Recognizing human motion with multiple acceleration sensors

Sensor Fusion for Semantic Place Labeling

“…Other studies on semantic place labeling so far [Reddy et al, 2010, Consolvo et al, 2008, Arase et al, 2010, Bouten et al, 1997, Perrin et al, 2000, Junker et al, 2004, Preece et al, 2009, Berchtold et al, 2010, Ravi et al, 2005, Bao and Intille, 2004, Chang et al, 2007, Farringdon et al, 1999, Kern et al, 2003, Mantyjarvi et al, 2001, Stikic et al, 2008, Zinnen et al, 2009, Lester et al, 2005, Siewiorek et al, 2003 are mostly based on unlabeled data or on a small number of sensor and state data. The field of physical activity recognition based on accelerometer sensor data is well researched [Consolvo et al, 2008, Arase et al, 2010, Berchtold et al, 2010, Bao and Intille, 2004, Farringdon et al, 1999, Kern et al, 2003].…”

“…The field of physical activity recognition based on accelerometer sensor data is well researched [Consolvo et al, 2008, Arase et al, 2010, Berchtold et al, 2010, Bao and Intille, 2004, Farringdon et al, 1999, Kern et al, 2003]. Accuracies of physical activity recognition could be achieved up to 90% [Reddy et al, 2010,Preece et al, 2009,Ravi et al, 2005, Bao and Intille, 2004, Chang et al, 2007, Mantyjarvi et al, 2001], but the current average smartphone has more sensors built in than only a accelorometer. Thus, our research focuses on exploiting as many sensor and state values our algorithms need to detect the semantic of a place for a user using sparse data to not unnecessary drown the battery.…”

Recognizing Workshop Activity Using Body Worn Microphones and Accelerometers

“…Activity recognition based on body worn sensors, in particular acceleration sensors, has been studied by different research groups [11,14,23]. However all of the above work focused on recognizing comparatively simple activities (walking, running, and sitting).…”

Discrimination between Upstairs and Downstairs Based on Accelerometer

“…The researchers usually collected data from a very small number of subjects, and each activity is often performed more than twice by the same subject [6], [9], [10], [20]. In this study, however, we use a more challenge dataset, SCUT-NAA [17], which contains 1278 samples of ten activities using only one tri-axial accelerometer in naturalistic settings.…”

“…Although the most prevalent everyday activities (sitting, walking, running, vacuuming) have been successfully recognized [2]- [7], climbing upstairs and downstairs are still hard to distinguish in a few studies [6], [9], [10], [18]- [20]. Some past works have demonstrated 24.07% to 84% recognition rates for upstairs and downstairs using acceleration data, which are summarized in Table 1.…”