2014
DOI: 10.1007/978-3-319-00846-2_368
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Intelligent Chair Sensor – Classification and Correction of Sitting Posture

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Cited by 16 publications
(38 citation statements)
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“…Active measurement is the recognition of posture and anthropometrics while the user is at the workstation. Automatic active recognition systems have been studied (Martins et al, 2014;Wongpatikaseree et al, 2014;Haveman and Kant, 2008), which allow some of the potential MSD (muskuloesqueletal) risks to be detected. One system uses two matrices of sensors arranged in cushions (Mota and Picard, 2003), and the CAPRIO system is a compromise between the other most used systems (Haveman and Kant, 2008).…”
Section: State Of the Artmentioning
confidence: 99%
See 1 more Smart Citation
“…Active measurement is the recognition of posture and anthropometrics while the user is at the workstation. Automatic active recognition systems have been studied (Martins et al, 2014;Wongpatikaseree et al, 2014;Haveman and Kant, 2008), which allow some of the potential MSD (muskuloesqueletal) risks to be detected. One system uses two matrices of sensors arranged in cushions (Mota and Picard, 2003), and the CAPRIO system is a compromise between the other most used systems (Haveman and Kant, 2008).…”
Section: State Of the Artmentioning
confidence: 99%
“…Usually, this information is a product of the user's impression and how well this is interpreted and executed in the system's adjustment. For the physical parameters, active information reading (Martins et al, 2014;Wongpatikaseree et al, 2014;Haveman and Kant, 2008) is also possible. Fig.…”
Section: Information Flowmentioning
confidence: 99%
“…In addition to cardiorespiratory monitoring, often the user's behavior and movements are tracked, which can be done by integrating pressure or force sensors. Martins et al [11] integrated matrices of 2-by-2 pressure cells into the seating and the backrest of an office chair to classify the user's sitting posture. Eight FSRs were integrated into a lay-on for office chairs by Hermann and Kõiva [12] and used to detect and sonificate the user's posture.…”
Section: Related Workmentioning
confidence: 99%
“…These pressures maps were used as input for an Artificial Neural Network (ANN) and postural classification in real-time were made. Results show that, for 11 postures, the overall score was 70%, but when the number of positions decreases to 8, the overall classification score was 93% [27]. After the development of the first prototype, a second one was built in order to solve the limitations of the first prototype [28].…”
Section: Introductionmentioning
confidence: 97%
“…In a previous work, our group developed chair prototype that was able to classify 11 different standard sitting postures [27]. Four air bladders were placed inside the chair seat pad and four were placed inside the backrest.…”
Section: Introductionmentioning
confidence: 99%