Aku Visuri

Quantifying Sources and Types of Smartwatch Usage Sessions

We seek to quantify smartwatch use, and establish differences and similarities to smartphone use. Our analysis considers use traces from 307 users that include over 2.8 million notifications and 800,000 screen usage events, and we compare our findings to previous work that quantifies smartphone use. The results show that smartwatches are used more briefly and more frequently throughout the day, with half the sessions lasting less than 5 seconds. Interaction with notifications is similar across both types of devices, both in terms of response times and preferred application types. We also analyse the differences between our smartwatch dataset and a dataset aggregated from four previously conducted smartphone studies. The similarities and differences between smartwatch and smartphone use suggest effect on usage that go beyond differences in form factor.

Predicting interruptibility for manual data collection: a cluster-based user model

Previous work suggests that Quantified-Self applications can retain long-term usage with motivational methods. These methods often require intermittent attention requests with manual data input. This may cause unnecessary burden to the user, leading to annoyance, frustration and possible application abandonment. We designed a novel method that uses on-screen alert dialogs to transform recurrent smartphone usage sessions into moments of data contributions and evaluate how accurately machine learning can reduce unintended interruptions. We collected sensor data from 48 participants during a 4-week long deployment and analysed how personal device usage can be considered in scheduling data inputs. We show that up to 81.7% of user interactions with the alert dialogs can be accurately predicted using user clusters, and up to 75.5% of unintended interruptions can be prevented and rescheduled. Our approach can be leveraged by applications that require self-reports on a frequent basis and may provide a better longitudinal QS experience.

Sensing Cold-Induced Situational Impairments in Mobile Interaction Using Battery Temperature

Previous work has highlighted the detrimental effect of cold ambience on fine-motor skills during interaction with mobile devices. In this work, we develop a method to infer changes in finger temperature of smartphone users without the need for specialised hardware. Specifically, we demonstrate that smartphone battery temperature is a reliable gauge for determining changes to finger temperature. In addition, we show that the behaviour of smartphone battery temperature in cold settings is consistent across different smartphone models and battery configurations. Our method can be used to determine cold-induced situational impairments, and trigger interface adaptations during mobile interaction.

UbiMI'17: ubiquitous mobile instrumentation

Thanks to the rapid development of mobile technologies, smartphones allow people to be reachable anywhere and anytime. In addition to the benefits for end users, researchers and developers can also benefit from the powerful devices that participants potentially carry on a daily basis. This minitrack workshop brings together researchers with an interest on using mobile devices as instruments to collect data and conduct mobile user studies, with a focus on understanding human-behavior, routines and gathering context.

Designing a context-aware assistive infrastructure for elderly care

We present an assistive healthcare platform, CARE, which aims to provide daily support for elderly caregivers with context-aware, unobtrusive, and actionable information. This information is collected through a plethora of IoT sensors installed strategically at an elderly care centre and is accessed through an Android tablet application. The applications goal is to empower nurses with a better understanding of elderly needs and ultimately, improve the care service. We investigate how IoT devices and sensors can enable a pervasive healthcare system, and discuss a wide-range of important parameters for integration of elderly care practices.

Impact of mood changes on application selection

Users of quantified self applications habitually log and track personal information, such as mood. Attempts to automate the procedure of logging mood have been made, but applications themselves rarely provide insights into the users mental well-being. In this paper we explore data from two small scale studies related to mobile device usage and mood tracking. We analyse associations between users mood throughout the day and the use of smartphone applications from different categories. Our analysis provides insights into the users behaviour based on their device usage. These insights mean that QS applications can independently use simple analysis tools to provide similar insights for the user.

S3: environmental fingerprinting with a credit card-sized NFC powered sensor board

People have become more aware about their environment and pay more attention to conditions, e.g., air quality, and UV light exposure. Conventional technologies for reading environmental conditions are expensive, bulky, situated, and do not meet peoples need for a mobile and portable tool for environmental fingerprinting on demand. We present a mobile-enabled client-server system for personalized environmental fingerprinting and crowdsourced environmental fingerprint datasets using a smartphone and a portable credit card-sized NFC powered sensor board.

Exploring mobile ad formats to increase brand recollection and enhance user experience

Digital marketing is increasingly moving from desktop (e.g., browser) to mobile environments (e.g., within mobile applications). The means for delivering ads however, remains largely unchanged: banners and videos. In this work, we explore transforming ad delivery methods to the mobile environment while mitigating issues causing frustration and distractions to the users, evident in both web and mobile marketing. We demonstrate that softly enforcing interaction with the ad - with minimal usable screen space reduction - can improve users attitude towards mobile advertising. Brand recollection is also influenced via increased interactions with the ad delivery method.

Understanding elderly care: a field-study for designing future homes

While the population is aging the role of information and communication technology (ICT) has grown in elderly care. This development has brought versatile ICT-related supportive systems to professionals and laymen working with aging people. The current study analyzed how professionals in elderly care perceived their workflow challenges before new ICT is developed and implemented to support their work. The results of this study are set to inform the design of a novel ICT system for a sheltered care home.

Challenges of Quantified-­Self: Encouraging Self-­Reported Data Logging During Recurrent Smartphone Usage

© Visuri et al. Published by BCS Learning and Development. Proceedings of British HCI 2017 – Digital Make-Believe. Sunderland, UK. Challenges of Quantified-Self: Encouraging SelfReported Data Logging During Recurrent Smartphone Usage Aku Visuri, Niels van Berkel, Chu Luo, Jorge Goncalves, Denzil Ferreira, Vassilis Kostakos Center for Ubiquitous Computing, University of Oulu; The University of Melbourne (first.last)@oulu.fi; n.vanberkel, chul3, jorge.goncalves, vassilis.kostakos@{student.}unimelb.edu.au