Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult

Castillo, José Carlos; Castro‐González, Álvaro; Fernández-Caballero, Antonio; Postigo, José Miguel Latorre; Pastor, José Manuel; Fernández-Sotos, Alicia; Salichs, Miguel Á.

doi:10.1007/s12559-016-9383-y

Cited by 72 publications

(34 citation statements)

References 47 publications

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“…Negative stress (or distress) is one of the most important mental states due to its significant effects in health [1][2][3]. Distress is considered cause and consequence of failure and difficulties in a wide variety of daily situations.…”

Section: Discussionmentioning

confidence: 99%

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Estimation of Mental Distress from Photoplethysmography

et al. 2018

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This paper introduces the design of a new wearable photoplethysmography (PPG) sensor and its assessment for mental distress estimation. In our design, a PPG sensor obtains blood volume information by means of an optical plethysmogram technique. A number of temporal, morphological and frequency markers are computed using time intervals between adjacent normal cardiac cycles to characterize pulse rate variability (PRV). In order to test the efficiency of the developed wearable for classifying distress versus calmness, the well-known International Affective Picture System has been used to induce different levels of arousal in forty-five healthy participants. The obtained results have shown that temporal features present a single discriminant power between emotional states of calm and stress, ranging from 67 to 72%. Moreover, a discriminant tree-based model is used to assess the possible underlying relationship among parameters. In this case, the combination of temporal parameters reaches 82.35% accuracy. Considering the low difficulty of metrics and methods used in this work, the algorithms are prepared to be embedded into a micro-controller device to work in real-time and in a long-term fashion.

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Section: Discussionmentioning

confidence: 99%

“…Mental distress can result in negative views of the environment, others, and the self. This is why it is important to investigate on devices and environments capable of recognizing and/or regulating negative emotions [1][2][3][4][5]. Sadness, anxiety, distraction, and symptoms of mental illness are manifestations of psychological distress.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Mental Distress from Photoplethysmography

et al. 2018

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“…As one subset of video object tracking, pedestrian detection and tracking has drawn massive research attention and been applied to many applications such as visual surveillance [4][5][6][7][8], driverassistance systems [9][10][11], human activity recognition [12][13][14], and others [15,16]. For pedestrian detection and tracking, visible camera and thermal imagery are two popularly used sources of image modalities, though not necessarily in a combined solution [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Cognitive Fusion of Thermal and Visible Imagery for Effective Detection and Tracking of Pedestrians in Videos

Yan¹,

Ren²,

Zhao

et al. 2017

Cogn Comput

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In this paper, we present an efficient framework to cognitively detect and track salient objects from videos. In general, colored visible image in red-green-blue (RGB) has better distinguishability in human visual perception, yet it suffers from the effect of illumination noise and shadows. On the contrary, the thermal image is less sensitive to these noise effects though its distinguishability varies according to environmental settings. To this end, cognitive fusion of these two modalities provides an effective solution to tackle this problem. First, a background model is extracted followed by a two-stage background subtraction for foreground detection in visible and thermal images. To deal with cases of occlusion or overlap, knowledge-based forward tracking and backward tracking are employed to identify separate objects even the foreground detection fails. To evaluate the proposed method, a publicly available color-thermal benchmark dataset Object Tracking and Classification in and Beyond the Visible Spectrum is employed here. For our foreground detection evaluation, objective and subjective analysis against several state-of-the-art methods have been done on our manually segmented ground truth. For our object tracking evaluation, comprehensive qualitative experiments have also been done on all video sequences. Promising results have shown that the proposed fusion-based approach can successfully detect and track multiple human objects in most scenes regardless of any light change or occlusion problem.

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“…Wearable systems are particularly important to an ever increasingly ageing population [4], [5]. The potential of real-world applications using wearable health monitoring is paramount.…”

Section: Introductionmentioning

confidence: 99%

ARISTARKO: A Software Framework for Physiological Data Acquisition

Martínez-Rodrigo

Pastor

Zangróniz

et al. 2016

Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016)

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This paper introduces a software framework denominated ARISTARKO. ARISTARKO has been designed and developed to integrate the data acquisition from a wearable physiological data acquisition device with any necessary processing layers in order to classify the acquired signals into a predefined set of emotional states. In this particular article, we use ARISTARKO for the sake of designing an experiment capable of showing a series of images from the well-known IAPS database. The IAPS pictures are labelled with arousal, valence and dominance values. Arousal is classified from the information contained in the database and the physiological signals acquired by the wearable, namely electro-dermal, electrocardiogram and superficial electromyogram activity, and skin temperature.

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Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult

Cited by 72 publications

References 47 publications

Estimation of Mental Distress from Photoplethysmography

Estimation of Mental Distress from Photoplethysmography

Cognitive Fusion of Thermal and Visible Imagery for Effective Detection and Tracking of Pedestrians in Videos

ARISTARKO: A Software Framework for Physiological Data Acquisition

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