Authors:
Hui Liu
and
Tanja Schultz
Affiliation:
Cognitive Systems Lab, University of Bremen, Bremen, Germany
Keyword(s):
Human Activity, Human Activity Recogntion, Activities of Daily Living, Wearable Sensing, Internal Sensing, Biosignals, CSL-SHARE, Statistical Analysis.
Abstract:
Human activity research in the field of informatics, such as activity segmentation, modeling, and recognition, is moving in an increasingly interpretable direction with the introduction of sports and kinematics knowledge. Many related research topics face a question: How long is the typical duration of the activities needed to be modeled? Several public human activity datasets do not strictly limit single motions’ repetition times, such as gait cycle numbers, in recording sessions, so they are not statistically significant concerning activity duration. Standing on the rigorous acquisition protocol design and well-segmented data corpus of the recently released multimodal wearable sensor-based human activity dataset CSL-SHARE, this paper analyzes the duration statistics and distribution of 22 basic single motions of daily activities and sports, hoping to provide research references for human activity studies. We discovered that (1) the duration of each studied human daily activity or s
imple sports activity reflects interpersonal similarities and naturally obeys a normal distribution; (2) one single motion (such as jumping and sitting down) or one cycle in the activities of cyclical motions (such as one gait cycle in walking) has an average duration in the interval from about 1 second to 2 seconds.
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