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Kevin Huang 0003

dblp:02/436-3 · DBLP profile ↗
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3ranked-venue papers
3as first author
0since 2021 · last 2014
0000-0001-7885-5752ORCID · corroborated

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

Human-computer interaction and ubiquitous computing · 3 · 3 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
2 papers
Health and well-being technologies · 38% Haptics and multimodal interaction · 25% Ubiquitous computing and smart environments · 19%

Topics — the 8 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Health and well-being technologies › rehabilitation
physical therapy
0.212014
A technology probe of wearable in-home computer-assisted physical therapy · CHI 2014
Health and well-being technologies › rehabilitation
physical therapy assistance
0.212014
A technology probe of wearable in-home computer-assisted physical therapy · CHI 2014
Ubiquitous computing and smart environments › smart home
smart home sensing
0.212014
A technology probe of wearable in-home computer-assisted physical therapy · CHI 2014
Learning and educational technologies › music education
music learning
0.112010
Mobile music touch: mobile tactile stimulation for passive learning · CHI 2010
Haptics and multimodal interaction › haptics
passive haptic learning
0.112010
Mobile music touch: mobile tactile stimulation for passive learning · CHI 2010
Haptics and multimodal interaction
tactile stimulation
0.112010
Mobile music touch: mobile tactile stimulation for passive learning · CHI 2010
Human-robot interaction › service robot › domestic robotics
home deployment
0.112014
A technology probe of wearable in-home computer-assisted physical therapy · CHI 2014
Haptics and multimodal interaction
wearable haptic device
0.012010
Mobile music touch: mobile tactile stimulation for passive learning · CHI 2010

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

technology probe · 0.2field deployment · 0.2user study · 0.1
YearPublicationVenuePosition
2014 A technology probe of wearable in-home computer-assisted physical therapy
abstract
Physical therapists could make better treatment decisions if they had accurate patient home exercise data but today this information is only available from patient self-report. A more accurate source of data could be gained from wearable computing designed for physical therapy exercise support. Existing systems have been tested in the lab but we have little information about issues they may face in home settings. We designed a technology probe, SenseCap, and deployed it for seven days in ten physical therapy patients' homes. SenseCap is a wearable physical therapy support system that gathers patient exercise compliance and performance data and summarizes the data in charts on an iPad Dashboard for physical therapists to view when patients return to the clinic. In this paper, we present the results of our deployment, show in-home patient exercise data gathered by the probe, and make design recommendations based on patient and physical therapist responses.
Kevin Huang 0003, Patrick J. Sparto, Sara B. Kiesler, Asim Smailagic, Jennifer Mankoff, Daniel P. Siewiorek
CHI1
2010 Mobile music touch: mobile tactile stimulation for passive learning
abstract
Mobile Music Touch (MMT) helps teach users to play piano melodies while they perform other tasks. MMT is a lightweight, wireless haptic music instruction system consisting of fingerless gloves and a mobile Bluetooth enabled computing device, such as a mobile phone. Passages to be learned are loaded into the mobile phone and are played repeatedly while the user performs other tasks. As each note of the music plays, vibrators on each finger in the gloves activate, indicating which finger is used to play each note. We present two studies on the efficacy of MMT. The first measures 16 subjects' ability to play a passage after using MMT for 30 minutes while performing a reading comprehension test. The MMT system was significantly more effective than a control condition where the passage was played repeatedly but the subjects' fingers were not vibrated. The second study compares the amount of time required for 10 subjects to replay short, randomly generated passages using passive training versus active training. Participants with no piano experience could repeat the passages after passive training while subjects with piano experience often could not.
Kevin Huang 0003, Thad Starner, Ellen Yi-Luen Do, Gil Weinberg, Daniel Kohlsdorf, Claas Ahlrichs, Rüdiger Leibrandt
CHI1
2008 Breaking the sound barrier: designing an interactive tool for language acquisition in preschool deaf children
abstract
This paper introduces a new interactive tool for teaching ASL to deaf preschool children. Our design makes use of a familiar form-factor, that of a teddy bear, to create a tangible media solution to presenting video content and providing intuitive means of interaction. Children interact with the system by "showing" the bear RFID flash cards to trigger ASL videos on an embedded LCD screen. The system supports different modes of learning and the ability to track the user's progress over time. Here we describe the design, prototyping, and evaluation of this system, which has been well-received in our initial pilot study. At the time of submission, a more empirically-based evaluation is under development.
Kevin Huang 0003, Jesse Smith, Kimberly Spreen, Mary Frances Jones
IDC1