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David Allport

dblp:54/2068 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1995
—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
Interaction techniques and input · 65% Ubiquitous computing and smart environments · 28% Haptics and multimodal interaction · 6%

Topics — the 5 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interaction techniques and input › gesture input
bare-hand interaction
0.011995
Applying Electric Field Sensing to Human-Computer Interfaces · CHI 1995
Ubiquitous computing and smart environments
device-free sensing
0.011995
Applying Electric Field Sensing to Human-Computer Interfaces · CHI 1995
Interaction techniques and input › input sensing › touch sensing
electric field sensing
0.011995
Applying Electric Field Sensing to Human-Computer Interfaces · CHI 1995
Interaction techniques and input
gesture input
0.011995
Applying Electric Field Sensing to Human-Computer Interfaces · CHI 1995
Haptics and multimodal interaction › haptic feedback
passive haptic feedback
0.011995
Applying Electric Field Sensing to Human-Computer Interfaces · CHI 1995

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

analytical modeling of sensor measurements · 0.0
YearPublicationVenuePosition
1995 Applying Electric Field Sensing to Human-Computer Interfaces
abstract
A non-contact sensor based on the interaction of a person with electric fields for human-computer interface is investigated. Two sensing modes are explored: an external electric field shunted to ground through a human body, and an external electric field transmitted through a human body to stationary receivers. The sensors are low power (milliwatts), high resolution (millimeter) low cost (a few dollars per channel), have low latency (millisecond), high update rate (1 kHz), high immunity to noise (>72 dB), are not affected by clothing, surface texture or reflectivity, and can operate on length scales from microns to meters. Systems incorporating the sensors include a finger mouse, a room that knows the location of its occupant, and people-sensing furniture. Haptic feedback using passive materials is described. Also discussed are empirical and analytical approaches to transform sensor measurements into position information. KEYWORDS: user interface, input device, gesture interface, non-...
Thomas G. Zimmerman, Joshua R. Smith 0001, Joseph A. Paradiso, David Allport, Neil Gershenfeld
CHI4