%0 Conference Paper %1 xu2017realworld %A Xu, Yaqian %A Hübener, I. %A Seipp, A. K. %A Ohly, S. %A David, K. %B Proceedings of the 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) %C Kona, HI, USA %D 2017 %I IEEE %K comtec itegpub sociallink %P 345-350 %R 10.1109/PERCOMW.2017.7917586 %T From the lab to the real-world: An investigation on the influence of human movement on Emotion Recognition using physiological signals %X The recognition of human emotions using physiological signals such as Electrodermal Activity (EDA), Electrocardiogram (ECG) or Electromyography (EMG), has been extensively researched in the past attracting a lot of interest during the last few decades. Although showing a relatively satisfactory performance under lab conditions, Emotion Recognition (ER) systems using physiological signals are not widely used in real-world scenarios. One important fact is that, in the real world, physiological signals may be influenced by human movement and therefore, they cannot be used as a unique indicative of emotions. In this paper, we investigate the influence of human movement on ER using physiological signals. We compare different measures of emotion before and after a test person has performed some physical activity (e.g. walking, going upstairs). We discuss the main differences between recognizing emotions in the lab and the real world and provide new insights into the development of ER systems in real-world scenarios.

@inproceedings{xu2017realworld, abstract = {The recognition of human emotions using physiological signals such as Electrodermal Activity (EDA), Electrocardiogram (ECG) or Electromyography (EMG), has been extensively researched in the past attracting a lot of interest during the last few decades. Although showing a relatively satisfactory performance under lab conditions, Emotion Recognition (ER) systems using physiological signals are not widely used in real-world scenarios. One important fact is that, in the real world, physiological signals may be influenced by human movement and therefore, they cannot be used as a unique indicative of emotions. In this paper, we investigate the influence of human movement on ER using physiological signals. We compare different measures of emotion before and after a test person has performed some physical activity (e.g. walking, going upstairs). We discuss the main differences between recognizing emotions in the lab and the real world and provide new insights into the development of ER systems in real-world scenarios.}, added-at = {2017-05-11T10:32:32.000+0200}, address = {Kona, HI, USA}, author = {Xu, Yaqian and Hübener, I. and Seipp, A. K. and Ohly, S. and David, K.}, biburl = {https://www.bibsonomy.org/bibtex/2526368e11e7105a64a500af65686bea9/comtec_pub}, booktitle = {Proceedings of the 2017 {IEEE} {International} {Conference} on {Pervasive} {Computing} and {Communications} {Workshops} ({PerCom} {Workshops})}, doi = {10.1109/PERCOMW.2017.7917586}, interhash = {36121ee22150430140cf84efdf8a2fca}, intrahash = {526368e11e7105a64a500af65686bea9}, keywords = {comtec itegpub sociallink}, month = mar, pages = {345-350}, publisher = {IEEE}, timestamp = {2018-01-11T11:00:43.000+0100}, title = {From the lab to the real-world: {An} investigation on the influence of human movement on {Emotion} {Recognition} using physiological signals}, year = 2017 }