Results 41 to 50 of about 980,735 (314)

A Comprehensive Study of Activity Recognition Using Accelerometers

Informatics, 2018
This paper serves as a survey and empirical evaluation of the state-of-the-art in activity recognition methods using accelerometers. The paper is particularly focused on long-term activity recognition in real-world settings.
Niall Twomey, Tom Diethe, Xenofon Fafoutis, Atis Elsts, Ryan McConville, Peter Flach, Ian Craddock   +6 more
doaj   +1 more source

Predicting Activity Duration in Smart Sensing Environments Using Synthetic Data and Partial Least Squares Regression: The Case of Dementia Patients

Sensors, 2022
The accurate recognition of activities is fundamental for following up on the health progress of people with dementia (PwD), thereby supporting subsequent diagnosis and treatments.
Miguel Ortiz-Barrios, Eric Järpe, Matías García-Constantino, Ian Cleland, Chris Nugent, Sebastián Arias-Fonseca, Natalia Jaramillo-Rueda   +6 more
doaj   +1 more source

Recognition of Daily and Sports Activities

2018 IEEE International Conference on Big Data (Big Data), 2018
Since being physically inactive was reported as one of the major risk factor of mortality, classifying daily and sports activities becomes a critical task that may improve human life quality. In this paper, the daily and sports activities dataset was used in order to evaluate and validate the employed approach.
Inanç N., Kayri M., Ertu?rul O.F.
openaire   +4 more sources

Activity Discovery and Activity Recognition: A New Partnership [PDF]

IEEE Transactions on Cybernetics, 2013
Activity recognition has received increasing attention from the machine learning community. Of particular interest is the ability to recognize activities in real time from streaming data, but this presents a number of challenges not faced by traditional offline approaches. Among these challenges is handling the large amount of data that does not belong
Diane J. Cook, Narayanan Chatapuram Krishnan, Parisa Rashidi   +2 more
openaire   +3 more sources

Opportunities for activity recognition using ultrasound doppler sensing on unmodified mobile phones

, 2022
Art. 8, 10 S.Nowadays activity recognition on smartphones is ubiquitously applied, for example to monitor personal health. The smartphone's sensors act as a foundation to provide information on movements, the user's location or direction.
Karolus, Jakob, Fu, Biying, Große-Puppendahl, Tobias, Hermann, Jonathan, Kuijper, Arjan   +4 more
core   +1 more source

Through-wall Human Pose Reconstruction and Action Recognition Using Four-dimensional Imaging Radar

Leida xuebao
Through-wall human pose reconstruction and behavior recognition have enormous potential in fields like intelligent security and virtual reality. However, existing methods for through-wall human sensing often fail to adequately model four-Dimensional (4D)
Rui ZHANG, Hanqin GONG, Ruiyuan SONG, Yadong LI, Zhi LU, Dongheng ZHANG, Yang HU, Yan CHEN   +7 more
doaj   +1 more source

Tangible User Interface and Mu Rhythm Suppression: The Effect of User Interface on the Brain Activity in Its Operator and Observer

Applied Sciences, 2017
The intuitiveness of tangible user interface (TUI) is not only for its operator. It is quite possible that this type of user interface (UI) can also have an effect on the experience and learning of observers who are just watching the operator using it ...
Kazuo Isoda, Kana Sueyoshi, Ryo Miyamoto, Yuki Nishimura, Yuki Ikeda, Ichiro Hisanaga, Stéphanie Orlic, Yeon-kyu Kim, Shigekazu Higuchi   +8 more
doaj   +1 more source

A Multi-Agent and Attention-Aware Enhanced CNN-BiLSTM Model for Human Activity Recognition for Enhanced Disability Assistance

Diagnostics
Background: Artificial intelligence (AI)-based automated human activity recognition (HAR) is essential in enhancing assistive technologies for disabled individuals, focusing on fall detection, tracking rehabilitation progress, and analyzing personalized ...
Mst Alema Khatun, Mohammad Abu Yousuf, Taskin Noor Turna, AKM Azad, Salem A. Alyami, Mohammad Ali Moni   +5 more
doaj   +1 more source

On-Device Deep Personalization for Robust Activity Data Collection

Sensors, 2020
One of the biggest challenges of activity data collection is the need to rely on users and keep them engaged to continually provide labels. Recent breakthroughs in mobile platforms have proven effective in bringing deep neural networks powered ...
Nattaya Mairittha, Tittaya Mairittha, Sozo Inoue   +2 more
doaj   +1 more source

Human Activity Recognition [PDF]

, 2005
Motion is an important cue for the human visual system Mobiles have fascinated children, Zeno (circa 500 B.C.) studied moving arrows to pose a paradox and Zeke is investigating the human brain devoted to the understanding of motion. In computer vision research, motion has played an important role for the past thirty years.
openaire   +1 more source