Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
An EMG-Based Control for an Upper-Limb Power-Assist Exoskeleton Robot
This map shows the geographic impact of Kazuo Kiguchi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kazuo Kiguchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kazuo Kiguchi more than expected).
This network shows the impact of papers produced by Kazuo Kiguchi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kazuo Kiguchi. The network helps show where Kazuo Kiguchi may publish in the future.
Co-authorship network of co-authors of Kazuo Kiguchi
This figure shows the co-authorship network connecting the top 25 collaborators of Kazuo Kiguchi.
A scholar is included among the top collaborators of Kazuo Kiguchi based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Kazuo Kiguchi. Kazuo Kiguchi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kiguchi, Kazuo & Yoshiaki Hayashi. (2012). Estimation of joint torque for a myoelectric arm by genetic programming based on EMG signals. World Automation Congress. 1–4.2 indexed citations
4.
Izumi, Kiyotaka, A. G. Buddhika P. Jayasekara, Keigo Watanabe, & Kazuo Kiguchi. (2010). Attentive and corrective feedback for adapting robot's perception on fuzzy linguistic information. Society of Instrument and Control Engineers of Japan. 1963–1968.1 indexed citations
HIROKAWA, Shunji, et al.. (2007). Development and evaluation of prosthesis capable of performing complete knee flexion. 28. 225–231.1 indexed citations
Izumi, Kiyotaka, et al.. (2003). Neural Network Based Disturbance Canceler with Feedback Error Learning for Nonholonomic Mobile Robots. 한국지능시스템학회 국제학술대회 발표논문집. 443–446.3 indexed citations
14.
Watanabe, Keigo, et al.. (2003). Control of redundant manipulators by fuzzy linguistic commands. Society of Instrument and Control Engineers of Japan. 3. 3199–3204.9 indexed citations
15.
Yamaguchi, Tomohiro, et al.. (2003). Obstacle Avoidance of Quadruped Robots with Consideration to the Order of Swing Leg. 제어로봇시스템학회 국제학술대회 논문집. 645–650.1 indexed citations
16.
Izumi, Keisuke, et al.. (2003). Control of nonholonomic mobile robots using a feedback error learning. Society of Instrument and Control Engineers of Japan. 3. 3205–3210.1 indexed citations
17.
Watanabe, Keigo, et al.. (2002). Obstacle Avoidance of Three-DOF Underactuated Manipulator by Using Switching Computed Torque Method. 4(4). 347–355.11 indexed citations
18.
Kiguchi, Kazuo, et al.. (2002). Application of Multiple Fuzzy-Neuro Controllers of an Exoskeletal Robot for Human Elbow Motion Support. 4(1). 49–55.14 indexed citations
19.
Watanabe, Keigo, et al.. (2001). Adaptive Actor-Critic Learning of Mobile Robots Using Actual and Simulated Experiences. 제어로봇시스템학회 국제학술대회 논문집. 312–316.7 indexed citations
20.
Watanabe, Keigo, et al.. (2001). Modular Fuzzy Neural Controller Driven by Voice Commands. 제어로봇시스템학회 국제학술대회 논문집. 194–197.11 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.