Even if posture detection is extremely useful in health monitoring and rehabilitation, as well as human movement dynamic analysis, other applications can benefit from this technique-design of ergonomic chairs, virtual reality applications, or teaching and learning environments. Among other negative consequences, a wrong posture may lead to acute or chronic problems, such as back pain, headaches, or digestive problems. In fact, it is common to adopt, during everyday activities, a wrong posture even if a correct ergonomic seat is provided for example, sitting slumped apparently is a more comfortable position than sitting with the back straight, but over time, it may cause tension, with muscle or joint pain. It is useful to underline that adopting a correct sitting posture is not easy for all people. One of the main applications of the detection and classification of posture is in the medical field-by being able to detect that a person is sitting in a wrong position, it is possible to correct it and reduce its negative consequences on health. Knowledge of the posture of a seated person turns out to be useful in many ways. Among them, the use of traditional alarms, computer prompts (e.g., Stretchly, Big Stretch Reminder, Awareness ), smart watches (e.g., Apple Watch, Fitbit trackers) and mobile applications (e.g., Break Timer, Eye Care 20 20 20 ) are a few examples.ĭespite these options, the time spent sitting is increasing, as analyzed in. Nowadays, there are several options to support the implementation of these breaks. Another option for avoiding prolonged static postures is to perform micro-breaks every 20–30 min of continuous sitting. As shown in, their use not only decreases sitting time but also reduces the cardio-metabolic risk. Among these, it is worth mentioning the use of height-adjustable sit–stand workstations. To mitigate these effects, in recent years many solutions have been proposed for reducing sitting time. Recent studies have shown that an increased sitting time may induce chronic diseases (eventually leading to death) and may also have a severe impact on psychological health (leading to anxiety and depression). Nowadays, a large percentage of the active population is spending many hours sitting either for work or leisure (office workers, watching TV, etc.). Overall, the performed analysis showed the proposed monitoring system could be used to identify body posture variations related to different levels of engagement of a seated user while performing cognitive tasks. This evidence highlighted the presence of movement presumably due to the increased cognitive engagement. A transition analysis conducted on postures assumed during the test showed that participants reached a different posture at the end of the test, when the cognitive engagement increased, with respect to the beginning. The collected results had been analyzed by considering three different time intervals based on the difficulty level of the test (low, medium, and high).
The effectiveness of the designed system was evaluated through an experiment where increasing stress levels were obtained by administering a Stroop test. The position of the sensors was selected for maximizing the detection of variations of user’s posture. To meet this aim, we placed a set of textile pressure sensors both on the backrest and on the seat of the chair. An office chair for analyzing the seated posture variation during the performance of a stress-level test is presented in this work.
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