Demo Data from EDBT 2026 / reviewers in the wild / expert
Frank Mendel
dblp:03/8072
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, 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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 87% Computational science and engineering · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics › medical simulation
musculoskeletal simulation |
0.1 | 1 | 2009 | Case Studies of Musculoskeletal-Simulation-Based Rehabilitation Program Evaluation · IEEE Trans. Robotics 2009 |
Medical and health informatics
rehabilitation |
0.1 | 1 | 2009 | Case Studies of Musculoskeletal-Simulation-Based Rehabilitation Program Evaluation · IEEE Trans. Robotics 2009 |
Computational science and engineering › engineering design
simulation-based design |
0.0 | 1 | 2009 | Case Studies of Musculoskeletal-Simulation-Based Rehabilitation Program Evaluation · IEEE Trans. Robotics 2009 |
Methods — techniques the papers use, named apart from their topics
parametric study · 0.1optimization · 0.1musculoskeletal analysis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | Case Studies of Musculoskeletal-Simulation-Based Rehabilitation Program EvaluationabstractVariability in motor rehabilitation program outcomes can be attributed not only to individual components (human patient/rehabilitation equipment) but also to their system-level interactions. Thus, effective deployment of a rehabilitation program depends upon: 1) suitable therapist selection of user-device ergonomics; 2) adjustable device settings; and 3) exercise regimen parameters; to achieve desired system-level motor performance. In this paper, we discuss aspects of creation of a virtual design environment, leveraging tools from musculoskeletal analysis, optimization, and simulation-based design, to permit therapists to rapidly evaluate and systematically customize rehabilitation programs. Specifically, this framework is intended to facilitate 1) parametric study of ergonomic/device/regimen settings on musculoskeletal performance; 2) use of design tools such as optimization for decision support in arriving at the best program; and 3) scaffolded examination of linkage between form and function by iterative what-if type of analyses. We use two case studies (bicep-curling and motor rehabilitative driving) to highlight benefits of such simulation-based rehabilitation program evaluation. Leng-Feng Lee, Madusudanan Sathia Narayanan, Srikanth Kannan, Frank Mendel, Venkat N. Krovi |
IEEE Trans. Robotics | 4 |