Object Detection Human Activity Recognition for Improved Patient Mobility and Caregiver Ergonomics

dc.contributor.authorMadhavan, Mahesh
dc.contributor.authorNkhoma, Patford
dc.contributor.authorKhoshkangini, Reza
dc.contributor.authorJamali, Mahtab
dc.contributor.authorDavidsson, Paul
dc.contributor.authorÅberg, Jan
dc.contributor.authorLjungqvist, Martin
dc.date.accessioned2025-07-30T07:05:29Z
dc.date.available2025-07-30T07:05:29Z
dc.date.issued2025
dc.description.abstract-translatedThis study explores the use of machine learning to enhance patient mobility and caregiver ergonomics by optimizing the use of mobility aids. Traditional manual assessments can be subjective and inaccurate, so this research develops a data-driven model for object detection and human activity recognition. A computer vision dataset was created using video recordings of controlled caregiving scenarios. The study leverages advanced machine learning models, including YOLO for object detection, pose estimation, ResNet-18 for frame classification, Inception-v4 for feature extraction, and LSTM for sequence modeling. The findings provide valuable insights into integrating machine learning into mobility aids, improving both patient outcomes and caregiver well-being.en
dc.description.sponsorshipThis study is supported by the ’Synergy’ project at Malmo University which was funded by the Knowledge Foundation in Sweden.
dc.description.sponsorshipThis study is supported by the ’Synergy’ project at Malmo University which was funded by the Knowledge Foundation in Sweden.en
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.doihttp://www.doi.org/10.24132/JWSCG.2025-2
dc.identifier.issn1213-6972 (print)
dc.identifier.issn1213-6964 (online)
dc.identifier.urihttp://hdl.handle.net/11025/62196
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.rights© Václav Skala - UNION Agencyen
dc.rights.accessopenAccessen
dc.subjectpomůcka pro mobilitucs
dc.subjectergonomiecs
dc.subjectpečovatelcs
dc.subjectstrojové učenícs
dc.subjectmuskuloskeletální poruchycs
dc.subject.translatedmobility aiden
dc.subject.translatedergonomicsen
dc.subject.translatedcaregiveren
dc.subject.translatedmachine learningen
dc.subject.translatedmusculoskeletal disordersen
dc.titleObject Detection Human Activity Recognition for Improved Patient Mobility and Caregiver Ergonomicsen
dc.typečlánekcs
dc.typearticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
local.files.count1*
local.files.size1490544*
local.has.filesyes*

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