Large scale mood and stress self-assessments on a smartwatch

Hänsel, Katrin; Alomainy, Akram; Haddadi, Hamed

doi:10.1145/2968219.2968305

Cited by 24 publications

(18 citation statements)

References 10 publications

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“…Examples of direct sensing are sound capture, video camera, motion sensors, and wearable body sensors (ii) Indirect sensing "focuses on identifying environmental conditions and spatial features" [15] For direct sensing, ambient intelligence techniques can be used to embed the sensing data into the environment. Such techniques can be classified as remote, mobile, or wearable sensing [63].…”

Section: Activity and Affect Recognitionmentioning

confidence: 99%

A Review of Wrist-Worn Wearable: Sensors, Models, and Challenges

2018

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Wearable technology impacts the daily life of its users. Wearable devices are defined as devices embedded within clothes, watches, or accessories. Wrist-worn devices, as a type of wearable devices, have gained popularity among other wearable devices. They allow quick access to vital information, and they are suitable for many applications. This paper presents a comprehensive survey of wearable computing as a research field and provides a systematic review of recent work specifically on wrist-worn wearables. The focus of this research is on wrist-worn wearable studies because there is a lack of systematic literature reviews related to this area. This study reviewed journal and conference articles from 2015 and 2017 with some studies from 2014 and 2018, resulting in a selection of 54 studies that met the selection criteria. The literature showed that research in wrist-worn wearables spans three domains, namely, user interface and interaction studies, user studies, and activity/affect recognition studies. Our study then concludes with challenges and open research directions.

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Section: Activity and Affect Recognitionmentioning

confidence: 99%

A Review of Wrist-Worn Wearable: Sensors, Models, and Challenges

2018

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“…Hansal et al [13] have used a smartwatch and mobile phone to log the current emotional state of the user. Instances of location, heart rate, prior physical activity (steps and workouts), ambient noise and wrist movements, from the watch accelerometer, have been passively collected [13].…”

Section: A Sensing Emotion Using Lifelogging Technologiesmentioning

confidence: 99%

“…Instances of location, heart rate, prior physical activity (steps and workouts), ambient noise and wrist movements, from the watch accelerometer, have been passively collected [13]. However, the system does require users to rate their current emotional state multiple times a day via a questionnaire.…”

Section: A Sensing Emotion Using Lifelogging Technologiesmentioning

confidence: 99%

“…However, in order to be truly pervasive, sensing and measuring emotion needs to occur unobtrusively. Furthermore, the inclusion of physiological data is important as these body signals are capable of being used to predict emotional states [13,22,24].…”

Section: A Sensing Emotion Using Lifelogging Technologiesmentioning

confidence: 99%

“…Miniaturization of sensors and increased computational power has enabled mobile devices to acquire a variety of personal data, including physiological signals and contextual information [13]. This availability of this hardware has afforded us the opportunity to collect a greater amount of data "in the wild" within real-life situations.…”

Section: Introductionmentioning

confidence: 99%

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A mobile lifelogging platform to measure anxiety and anger during real-life driving

Dobbins

Fairclough

2017

2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)

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Abstract-The experience of negative emotions in everyday life, such as anger and anxiety, can have adverse effects on longterm cardiovascular health. However, objective measurements provided by mobile technology can promote insight into this psychobiological process and promote self-awareness and adaptive coping. It is postulated that the creation of a mobile lifelogging platform can support this approach by continuously recording personal data via mobile/wearable devices and processing this information to measure physiological correlates of negative emotions. This paper describes the development of a mobile lifelogging system that measures anxiety and anger during real-life driving. A number of data streams have been incorporated in the platform, including cardiovascular data, speed of the vehicle and first-person photographs of the environment. In addition, thirteen participants completed five days of data collection during daily commuter journeys to test the system. The design of the system hardware and associated data streams are described in the current paper, along with the results of preliminary data analysis.

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The Personality Panorama: Conceptualizing Personality through Big Behavioural Data

2020

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Personality psychology has long been grounded in data typologies, particularly in the delineation of behavioural, life outcome, informant‐report, and self‐report sources of data from one another. Such data typologies are becoming obsolete in the face of new methods, technologies, and data philosophies. In this article, we discuss personality psychology's historical thinking about data, modern data theory's place in personality psychology, and several qualities of big data that urge a rethinking of personality itself. We call for a move away from self‐report questionnaires and a reprioritization of the study of behaviour within personality science. With big data and behavioural assessment, we have the potential to witness the confluence of situated, seamlessly interacting psychological processes, forming an inclusive, dynamic, multiangle view of personality. However, big behavioural data come hand in hand with important ethical considerations, and our emerging ability to create a ‘personality panopticon’ requires careful and thoughtful navigation. For our research to improve and thrive in partnership with new technologies, we must not only wield our new tools thoughtfully, but humanely. Through discourse and collaboration with other disciplines and the general public, we can foster mutual growth and ensure that humanity's burgeoning technological capabilities serve, rather than control, the public interest. © 2020 European Association of Personality Psychology

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Large scale mood and stress self-assessments on a smartwatch

Cited by 24 publications

References 10 publications

A Review of Wrist-Worn Wearable: Sensors, Models, and Challenges

A Review of Wrist-Worn Wearable: Sensors, Models, and Challenges

A mobile lifelogging platform to measure anxiety and anger during real-life driving

The Personality Panorama: Conceptualizing Personality through Big Behavioural Data

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