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Andrew Fogg

dblp:10/1441 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Wearable and physiological sensing · 56% Health and well-being technologies · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wearable and physiological sensing
lifelogging		 0.112007
Do life-logging technologies support memory for the past?: an experimental study using sensecam · CHI 2007
Health and well-being technologies › cognitive support
memory support		 0.112007
Do life-logging technologies support memory for the past?: an experimental study using sensecam · CHI 2007
Wearable and physiological sensing
wearable camera		 0.012007
Do life-logging technologies support memory for the past?: an experimental study using sensecam · CHI 2007

Methods — techniques the papers use, named apart from their topics

experimental study · 0.1
YearPublicationVenuePosition
2007 Do life-logging technologies support memory for the past?: an experimental study using sensecam
abstract
We report on the results of a study using SenseCam, a "life-logging" technology in the form of a wearable camera, which aims to capture data about everyday life in order to support people's memory for past, personal events. We find evidence that SenseCam images do facilitate people's ability to connect to their past, but that images do this in different ways. We make a distinction between "remembering" the past, and "knowing" about it, and provide evidence that SenseCam images work differently over time in these capacities. We also compare the efficacy of user-captured images with automatically captured images and discuss the implications of these findings and others for how we conceive of and make claims about life-logging technologies.
Abigail Sellen, Andrew Fogg, Mike Aitken, Steve Hodges 0001, Carsten Rother, Kenneth R. Wood
 CHI2