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Designing and installing long-term monitoring equipment in the users’ home sphere often presents challenges in terms of reliability, privacy, and deployment. Taking the logging of sleeping postures as an example, this study examines data from two very different modalities, high-fidelity video footage and logged wrist acceleration, that were chosen for their ease of setting up and deployability for...
This paper conducts a preliminary study in which sleeping behavior is predicted using long-term activity data from a wearable sensor. For this purpose, two scenarios are scrutinized: The first predicts sleeping behavior using a day-of-the-week model. In a second scenario typical sleep patterns for either working or weekend days are modeled. In a continuous experiment over 141 days (6 months), sleeping...
The monitoring of sleep by quantifying sleeping time and quality is pivotal in many preventive health care scenarios. A substantial amount of wearable sensing products have been introduced to the market for just this reason, detecting whether the user is either sleeping or awake. Assessing these devices for their accuracy in estimating sleep is a daunting task, as their hardware design tends to be...
The experience sampling methodology is a well known tool in psychology to asses a subject's condition. Regularly or whenever an important event happens the subject stops whatever he is currently involved in and jots down his current perceptions, experience, and activities, which in turn form the basis of these diary studies. Such methods are also widely in use for gathering labelled data for wearable...
Users share a lot of personal information with friends, family members, and colleagues via social networks. Surprisingly, some users choose to share their sleeping patterns, perhaps both for awareness as well as a sense of connection to others. Indeed, sharing basic sleep data, whether a person has gone to bed or waking up, informs others about not just one's sleeping routines but also indicates physical...
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