Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation

Fernández-Caballero, Antonio; Postigo, José Miguel Latorre; Pastor, José Manuel; Fernández-Sotos, Alicia

doi:10.1007/978-3-319-13105-4_50

Cited by 41 publications

(19 citation statements)

References 23 publications

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“…Emotion Recognition: Recent years have witnessed a growing interest in systems capable of inferring user emotions and reacting to them [24,25]. Such systems can be used for designing and testing games, movies, advertisement, online content, and human-computer Finally, another class of emotion recognition techniques relies on smartphone usage patterns (calling, application usage, etc.)…”

Section: Background and Related Workmentioning

confidence: 99%

Emotion recognition using wireless signals

Zhao

Adib

Katabi

2016

Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking

352

165

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This thesis demonstrates a new technology that can infer a person's emotions from RF signals reflected off his body. EQ-Radio transmits an RF signal and analyzes its reflections off a person's body to recognize his emotional state (happy, sad, etc.). The key enabler underlying EQ-Radio is a new algorithm for extracting the individual heartbeats from the wireless signal at an accuracy comparable to on-body ECG monitors. The resulting beats are then used to compute emotion-dependent features which feed a machine-learning emotion classifier. We describe the design and implementation of EQ-Radio, and demonstrate through a user study that its emotion recognition accuracy is on par with state-of-the-art emotion recognition systems that require a person to be hooked to an ECG monitor. I am grateful to the members of the NETMIT for their insightful discussions and to all the human subjects for their participation in our experiments.

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Section: Background and Related Workmentioning

confidence: 99%

Emotion recognition using wireless signals

Zhao

Adib

Katabi

2016

Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking

352

165

View full text Add to dashboard Cite

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“…This article is based on the assumption of the power of color to change mood. The described proposal falls within the project"Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation" [2], [3]. The objective of the project is to find solutions for improving the quality of life and care of the elderly who can or wants to continue living at home by using emotion detection and regulation means.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Color Preference for Emotion Regulation

Sokolova

Fernández-Caballero

Ros

et al. 2015

Artificial Computation in Biology and Medicine

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Abstract. This paper introduces a study on the relationship between emotion regulation and color preference. In the described pilot study, participants are asked to label uniform color images by using opposite meaningful words belonging to four semantic scales, namely "Tension" (ranging from Relax to Stress), "Temperature" (Coldness to Warmness), "Amusement" (Boredom to Fun) and "Attractiveness" (Pleasantness to Unpleasantness). Simultaneously, the participants have to indicate if they feel certain emotions while observing each colored image, as well as to rate the intensity of the feeling. The labeled emotions are "Joy", "Happiness", and "Sadness". The results demonstrate that people generally perceive color emotions for one-colored images in similar ways, though showing some variations for males and females. Several conclusions about the relations between color and emotions are presented.

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“…It is well known that elderly people generally prefer to live in their own homes over other options [5,6]. This fact causes an additional tear in the healthcare system balances since elderly have to be attended at their homes.…”

Section: Introductionmentioning

confidence: 98%

Non-lineal EEG Modelling by Using Quadratic Entropy for Arousal Level Classification

Martínez-Rodrigo

Alcaraz

García-Martínez

et al. 2016

Innovation in Medicine and Healthcare 2016

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Nowadays, assistive technologies together with ubiquitous and pervasive computing are emerging as main alternative to help ageing population. In this respect, an important number of works have been carried out to improve the quality of life in elderly from a physical point of view. However, less efforts have been made in monitoring the mental and emotional states of the elderly. This work presents a nonlinear model for discriminating different arousal levels through quadratic entropy and a decision tree-based algorithm. Two hundred and seventy eight EEG recordings lasting one minute each were used to train the proposed model. The recordings belong to the Dataset for Emotion Analysis using Physiological signals (DEAP). In agreement with the complexity and variability observed in other works, our results report a low quadratic entropy when subjects face high arousal stimuli. Finally, the model achieves a global performance around 70 % when discriminating between calm and excitement events.

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Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation

Cited by 41 publications

References 23 publications

Emotion recognition using wireless signals

Emotion recognition using wireless signals

Evaluation of Color Preference for Emotion Regulation

Non-lineal EEG Modelling by Using Quadratic Entropy for Arousal Level Classification

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