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Akihiko Saito

dblp:13/49 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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
Ubiquitous computing and smart environments · 67% Health and well-being technologies · 33%

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

TopicWeightPapersLastEvidence papers
Ubiquitous computing and smart environments › context recognition
human behavior recognition
0.012000
Infant Behavior Recognition System Based on Pressure Distribution Image · ICRA 2000
Health and well-being technologies › health monitoring
infant monitoring
0.012000
Infant Behavior Recognition System Based on Pressure Distribution Image · ICRA 2000
Ubiquitous computing and smart environments
pressure distribution sensing
0.012000
Infant Behavior Recognition System Based on Pressure Distribution Image · ICRA 2000

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

pressure distribution image analysis · 0.0activity score · 0.0
YearPublicationVenuePosition
2000 Infant Behavior Recognition System Based on Pressure Distribution Image
abstract
The authors developed a novel infant behavior recognition system based on a pressure distribution image. The system can recognize an infant's status (quiet, moving and crying), posture, body parts' positions and movement unrestrainedly. It can, in recognizing the behavior, cope with the infant's rapid growth and unique physique. The algorithm of the infant behavior recognition system is summarized as follows. 1) First, the system measures the pressure distribution image with 384 pressure sensors distributed in the bed. 2) The authors propose "activity score"; this is calculated by using the measured pressure distribution image and indicates kinetic energy of the infant's activity. Based on the activity score, the system decides the infant's status. 3) If the infant is quiet, the system estimates the infant's physique. 4) Based on the estimated physique, the system recognizes the infant's posture and body part movement. Experimental results reveal that the system successfully recognizes infants' status (quiet, moving and crying), posture, body parts position and movements.
Tatsuya Harada, Akihiko Saito, Tomomasa Sato, Taketoshi Mori
ICRA2