Image processing-aided working posture analysis: I-OWAS. (July 2015)
- Record Type:
- Journal Article
- Title:
- Image processing-aided working posture analysis: I-OWAS. (July 2015)
- Main Title:
- Image processing-aided working posture analysis: I-OWAS
- Authors:
- Fığlalı, Nilgün
Cihan, Ahmet
Esen, Hatice
Fığlalı, Alpaslan
Çeşmeci, Davut
Güllü, Mehmet Kemal
Yılmaz, Mustafa Kerim - Abstract:
- Highlights: OWAS method is adapted to an integrated software as a prototype. It operates completely computer-aided with the help of image processing techniques. That model's performance is high while robust recording conditions can be settled. Necessity of expert analyst is eliminated. The model will support the common use of OWAS in industry. Abstract: Musculoskeletal Disorders (MSDs) rank among the commonest health problems both in the frequency of concurrency and in the money spent on these disorders, which mainly stem from poor working posture it also negatively affects employees in terms of job productivity, life quality, and both physical and social activities. Analyzing and improving working postures with scientific methods provides significant contributions in the field of controlling job performance and decreasing MSDs. OWAS (Ovako Working Posture Analyzing System) is one of the methods for analyzing working postures and can be applied to very diverse areas successfully. In this study, a prototype of integrated software, which is based on image processing techniques, was developed (I-OWAS), and the performance of the model was presented. I-OWAS begins with separating the video film into frames, producing OWAS codes belonging to working posture in each frame, and then classifying the images according to risk categories. Despite OWAS being a successful method for analyzing working postures, it requires an expert analysis. Also the manual analyzing process is soHighlights: OWAS method is adapted to an integrated software as a prototype. It operates completely computer-aided with the help of image processing techniques. That model's performance is high while robust recording conditions can be settled. Necessity of expert analyst is eliminated. The model will support the common use of OWAS in industry. Abstract: Musculoskeletal Disorders (MSDs) rank among the commonest health problems both in the frequency of concurrency and in the money spent on these disorders, which mainly stem from poor working posture it also negatively affects employees in terms of job productivity, life quality, and both physical and social activities. Analyzing and improving working postures with scientific methods provides significant contributions in the field of controlling job performance and decreasing MSDs. OWAS (Ovako Working Posture Analyzing System) is one of the methods for analyzing working postures and can be applied to very diverse areas successfully. In this study, a prototype of integrated software, which is based on image processing techniques, was developed (I-OWAS), and the performance of the model was presented. I-OWAS begins with separating the video film into frames, producing OWAS codes belonging to working posture in each frame, and then classifying the images according to risk categories. Despite OWAS being a successful method for analyzing working postures, it requires an expert analysis. Also the manual analyzing process is so laborious and time consuming. I-OWAS provide the computer support for the manual coding stage and eliminates the need for an expert analyst; hence, the method can be widely used in industry. … (more)
- Is Part Of:
- Computers & industrial engineering. Volume 85(2015)
- Journal:
- Computers & industrial engineering
- Issue:
- Volume 85(2015)
- Issue Display:
- Volume 85, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 85
- Issue:
- 2015
- Issue Sort Value:
- 2015-0085-2015-0000
- Page Start:
- 384
- Page End:
- 394
- Publication Date:
- 2015-07
- Subjects:
- Musculoskeletal disorders -- Working posture analysis -- OWAS -- Image processing
Engineering -- Data processing -- Periodicals
Industrial engineering -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03608352 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cie.2015.03.011 ↗
- Languages:
- English
- ISSNs:
- 0360-8352
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.713000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7013.xml