TY - GEN
T1 - Device-free sensing for classification of human activities using high-order cumulant algorithm
AU - Zhong, Yi
AU - Zhu, Jin Bao
AU - Dutkiewicz, Eryk
AU - Jiang, Ting
AU - Zhou, Zheng
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - In this paper, the possibility of using an emerging approach, namely device-free sensing (DFS) technology, for classification of human activities is investigated. To fully evaluate this approach, several samples have been collected in an outdoor open-field environment. Using the collected data along with a classifier, a high-order cumulant (HOC) based feature extraction algorithm is investigated. To demonstrate the improvement of using this algorithm, the classical approach that is based on received-signal strength (RSS) is chosen as a benchmark. The experiment results demonstrated that the classification accuracy of the proposed algorithm is better than the classical approach by at least 15%. In addition, the reliability of the presented approach due to variation of training samples and signal-to-noise ratio (SNR) are also carefully tested using experimentally recorded samples, so that a good reliability can be ensured.
AB - In this paper, the possibility of using an emerging approach, namely device-free sensing (DFS) technology, for classification of human activities is investigated. To fully evaluate this approach, several samples have been collected in an outdoor open-field environment. Using the collected data along with a classifier, a high-order cumulant (HOC) based feature extraction algorithm is investigated. To demonstrate the improvement of using this algorithm, the classical approach that is based on received-signal strength (RSS) is chosen as a benchmark. The experiment results demonstrated that the classification accuracy of the proposed algorithm is better than the classical approach by at least 15%. In addition, the reliability of the presented approach due to variation of training samples and signal-to-noise ratio (SNR) are also carefully tested using experimentally recorded samples, so that a good reliability can be ensured.
KW - device-free sensing technology
KW - high-order cumulant (HOC)
KW - human activities
KW - support vector machine (SVM)
UR - http://www.scopus.com/inward/record.url?scp=85049447250&partnerID=8YFLogxK
U2 - 10.1109/ISCIT.2017.8261203
DO - 10.1109/ISCIT.2017.8261203
M3 - Conference contribution
AN - SCOPUS:85049447250
T3 - 2017 17th International Symposium on Communications and Information Technologies, ISCIT 2017
SP - 1
EP - 4
BT - 2017 17th International Symposium on Communications and Information Technologies, ISCIT 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th International Symposium on Communications and Information Technologies, ISCIT 2017
Y2 - 25 September 2017 through 27 September 2017
ER -