Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Özlem Durmaz İncel"'
Autor:
Begüm Özkaynak, Necati Aras, İrem Daloğlu Çetinkaya, Cem Ersoy, Özlem Durmaz İncel, Mutlu Koca, İrem Nalça, Turgut Tüzün Onay, Sinan Öncü, Berivan Ülger Vatansever, Eda Yücesoy, Can A. Yücesoy
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
Smart city development is a complex, transdisciplinary challenge that requires adaptive resource use and context-aware decision-making practices to enhance human functionality and capabilities while respecting societal and environmental rights, and e
Externí odkaz:
https://doaj.org/article/efb893910d8840cf9221d19d5dc4ca33
Autor:
Berrenur Saylam, Özlem Durmaz İncel
Publikováno v:
Diagnostics, Vol 14, Iss 5, p 501 (2024)
This study investigates the prediction of mental well-being factors—depression, stress, and anxiety—using the NetHealth dataset from college students. The research addresses four key questions, exploring the impact of digital biomarkers on these
Externí odkaz:
https://doaj.org/article/bf7800559fdf481e87b58877533e39e3
Autor:
Berrenur Saylam, Özlem Durmaz İncel
Publikováno v:
Sensors, Vol 23, Iss 21, p 8987 (2023)
Wearable devices have become ubiquitous, collecting rich temporal data that offers valuable insights into human activities, health monitoring, and behavior analysis. Leveraging these data, researchers have developed innovative approaches to classify
Externí odkaz:
https://doaj.org/article/bc98555aaf5244fbaa6abd0bbd4752cf
Autor:
Berrenur Saylam, Özlem Durmaz İncel
Publikováno v:
Berrenur Saylam
With the development of wearable technologies, a new kind of healthcare data has become valuable as medical information. These data provide meaningful information regarding an individual's physiological and psychological states, such as activity leve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee74a2b4c581f0eb92bb45ee5d1a5da5
Autor:
Sumeyye Agac, Ozlem Durmaz Incel
Publikováno v:
Diagnostics, Vol 13, Iss 11, p 1861 (2023)
Sensor-based human activity recognition with wearable devices has captured the attention of researchers in the last decade. The possibility of collecting large sets of data from various sensors in different body parts, automatic feature extraction, a
Externí odkaz:
https://doaj.org/article/cb49c3c2a2d44f42bbcfa1045f5b1c67
Autor:
Ozlem Durmaz Incel, Secil Gunay, Yasemin Akan, Yunus Barlas, Okan Engin Basar, Gulfem Isiklar Alptekin, Mustafa Isbilen
Publikováno v:
IEEE Access, Vol 9, Pp 38943-38960 (2021)
Authenticating a user in the right way is essential to IT systems, where the risks are becoming more and more complex. Especially in the mobile world, banking applications are among the most delicate systems requiring strict rules and regulations. Ex
Externí odkaz:
https://doaj.org/article/fb1d3ee8737e46ddb3a43a6069b9d895
Autor:
Ozlem Durmaz Incel
Publikováno v:
Sensors, Vol 15, Iss 10, Pp 25474-25506 (2015)
Phone placement, i.e., where the phone is carried/stored, is an important source of information for context-aware applications. Extracting information from the integrated smart phone sensors, such as motion, light and proximity, is a common technique
Externí odkaz:
https://doaj.org/article/0ae9d875198c42e9a86b0dd754f7baba
Publikováno v:
Sensors, Vol 15, Iss 1, Pp 2059-2085 (2015)
Physical activity recognition using embedded sensors has enabled many context-aware applications in different areas, such as healthcare. Initially, one or more dedicated wearable sensors were used for such applications. However, recently, many resear
Externí odkaz:
https://doaj.org/article/cde5d9d2231d4822806243a4564def01
Publikováno v:
Sensors, Vol 14, Iss 6, Pp 10146-10176 (2014)
For physical activity recognition, smartphone sensors, such as an accelerometer and a gyroscope, are being utilized in many research studies. So far, particularly, the accelerometer has been extensively studied. In a few recent studies, a combination
Externí odkaz:
https://doaj.org/article/cb823c7be57943e28a91757c638f2994
Publikováno v:
Sensors, Vol 14, Iss 6, Pp 9692-9719 (2014)
Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs) provide a great potential for ambient assisted living (AAL) applications, ranging from health and wellbeing monitoring to resource consumption
Externí odkaz:
https://doaj.org/article/b00e0ec6a9b748e3858e7c2dcba69c7a