Relationship analysis between body flexion angles and smartphone tilt during smartphone use |
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Affiliation: | 1. School of Information Convergence, Kwangwoon University, Republic of Korea;2. Department of Industrial and Management Engineering, Incheon National University (INU), Republic of Korea;1. Department of Kinesiology and Physical Education, McGill University, 475 Pine Avenue West, Montreal, Quebec, H2W 1S4, Canada?;2. Feil & Oberfeld/CRIR Research Center, Jewish Rehabilitation Hospital, 3205 Alton, Goldbloom Place, Laval, Quebec, H7V 1R2, Canada;1. Ergonomics Department, Instituto Nacional de Seguridad, Salud y Bienestar en el Trabajo (INSSBT), Dulcet 2-10, 08034, Barcelona, Spain;2. GTM - Grup de Tecnologies Mèdia, La Salle, Universitat Ramon Llull, Enginyeria La Salle, Edifici Jaume Hilari, Quatre Camins 2, 08022, Barcelona, Spain;1. Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA 16802, USA;2. Department of Medicine, The Pennsylvania State University College of Medicine, Hershey, PA 17033, USA;3. Department of Public Health Sciences, The Pennsylvania State University College of Medicine, Hershey, PA 17033, USA |
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Abstract: | Although smartphones are used as essential devices in everyday life, many users are exposed to joint diseases owing to prolonged use. The objectives of this study were to analyze how posture and smartphone tasks affect various body flexion angles and develop an algorithm to classify posture/task and estimate body flexion angles using smartphone tilt data. Eighteen participants performed two tasks (playing a game and reading news) in two postures (sitting and standing) in a laboratory environment. The three-axis orientation data (azimuth, pitch, and roll) of the smartphone and the participants’ body flexion angles were measured simultaneously. This study found that the cervical, thoracic, lumbar, and overall flexion angles were all statistically significantly different depending on the posture of the smartphone user, and the cervical flexion angle was significantly different depending on the task. Furthermore, task and task × posture can be classified with high accuracy based on smartphone tilt data, and tilt data had a high correlation with body flexion angles. Relevance to industry: The results of this study can be used as a reference for designing various products and interfaces for neck health. The results can be applied as a smartphone alarm or a built-in application, which can inform the user of the need to stretch his or her neck. |
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Keywords: | Smartphone Inertial measurement unit (IMU) Sensor Cervical flexion Thoracic flexion Lumbar flexion |
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