By a News Reporter-Staff News Editor at Journal of Technology -- New research on Sensor Research is the subject of a report. According to news reporting out of Suwon, South Korea, by VerticalNews editors, research stated, "Smartphone-based activity recognition (SP-AR) recognizes users' activities using the embedded accelerometer sensor. Only a small number of previous works can be classified as online systems, i.e., the whole process (pre-processing, feature extraction, and classification) is performed on the device."
Our news journalists obtained a quote from the research from Ajou University, "Most of these online systems use either a high sampling rate (SR) or long data-window (DW) to achieve high accuracy, resulting in short battery life or delayed system response, respectively. This paper introduces a real-time/online SP-AR system that solves this problem. Exploratory data analysis was performed on acceleration signals of 6 activities, collected from 30 subjects, to show that these signals are generated by an autoregressive (AR) process, and an accurate AR-model in this case can be built using a low SR (20 Hz) and a small DW (3 s). The high within class variance resulting from placing the phone at different positions was reduced using kernel discriminant analysis to achieve position-independent recognition. Neural networks were used as classifiers. Unlike previous works, true subject-independent evaluation was performed, where 10 new subjects evaluated the system at their homes for 1 week."
According to the news editors, the research concluded: "The results show that our features outperformed three commonly used features by 40% in terms of accuracy for the given SR and DW."
For more information on this research see: Exploratory data analysis of acceleration signals to select light-weight and accurate features for real-time activity recognition on smartphones. Sensors, 2013;13(10):13099-122. (Elsevier - www.elsevier.com; Sensors - www.elsevier.com/wps/product/cws_home/504103)
Our news journalists report that additional information may be obtained by contacting A.M. Khan, Division of Information and Computer Engineering, Ajou University, San 5 Woncheon-dong, Suwon 443-749, South Korea. Additional authors for this research include M.H. Siddiqi and S.W Lee.
Keywords for this news article include: Asia, Suwon, South Korea, Sensor Research.
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