Human activity recognition by smartphones regardless of device orientation

Multi-Label Human Activity Recognition on Image Using Deep Learning

“…There are several methods for recognizing human activity. Some works consider using data from sensors of smartphones and other devices [2,3], as well as from wearable sensors [4,5,6]. There are also methods for human activity recognition by image or video [7,8].…”

Human Activity Tracking by Mobile Phones Through Hebbian Learning

“…The feature set used by the system was created by selecting from a pool of features from [5][10] and [16]. In order to improve accuracy and reduce computational expenses, a feature selection was performed.…”

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“…A separate coordinate system can be used for each activity, as long as the resulting acceleration signatures are not the same. Principal component analysis (PCA) was used for preprocessing the motion signals in [11], [14], [15], [16]. Performance is to be evaluated differently from smartphone based methods to attachable accelerometer based methods.…”

“…One method that is good for detecting one set of activites (i.e., using kNN to classify walking, running, and other exercise activities) may not necessarily be the best choice for detecting another activity set (i.e., fall detection).Another issue with some studies is that outside of a lab setting, users position the smartphone with different orientations and on different on-body locations. Studies that have addressed this problem include [11] [14] [15] [16].…”