Papers

7

Total Citations

65

H-Index

6

About

Mark Price is a researcher whose work bridges biomechanics, robotics, and rehabilitation engineering, with a particular focus on human movement augmentation and haptic interfaces. His research spans two compelling domains: musculoskeletal simulation and wearable robotic systems for gait rehabilitation. In the realm of computational biomechanics, Price has made notable contributions through dynamic optimization techniques applied to human movement. His work on incorporating actuator dynamics into musculoskeletal simulations (21 citations) and developing generalized prosthesis models for gait prediction (10 citations) advances how researchers evaluate and design assistive devices before physical prototyping. Price's parallel body of work on robotic exoskeletons demonstrates a sophisticated understanding of neural adaptation in locomotion. His studies on asymmetric hip stiffness applied through wearable exoskeletons reveal how the nervous system responds to mechanical perturbations, carrying important implications for neurological gait rehabilitation. Beyond lower-limb robotics, Price has explored haptic interfaces for large-format touchscreens, developing innovative steered-wheel mechanisms that deliver kinesthetic force feedback to users — an underexplored but practical frontier in human-computer interaction. With over 65 cumulative citations across seven publications spanning 2016 to 2024, Price represents a productive researcher whose interdisciplinary approach meaningfully connects computational modeling, robotic hardware design, and human motor learning.

Research Focus

Key Achievements

6
H-Index
7
Papers
65
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Inclusion of actuator dynamics in simulations of assisted human movement
21 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: University of Massachusetts Amherst, University of Žilina

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago