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ExerSeat - Sensor-Supported Exercise System for Ergonomic Microbreaks

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Ambient Intelligence (AmI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9425))

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Abstract

The percentage of older adult workers in Europe has been increasing in the last decades. They are an important part of the work force, highly experienced and often hard to replace. However, their productivity can be affected by health problems, such as lower back pain. This increases the cost for employers and reduces the quality of life of the office workers. Knowledge workers that spend a large part of their day in front of a screen are particularly affected by pack pain. Regular exercise can help to mitigate some of these issues. This training can be performed in microbreaks that are taken at regular intervals during the work day. In this work we present ExerSeat, a combination of a smart sensing chair that uses eight capacitive proximity sensors to precisely track the posture of persons on or near an office chair. It is augmented by a desktop training software that is able to track exercises and training units during microbreaks, by analyzing frequency and form. We have performed a pilot over eight weeks with ten office workers. They performed training units at regular intervals during their work day. We report on the findings.

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Acknowledgments

We would like to extend our gratitude to the Operations Support Services Unit volunteers at VTT Espoo for participating in our pilot, providing detailed feedback and to their management for allowing our minor intervention to their daily office routine. This work was supported by EIT Digital under the project number SSP14267.

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Correspondence to Andreas Braun .

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Braun, A., Schembri, I., Frank, S. (2015). ExerSeat - Sensor-Supported Exercise System for Ergonomic Microbreaks. In: De Ruyter, B., Kameas, A., Chatzimisios, P., Mavrommati, I. (eds) Ambient Intelligence. AmI 2015. Lecture Notes in Computer Science(), vol 9425. Springer, Cham. https://doi.org/10.1007/978-3-319-26005-1_16

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  • DOI: https://doi.org/10.1007/978-3-319-26005-1_16

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