclusions: The practice of supervised and regular physical activity, combining aerobic, resistance, stretching, and respiratory exercises, yields positive effects in the coping capacity and in the accomplishment of the daily activities.

scholarly journals Preimpact Fall Detection for Elderly Based on Fractional Domain

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Ning Liu ◽  
Dedi Zhang ◽  
Zhong Su ◽  
Tianrun Wang
Keyword(s):  
Social Cost ◽  
Detection System ◽  
Fall Detection ◽  
The Elderly ◽  
Selection Method ◽  
Excellent Performance ◽  
Motion Data ◽  
Algorithm Framework ◽  
Warning Effect ◽  
Mean Filtering

The aging population has become a growing worldwide problem. Every year, deaths and injuries caused by elderly people's falls bring huge social costs. To reduce the rate of injury and death caused by falls among the elderly and the following social cost, the elderly must be monitored. In this context, falls detecting has become a hotspot for many research institutions and enterprises at home and abroad. This paper proposes an algorithm framework to prealarm the fall based on fractional domain, using inertial data sensor as motion data collection devices, preprocessing the data by axis synthesis and mean filtering, and using fractional-order Fourier transform to convert the collected data from time domain to fractional domain. Based on the above, a multilayer dichotomy classifier is designed, and each node parameter selection method is given, which constructed a preimpact fall detection system with excellent performance. The experiment result demonstrates that the algorithm proposed in this paper can guarantee better warning effect and classification accuracy with fewer features.

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