| Publisher DOI: | 10.1145/3594806.3596529 | Title: | NeckWatcher : a real-time monitoring tool for the assessment of the neck posture | Language: | English | Authors: | Trygub, Iryna Ahlf, Johanna Campanale, Martina Jeworutzki, André  Schwarzer, Jan |
Keywords: | pose estimation; machine learning; posture detection; neck pain | Issue Date: | 10-Aug-2023 | Publisher: | Association for Computing Machinery | Part of Series: | Proceedings of the 16th ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA 2023) | Startpage: | 241 | Endpage: | 242 | Conference: | International Conference on PErvasive Technologies Related to Assistive Environments 2023 | Abstract: | Persistant poor posture can lead to the development of neck pain. Many different solutions have been proposed to aid in neck posture control, but most of them require additional devices. In this study, we present NeckWatcher, a tool that builds on MediaPipe Pose and utilizes an integrated webcam to monitor a person’s neck posture in real-time. It is designed to be user-friendly and realized as a stand-alone solution. Our first results suggest that NeckWatcher can be a useful tool for improving the sitting posture and, by that, reducing the risk of developing neck pain. |
URI: | https://hdl.handle.net/20.500.12738/20165 | ISBN: | 979-8-4007-0069-9 | Review status: | This version was peer reviewed (peer review) | Institute: | Department Informatik (ehemalig, aufgelöst 10.2025) Fakultät Technik und Informatik (ehemalig, aufgelöst 10.2025) Forschungs- und Transferzentrum Smart Systems |
Type: | Chapter/Article (Proceedings) |
| Appears in Collections: | Publications without full text |
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