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Diary-Like Long-Term Activity Recognition: Touch or Voice Interaction? | IEEE Conference Publication | IEEE Xplore

Diary-Like Long-Term Activity Recognition: Touch or Voice Interaction?


Abstract:

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 ...Show More

Abstract:

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 long-term activity recognition, where subjects are asked to note conducted activities. We present the design of a personal electronic diary for daily activities, including user interfaces on a PC, Smartphone, and Google Glass. A 23-participant structured in-field study covering seven different activities highlights the difference of mobile touch interaction and ubiquitous voice recognition for tracking activities.
Date of Conference: 16-19 June 2014
Date Added to IEEE Xplore: 04 December 2014
ISBN Information:
Conference Location: Zurich, Switzerland
Citations are not available for this document.

I. Introduction

Ecological Momentary Assessment (EMA) [1] is a type of psychological study design concerned with the sampling of experiences throughout the course of a day. In contrast to study designs like End-of-Day diaries, EMA designs are less prone recall, recency, peak and summary bias [2]. Mainly because the sampling happens on a regular basis by the use of electronic diaries. These can be either watches, palm computers, Smartphones or any other mobile computing device, which remind the participant that an input is necessary. This “manual” sampling of experiences / activities is dual to gathering self-reported ground truth for wearable activity recognition systems.

Cites in Papers - |

Cites in Papers - IEEE (1)

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1.
Rebecca Adaimi, Ka Tai Ho, Edison Thomaz, "Usability of a Hands-Free Voice Input Interface for Ecological Momentary Assessment", 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp.1-5, 2020.

Cites in Papers - Other Publishers (2)

1.
Xinghui Yan, Katy Madier, Sun Young Park, Mark Newman, "Towards Low-burden In-situ Self-reporting", Companion Publication of the 2019 on Designing Interactive Systems Conference 2019 Companion, pp.337, 2019.
2.
Javier Hernandez, Daniel McDuff, Christian Infante, Pattie Maes, Karen Quigley, Rosalind Picard, "Wearable ESM", Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services, pp.195, 2016.
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References

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