Human Activity Recognition in Daily Life and Sports Using Inertial Sensors
Human Activity Recognition (HAR) deals with the automatic recognition of physical activities and plays a major role in the health and sports sector. Knowledge about the performed activities can be used to monitor compliance regarding physical activity recommendations, investigate the causes of physi...
Đã lưu trong:
| Tác giả chính: | |
|---|---|
| Định dạng: | Online |
| Ngôn ngữ: | Tiếng Anh |
| Được phát hành: |
FAU University Press
2025
|
| Những chủ đề: | |
| Truy cập trực tuyến: | ONIX_20251215T160010_9783961472260_45 |
| Các nhãn: |
Không có thẻ, Là người đầu tiên thẻ bản ghi này!
|
| _version_ | 1869520249110396928 |
|---|---|
| author | Schuldhaus, Dominik |
| author_browse | Schuldhaus, Dominik |
| author_facet | Schuldhaus, Dominik |
| author_sort | Schuldhaus, Dominik |
| collection | Directory of Open Access Books |
| description | Human Activity Recognition (HAR) deals with the automatic recognition of physical activities and plays a major role in the health and sports sector. Knowledge about the performed activities can be used to monitor compliance regarding physical activity recommendations, investigate the causes of physical activity behavior, implement sport-specific training programs, and replicate the physical demands during sport competition. Currently available tools for HAR often rely on questionnaires which involve problems in the reliability when recalling activities. In this thesis, algorithms for HAR are introduced and evaluated which apply machine learning techniques to inertial sensor data. Daily as well as sport-specific activities are considered including sitting, washing dishes, climbing stairs, and kicking in soccer. Besides the development and implementation of algorithms, mandatory extensions regarding the design of HAR systems are further identified and future research directions are provided. |
| format | Online |
| id | doab-20.500.12854ir-170197 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | FAU University Press |
| publisherStr | FAU University Press |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1701972025-12-16T05:17:58Z Human Activity Recognition in Daily Life and Sports Using Inertial Sensors Schuldhaus, Dominik Gyroskop Beschleunigungssensor Maschinelles Lernen Monitoring Data Mining Fußball thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UN Databases::UNC Data capture and analysis thema EDItEUR::U Computing and Information Technology::UX Applied computing Human Activity Recognition (HAR) deals with the automatic recognition of physical activities and plays a major role in the health and sports sector. Knowledge about the performed activities can be used to monitor compliance regarding physical activity recommendations, investigate the causes of physical activity behavior, implement sport-specific training programs, and replicate the physical demands during sport competition. Currently available tools for HAR often rely on questionnaires which involve problems in the reliability when recalling activities. In this thesis, algorithms for HAR are introduced and evaluated which apply machine learning techniques to inertial sensor data. Daily as well as sport-specific activities are considered including sitting, washing dishes, climbing stairs, and kicking in soccer. Besides the development and implementation of algorithms, mandatory extensions regarding the design of HAR systems are further identified and future research directions are provided. 2025-12-16T05:17:57Z 2025-12-16T05:17:57Z 2025-12-15T15:04:30Z 2019 book ONIX_20251215T160010_9783961472260_45 https://library.oapen.org/handle/20.500.12657/109165 9783961472260 9783961472253 https://directory.doabooks.org/handle/20.500.12854/170197 eng FAU Studien aus der Informatik open access image/jpeg Attribution 4.0 International https://library.oapen.org/bitstream/20.500.12657/109165/1/9783961472260.pdf FAU University Press 10.25593/978-3-96147-226-0 10.25593/978-3-96147-226-0 2c600dea-eece-4066-87be-da335e323fdb 9783961472260 9783961472253 266 Erlangen open access |
| spellingShingle | Gyroskop Beschleunigungssensor Maschinelles Lernen Monitoring Data Mining Fußball thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UN Databases::UNC Data capture and analysis thema EDItEUR::U Computing and Information Technology::UX Applied computing Schuldhaus, Dominik Human Activity Recognition in Daily Life and Sports Using Inertial Sensors |
| title | Human Activity Recognition in Daily Life and Sports Using Inertial Sensors |
| title_full | Human Activity Recognition in Daily Life and Sports Using Inertial Sensors |
| title_fullStr | Human Activity Recognition in Daily Life and Sports Using Inertial Sensors |
| title_full_unstemmed | Human Activity Recognition in Daily Life and Sports Using Inertial Sensors |
| title_short | Human Activity Recognition in Daily Life and Sports Using Inertial Sensors |
| title_sort | human activity recognition in daily life and sports using inertial sensors |
| topic | Gyroskop Beschleunigungssensor Maschinelles Lernen Monitoring Data Mining Fußball thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UN Databases::UNC Data capture and analysis thema EDItEUR::U Computing and Information Technology::UX Applied computing |
| topic_facet | Gyroskop Beschleunigungssensor Maschinelles Lernen Monitoring Data Mining Fußball thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UN Databases::UNC Data capture and analysis thema EDItEUR::U Computing and Information Technology::UX Applied computing |
| url | ONIX_20251215T160010_9783961472260_45 |
| work_keys_str_mv | AT schuldhausdominik humanactivityrecognitionindailylifeandsportsusinginertialsensors |