Investigating User Needs for Bio-sensing and Affective Wearables

Abstract

Bio-sensing wearables are currently advancing to provide users with a lot of information about their physiological and affective states. However, relatively little is known about users' interest in acquiring, sharing and receiving this information and through which channels and modalities. To close this gap, we report on the results of an online survey (N=109) exploring principle aspects of the design space of wearables such as data types, contexts, feedback modalities and sharing behaviors. Results show that users are interested in obtaining physiological, emotional and cognitive data through modalities beyond traditional touchscreen output. Valence of the information, whether positive or negative affects the sharing behaviors.

Exploring public wearable display of wellness tracker data

“…For example whilst noting motivational benefits, Gui et al [24] and Newman et al [48] report on users' concerns about their online image and the need to maintain a positive impression of one's self to the social community. Similar issues were found by Hassib et al [49] who studied users' willingness to share physiological, emotional, and cognitive personal data, finding that the parameter value or valence affects willingness to share [49].…”

“…The value from the data source takes on a positive or negative valence based on the perception of its value [49]. Whilst many of the perception thresholds that define valence are based on medical research, others may be cultural or based on targets created by groups or even individuals.…”

Improving Driver Emotions with Affective Strategies

“…An affective in-car system must, first of all, be aware of the driver's state [22], which is comprised, e.g., of physical features, mental workload, fatigue, the level of distraction, and emotions [16,23]. Psychophysiological measures like heart rate variability, skin conductance, skin temperature, breathing rate, or EEG can be used to deduce driver states [24][25][26][27][28]. At the same time, unobtrusive contactless technologies like audio-visual sensors or eye-tracking might have lower initial hurdles regarding acceptance in cars: a video stream of the driver can be used to extract facial action coding units, which in combination with voice features can inform an emotion detection system [29,30], and measures of pupil diameter can be used to assess mental workload [31].…”

“…A decrease in negative emotions results in a change of cognitive load and physiological signals [24][25][26][27][28].…”

Brainatwork

“…Recent research showed that knowledge about one's own state can boost productivity, empathy, and help in changing behaviors [7,11]. This increasing interest in self-awareness is evident in the growing quantified-self movement which utilizes long-term data collections for increasing health or well-being.…”