Data@Hand: Fostering Visual Exploration of Personal Data on Smartphones Leveraging Speech and Touch Interaction

TL;DR

This paper introduces Data@Hand, a mobile app that combines speech and touch to enhance personal health data exploration on smartphones, demonstrated through a user study with Fitbit users.

Contribution

It presents a novel multimodal interaction design for mobile health data visualization, integrating speech and touch for improved data exploration.

Findings

Participants successfully adopted multimodal interaction for data exploration.

Multimodal interaction facilitated more convenient and fluid data navigation.

Design implications for future mobile health visualization tools are discussed.

Abstract

Most mobile health apps employ data visualization to help people view their health and activity data, but these apps provide limited support for visual data exploration. Furthermore, despite its huge potential benefits, mobile visualization research in the personal data context is sparse. This work aims to empower people to easily navigate and compare their personal health data on smartphones by enabling flexible time manipulation with speech. We designed and developed Data@Hand, a mobile app that leverages the synergy of two complementary modalities: speech and touch. Through an exploratory study with 13 long-term Fitbit users, we examined how multimodal interaction helps participants explore their own health data. Participants successfully adopted multimodal interaction (i.e., speech and touch) for convenient and fluid data exploration. Based on the quantitative and qualitative findings, we discuss design implications and opportunities with multimodal interaction for better supporting visual data exploration on mobile devices.