Daniel Paluska

896 citations
6 papers · 650 · h-index 6

Impact in

    • Stroke Rehabilitation and Recovery
    • Prosthetics and Rehabilitation Robotics
    • Muscle activation and electromyography studies
    • Robotic Locomotion and Control
    • Soft Robotics and Applications
    • Mechanical Circulatory Support Devices
    • Advanced Sensor and Energy Harvesting Materials

Papers in

Daniel Paluska

6 papers receiving 623 citations

Peers

Daniel Paluska
Comparison fields: 5 of 42
  • Rehabilitation 125
  • Biomedical Engineering 607
  • Control and Systems Engineering 151
  • Physical Therapy, Sports Therapy and Rehabilitation 17
  • Mechanical Engineering 73
Replace Kazuhito HYODO with:
Kazuhito HYODO Japan
Daniele Cafolla Italy
Jing Qiu China
Giorgio Carpino Italy
Pierre Cherelle Belgium
Mineo Ishii Japan
Vivek Sangwan United States
Kenneth A. Pasch United States
Pieter Beyl Belgium
Gian Maria Gasparri Italy
Daniel Paluska relative to Kazuhito HYODO Japan Kazuhito HYODO's profile →
Citations per field
00.5×3.3×
Kazuhito HYODO · 1×
Citations per year

Countries citing papers authored by Daniel Paluska

Since Specialization
Citations

This map shows the geographic impact of Daniel Paluska'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 Daniel Paluska with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Paluska more than expected).

Fields of papers citing papers by Daniel Paluska

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Paluska. 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 Daniel Paluska. The network helps show where Daniel Paluska may publish in the future.

Co-authors

The 11 scholars most cited alongside Daniel Paluska, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Paluska Line = papers co-authored together Daniel Paluska links everyone, so they are left out of the graph.

All Works

About Daniel Paluska

Daniel Paluska is a scholar working on Biomedical Engineering, Pathology and Forensic Medicine, Rehabilitation, Cognitive Neuroscience and Infectious Diseases, having authored 6 papers that have together received 650 indexed citations. Recurring topics across this work include Prosthetics and Rehabilitation Robotics (6 papers), Muscle activation and electromyography studies (5 papers), Robotic Locomotion and Control (3 papers), Motor Control and Adaptation (1 paper), Spinal Cord Injury Research (1 paper), Advanced Sensor and Energy Harvesting Materials (1 paper) and Stroke Rehabilitation and Recovery (1 paper). The work is most often cited by research in Rehabilitation (125 citations), Biomedical Engineering (607 citations), Control and Systems Engineering (151 citations), Physical Therapy, Sports Therapy and Rehabilitation (17 citations) and Mechanical Engineering (73 citations). Daniel Paluska has collaborated with scholars based in United States. Frequent co-authors include Hugh Herr, Jerry Pratt, David Robinson, Gill A. Pratt, Conor J. Walsh, Kenneth A. Pasch, Ken Endo, Yi-Je Lim, Ye Ding and Paolo Bonato. Their work appears in journals such as Robotics and Autonomous Systems and PubMed.

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.

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