NeckWatcher : a real-time monitoring tool for the assessment of the neck posture

Trygub, Iryna; Ahlf, Johanna; Campanale, Martina; Jeworutzki, André; Schwarzer, Jan

doi:10.1145/3594806.3596529

Verlagslink DOI:	10.1145/3594806.3596529
Titel:	NeckWatcher : a real-time monitoring tool for the assessment of the neck posture
Sprache:	Englisch
Autorenschaft:	Trygub, Iryna Ahlf, Johanna Campanale, Martina Jeworutzki, André Schwarzer, Jan
Schlagwörter:	pose estimation; machine learning; posture detection; neck pain
Erscheinungsdatum:	10-Aug-2023
Verlag:	Association for Computing Machinery
Teil der Schriftenreihe:	Proceedings of the 16th ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA 2023)
Anfangsseite:	241
Endseite:	242
Konferenz:	International Conference on PErvasive Technologies Related to Assistive Environments 2023
Zusammenfassung:	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
Begutachtungsstatus:	Diese Version hat ein Peer-Review-Verfahren durchlaufen (Peer Review)
Einrichtung:	Department Informatik (ehemalig, aufgelöst 10.2025) Fakultät Technik und Informatik (ehemalig, aufgelöst 10.2025) Forschungs- und Transferzentrum Smart Systems
Dokumenttyp:	Konferenzveröffentlichung
Enthalten in den Sammlungen:	Publications without full text