000265351 001__ 265351
000265351 005__ 20190812204800.0
000265351 037__ $$aCONF
000265351 245__ $$aMulti-Modal Acute Stress Recognition Using Off-the-Shelf Wearable Devices
000265351 260__ $$c2019-04-24
000265351 269__ $$a2019-04-24
000265351 300__ $$a6
000265351 336__ $$aConference Papers
000265351 520__ $$aMonitoring stress and, in general, emotions has attracted a lot of attention over the past few decades. Stress monitoring has many applications, including high-risk missions and surgical procedures as well as mental/emotional health monitoring. In this paper, we evaluate the possibility of stress and emotion monitoring using off-the-shelf wearable sensors. To this aim, we propose a multi-modal machine-learning technique for acute stress episodes detection, by fusing the information careered in several biosignals and wearable sensors. Furthermore, we investigate the contribution of each wearable sensor in stress detection and demonstrate the possibility of acute stress recognition using wearable devices. In particular, we acquire the physiological signals using the Shimmer3 ECG Unit and the Empatica E4 wristband. Our experimental evaluation shows that it is possible to detect acute stress episodes with an accuracy of 84.13%, for an unseen test set, using multi-modal machine-learning and sensor-fusion techniques.
000265351 6531_ $$aReal-Time Stress Detection; 
000265351 6531_ $$aAcute Stress Recognition;
000265351 6531_ $$aOnline Workload Detection;
000265351 6531_ $$aWearable Systems;
000265351 6531_ $$aWearable Devices;
000265351 6531_ $$aMulti-Modal Machine Learning;
000265351 6531_ $$aWearable Sensor Fusion;
000265351 700__ $$g303912$$aMontesinos Canovas, Victoriano$$0260923
000265351 700__ $$g206640$$aDell'Agnola, Fabio Isidoro Tiberio$$0248838
000265351 700__ $$g261121$$aArza Valdes, Adriana$$0251510
000265351 700__ $$0250060$$aAminifar, Amir$$g199984
000265351 700__ $$0240268$$aAtienza Alonso, David$$g169199
000265351 7112_ $$aInternational Engineering in Medicine and Biology Conference
000265351 710__ $$aVictoriano Montesinos
000265351 8560_ $$fbeatrice.marselli@epfl.ch
000265351 8564_ $$uhttps://infoscience.epfl.ch/record/265351/files/Multi-Modal%20Acute%20Stress%20Recognition%20Using%20Off-the-Shelf%20Wearable%20Devices.pdf$$s444255
000265351 909C0 $$mdavid.atienza@epfl.ch$$mhomeira.salimi@epfl.ch$$0252050$$zMarselli, Béatrice$$xU11977$$pESL
000265351 909CO $$pconf$$pSTI$$ooai:infoscience.epfl.ch:265351
000265351 960__ $$aamir.aminifar@epfl.ch
000265351 961__ $$afantin.reichler@epfl.ch
000265351 973__ $$aEPFL$$rREVIEWED
000265351 980__ $$aCONF
000265351 981__ $$aoverwrite