Zobrazeno 1 - 10
of 1 040
pro vyhledávání: '"Human activity recognition (HAR)"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Hand gesture recognition based on sparse multichannel surface electromyography (sEMG) still poses a significant challenge to deployment as a muscle–computer interface. Many researchers have been working to develop an sEMG-based hand gestur
Externí odkaz:
https://doaj.org/article/23d8bd29525e459083470afd4af61e1a
Publikováno v:
Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, Vol 12, Iss 1 (2024)
This work presents an on-device machine learning model with the ability to identify different mobility gestures called human activity recognition (HAR), which includes running, walking, squatting, jumping, and others. The data is collected through an
Externí odkaz:
https://doaj.org/article/0637afd14c844cd2a0ff10abfbe0986c
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 2, Pp 842-876 (2024)
Human activity recognition (HAR) remains an essential field of research with increasing real-world applications ranging from healthcare to industrial environments. As the volume of publications in this domain continues to grow, staying abreast of the
Externí odkaz:
https://doaj.org/article/8393236a93254975ae39fa93d0d1528f
Publikováno v:
International Journal of Intelligent Computing and Cybernetics, 2023, Vol. 17, Issue 1, pp. 126-142.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJICC-06-2023-0147
Autor:
Marija Stojchevska, Mathias De Brouwer, Martijn Courteaux, Bram Steenwinckel, Sofie Van Hoecke, Femke Ongenae
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-21 (2024)
Abstract The detection of Activities of Daily Living (ADL) holds significant importance in a range of applications, including elderly care and health monitoring. Our research focuses on the relevance of ADL detection in elderly care, highlighting the
Externí odkaz:
https://doaj.org/article/0309b537b5bf4c5c8d81b2659c1a0e1c
Publikováno v:
IEEE Access, Vol 12, Pp 153188-153202 (2024)
Innovative monitoring solutions utilizing radar have been developed to meet various safety needs. Radar technologies, equipped with unique features, have proven to be effective tools for human activity recognition in diverse environments. Radar compl
Externí odkaz:
https://doaj.org/article/9f8c06e2b6da4752aed7e041e381441b
Publikováno v:
IEEE Access, Vol 12, Pp 151649-151668 (2024)
Sensor-based datasets are extensively utilized in human-computer interaction (HCI) and medical applications due to their portability and strong privacy features. Many researchers have developed sensor-based human activity recognition (HAR) systems to
Externí odkaz:
https://doaj.org/article/b4954e70f0b940c49a9e98c576269f1e
Autor:
Furqan Alam, Pawel Plawiak, Ahmed Almaghthawi, Mohammad Reza Chalak Qazani, Sanat Mohanty, and Roohallah Alizadehsani
Publikováno v:
IEEE Access, Vol 12, Pp 112232-112248 (2024)
Human Activity Recognition (HAR) is becoming increasingly important in the fast-evolving landscapes of wearable sensors, smart applications, and the Internet of Things (IoT) paradigms. HAR is rapidly gaining importance, especially in health monitorin
Externí odkaz:
https://doaj.org/article/8b2a53402aa643ab96491d6fe7b72863
Publikováno v:
IEEE Access, Vol 12, Pp 88841-88861 (2024)
Automated Human Activity Recognition (HAR) stems from the requirement to seamlessly integrate technology into daily life, to enhance user experience, improve healthcare, provide improved operations, ensure safety, deliver data-driven insights, and ad
Externí odkaz:
https://doaj.org/article/249f188a4c544fcd938c9dbf4143236f
Autor:
Heba Nematallah, Sreeraman Rajan
Publikováno v:
IEEE Access, Vol 12, Pp 52127-52149 (2024)
Human Activity Recognition (HAR) based on Inertial Measurement Unit (IMU) has become increasingly important in health and fitness applications. These systems can continuously and cost-effectively monitor human activity, regardless of the surrounding
Externí odkaz:
https://doaj.org/article/3a4145820e3e44ac8127d6d737cd2a47