RFexpress! – Exploiting the wireless network edge for RF-based emotion sensing

Muneeba Raja, Stephan Sigg

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

We present RFexpress! the first-ever network-edge based system to recognize emotion from movement, gesture and pose via Device-Free Activity Recognition (DFAR). With the proliferation of the IoT, also wireless access points are deployed at increasingly dense scale. in particular, this includes vehicular nodes (in-car WiFi or Bluetooth), office (Wlan APs, WiFi printer or projector) and private indoor domains (home WiFi mesh, Wireless media access), as well as public spaces (City/open WiFi, Cafes, shopping spaces). Processing RF-fluctuation at such edge-devices, enables environmental perception. In this paper, we focus on the distinction between neutral and agitated emotional states of humans from RF-fluctuation at the wireless network edge in realistic environments. In particular, the system is able to detect risky driving behaviour in a vehicular setting as well as spotting angry conversations in an indoor environment. We also study the effectiveness of edge-based DFAR emotion and activity recognition systems in real environments such as cafes, malls, outdoor and office spaces. We measure radio characteristics in these environments at different days and times and analyse the impact of variations in the Signal to Noise Ratio (SNR) on the accuracy of DFAR emotion and activity recognition. In a case study with 5 subjects, we then exploit the limits of edge-based DFAR by deriving critical SNR values under which activity and emotion recognition results are no longer reliable. In case studies with 8 and 5 subjects the system further could achieve recognition accuracies of 82.9% and 64% for vehicular and stationary wireless network edge in the wild (non-laboratory noisy environments and non-scripted, natural individual behaviour patterns).
Original languageEnglish
Title of host publicationProceedings of IEEE International Conference on Emerging Technologies and Factory Automation
PublisherIEEE
Number of pages8
ISBN (Electronic)978-1-5090-6505-9
DOIs
Publication statusPublished - 2018
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Emerging Technologies and Factory Automation - Limassol, Cyprus
Duration: 12 Sep 201715 Sep 2017
Conference number: 22

Publication series

NameProceedings of IEEE International Conference on Emerging Technologies and Factory Automation
ISSN (Print)1946-0740
ISSN (Electronic)2379-9560

Conference

ConferenceIEEE International Conference on Emerging Technologies and Factory Automation
Abbreviated titleETFA
CountryCyprus
CityLimassol
Period12/09/201715/09/2017

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