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M. Khalid

dblp:40/6692 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2008
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging 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.

Artificial intelligence
1 paper
Motion planning and robot control · 100%
Human-computer interaction and pervasive computing
1 paper
Health and well-being technologies · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Health and well-being technologies › rehabilitation technology
functional electrical stimulation		 0.011996
Modular hybrid functional electrical stimulation system · ICRA 1996

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

robust control · 0.0human model · 0.0
YearPublicationVenuePosition
2008 CMAC for Driver Behavior Profiling based on Real-Time Driving Data
Abdul Wahab 0001, Norhaslinda Kamaruddin, M. Khalid
 CAINE3
1996 Modular hybrid functional electrical stimulation system
abstract
We consider the design of a modular hybrid functional electrical stimulation (FES) system for an injured person. We propose a system using an assistant robot to follow the FES performance, as FES control has many uncertainties in characteristics. The assistant robot used is a 3-link serial type, and attached to the injured person to actively assist the FES performance. The assistant robot must be very simple, light, and can be easily attached to the injured person. We constitute various types of human models which can be used to show the exact actions and muscle function characteristics. Furthermore, we propose a control system for the model of an injured person fitted with the assistant robot. Finally, we show that a robust performance of the injured person has been achieved in the standing motion using the modular hybrid FES system.
Toshihiro Yukawa, M. Khalid, Masaru Uchiyama, Hikaru Inooka, T. Ohashi, Goro Obinata, Hitoshi Kagaya, Yoichi Shimada
 ICRA2