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Trisha Andrew

dblp:228/5978 · also Trisha L. Andrew · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2022
0000-0002-8193-2912ORCID · corroborated

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

Computer networks · 2 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

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
Wearable and physiological sensing · 67% Interaction techniques and input · 13% Games and playful interaction · 13%

Topics — the 2 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wearable and physiological sensing › textile sensors
textile pressure sensing
0.612022
FabToys: plush toys with large arrays of fabric-based pressure sensors to enable fine-grained interaction detection · MobiSys 2022
Wearable and physiological sensing
textile sensors
0.312018
Fabric as a Sensor: Towards Unobtrusive Sensing of Human Behavior with Triboelectric Textiles · SenSys 2018

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

fabric-based sensors · 0.6triboelectric sensing · 0.3
YearPublicationVenuePosition
2022 FabToys: plush toys with large arrays of fabric-based pressure sensors to enable fine-grained interaction detection
abstract
Recent advances in fabric-based sensors have made it possible to densely instrument textile surfaces on smart toys without changing their look and feel. While such surfaces can be instrumented with traditional sensors, rigid elements change the nature of interaction and diminish the appeal of plush toys.
Ali Kiaghadi, Seyedeh Zohreh Homayounfar, Trisha Andrew, Deepak Ganesan
MobiSys4
2022 PhyMask: Robust Sensing of Brain Activity and Physiological Signals During Sleep with an All-textile Eye Mask
abstract
Clinical-grade wearable sleep monitoring is a challenging problem since it requires concurrently monitoring brain activity, eye movement, muscle activity, cardio-respiratory features, and gross body movements. This requires multiple sensors to be worn at different locations as well as uncomfortable adhesives and discrete electronic components to be placed on the head. As a result, existing wearables either compromise comfort or compromise accuracy in tracking sleep variables. We propose PhyMask, an all-textile sleep monitoring solution that is practical and comfortable for continuous use and that acquires all signals of interest to sleep solely using comfortable textile sensors placed on the head. We show that PhyMask can be used to accurately measure all the signals required for precise sleep stage tracking and to extract advanced sleep markers such as spindles and K-complexes robustly in the real-world setting. We validate PhyMask against polysomnography (PSG) and show that it significantly outperforms two commercially-available sleep tracking wearables—Fitbit and Oura Ring.
Soha Rostaminia, Seyedeh Zohreh Homayounfar, Ali Kiaghadi, Trisha Andrew, Deepak Ganesan
ACM Trans. Comput. Heal.4
2018 Fabric as a Sensor: Towards Unobtrusive Sensing of Human Behavior with Triboelectric Textiles
abstract
Smart apparel with embedded sensors have the potential to revolutionize human behavior sensing by leveraging everyday clothing as the sensing substrate. However, existing textile-based sensing techniques rely on tight-fitting garments to obtain sufficient signal to noise, making it uncomfortable to wear and limiting the technology to niche applications like athletic performance monitoring.
Ali Kiaghadi, Morgan Baima, Jeremy Gummeson, Trisha Andrew, Deepak Ganesan
SenSys4