Wearable-Based Affect Recognition—A Review

Affect recognition is an interdisciplinary research field bringing together researchers from natural and social sciences. Affect recognition research aims to detect the affective state of a person based on observables, with the goal to, for example, provide reasoning for the person’s decis...

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Main Authors: Philip Schmidt, Attila Reiss, Robert Dürichen, Kristof Van Laerhoven
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/19/19/4079
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spelling doaj-93ae919a826c4ee3821c37b22022be682020-11-25T02:43:20ZengMDPI AGSensors1424-82202019-09-011919407910.3390/s19194079s19194079Wearable-Based Affect Recognition—A ReviewPhilip Schmidt0Attila Reiss1Robert Dürichen2Kristof Van Laerhoven3Robert Bosch GmbH, Robert-Bosch-Campus 1, 71272 Renningen, GermanyRobert Bosch GmbH, Robert-Bosch-Campus 1, 71272 Renningen, GermanyRobert Bosch GmbH, Robert-Bosch-Campus 1, 71272 Renningen, GermanyUniversity Siegen , Hölderlinstr. 3, 57076 Siegen, GermanyAffect recognition is an interdisciplinary research field bringing together researchers from natural and social sciences. Affect recognition research aims to detect the affective state of a person based on observables, with the goal to, for example, provide reasoning for the person’s decision making or to support mental wellbeing (e.g., stress monitoring). Recently, beside of approaches based on audio, visual or text information, solutions relying on wearable sensors as observables, recording mainly physiological and inertial parameters, have received increasing attention. Wearable systems enable an ideal platform for long-term affect recognition applications due to their rich functionality and form factor, while providing valuable insights during everyday life through integrated sensors. However, existing literature surveys lack a comprehensive overview of state-of-the-art research in wearable-based affect recognition. Therefore, the aim of this paper is to provide a broad overview and in-depth understanding of the theoretical background, methods and best practices of wearable affect and stress recognition. Following a summary of different psychological models, we detail the influence of affective states on the human physiology and the sensors commonly employed to measure physiological changes. Then, we outline lab protocols eliciting affective states and provide guidelines for ground truth generation in field studies. We also describe the standard data processing chain and review common approaches related to the preprocessing, feature extraction and classification steps. By providing a comprehensive summary of the state-of-the-art and guidelines to various aspects, we would like to enable other researchers in the field to conduct and evaluate user studies and develop wearable systems.https://www.mdpi.com/1424-8220/19/19/4079reviewaffective computingaffect recognitionwearablesdata collectionphysiological signalsmachine learningphysiological featuresensors
collection DOAJ
language English
format Article
sources DOAJ
author Philip Schmidt
Attila Reiss
Robert Dürichen
Kristof Van Laerhoven
spellingShingle Philip Schmidt
Attila Reiss
Robert Dürichen
Kristof Van Laerhoven
Wearable-Based Affect Recognition—A Review
Sensors
review
affective computing
affect recognition
wearables
data collection
physiological signals
machine learning
physiological feature
sensors
author_facet Philip Schmidt
Attila Reiss
Robert Dürichen
Kristof Van Laerhoven
author_sort Philip Schmidt
title Wearable-Based Affect Recognition—A Review
title_short Wearable-Based Affect Recognition—A Review
title_full Wearable-Based Affect Recognition—A Review
title_fullStr Wearable-Based Affect Recognition—A Review
title_full_unstemmed Wearable-Based Affect Recognition—A Review
title_sort wearable-based affect recognition—a review
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2019-09-01
description Affect recognition is an interdisciplinary research field bringing together researchers from natural and social sciences. Affect recognition research aims to detect the affective state of a person based on observables, with the goal to, for example, provide reasoning for the person’s decision making or to support mental wellbeing (e.g., stress monitoring). Recently, beside of approaches based on audio, visual or text information, solutions relying on wearable sensors as observables, recording mainly physiological and inertial parameters, have received increasing attention. Wearable systems enable an ideal platform for long-term affect recognition applications due to their rich functionality and form factor, while providing valuable insights during everyday life through integrated sensors. However, existing literature surveys lack a comprehensive overview of state-of-the-art research in wearable-based affect recognition. Therefore, the aim of this paper is to provide a broad overview and in-depth understanding of the theoretical background, methods and best practices of wearable affect and stress recognition. Following a summary of different psychological models, we detail the influence of affective states on the human physiology and the sensors commonly employed to measure physiological changes. Then, we outline lab protocols eliciting affective states and provide guidelines for ground truth generation in field studies. We also describe the standard data processing chain and review common approaches related to the preprocessing, feature extraction and classification steps. By providing a comprehensive summary of the state-of-the-art and guidelines to various aspects, we would like to enable other researchers in the field to conduct and evaluate user studies and develop wearable systems.
topic review
affective computing
affect recognition
wearables
data collection
physiological signals
machine learning
physiological feature
sensors
url https://www.mdpi.com/1424-8220/19/19/4079
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AT attilareiss wearablebasedaffectrecognitionareview
AT robertdurichen wearablebasedaffectrecognitionareview
AT kristofvanlaerhoven wearablebasedaffectrecognitionareview
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