Demo Data from SIGIR 2026 / reviewers in the wild / expert
Nathan Dunkelberger
dblp:220/4621
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2018
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 first-author
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 |
Haptics and multimodal interaction · 70% Accessibility and assistive technology · 30% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Haptics and multimodal interaction
haptic communication |
0.3 | 1 | 2018 | Conveying language through haptics: a multi-sensory approach · UbiComp 2018 |
Accessibility and assistive technology › assistive technology
sensory substitution |
0.3 | 1 | 2018 | Conveying language through haptics: a multi-sensory approach · UbiComp 2018 |
Haptics and multimodal interaction
wearable haptic device |
0.1 | 1 | 2018 | Conveying language through haptics: a multi-sensory approach · UbiComp 2018 |
Methods — techniques the papers use, named apart from their topics
user study · 0.3training · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Conveying language through haptics: a multi-sensory approachabstractIn our daily lives, we rely heavily on our visual and auditory channels to receive information from others. In the case of impairment, or when large amounts of information are already transmitted visually or aurally, alternative methods of communication are needed. A haptic language offers the potential to provide information to a user when visual and auditory channels are unavailable. Previously created haptic languages include deconstructing acoustic signals into features and displaying them through a haptic device, and haptic adaptations of Braille or Morse code; however, these approaches are unintuitive, slow at presenting language, or require a large surface area. We propose using a multi-sensory haptic device called MISSIVE, which can be worn on the upper arm and is capable of producing brief cues, sufficient in quantity to encode the full English phoneme set. We evaluated our approach by teaching subjects a subset of 23 phonemes, and demonstrated an 86% accuracy in a 50 word identification task after 100 minutes of training. Nathan Dunkelberger, Jennifer L. Sullivan, Joshua Bradley, Nickolas P. Walling, Indu Manickam, Gautam Dasarathy, Ali Israr, Frances Lau, Keith Klumb, Brian Knott, Freddy Abnousi, Richard G. Baraniuk, Marcia Kilchenman O'Malley |
UbiComp | 1 |