Massimo Sartori
Biomedical Engineering · 2012–2017
A researcher in the Science corpus: 3 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Biomedical Engineering — 26 citations into it
- Cognitive Neuroscience — 16 citations into it
- Orthopedics and Sports Medicine — 5 citations into it
Whom Massimo Sartori trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Frank C. Anderson
- Jonathan Ko
- Thomas S. Buchanan
- David G. Lloyd
- Scott L. Delp
- Marcus G. Pandy
- Dieter Fox
- Thor F. Besier
- Samuel R. Hamner
Papers from Massimo Sartori's perspective
Ordered by how strongly the researchers Massimo Sartori trusts endorse each paper. Same corpus, a different order for every researcher.
- Neuromusculoskeletal modeling: estimation of muscle forces and joint moments and movements from measurements of neural command. (Journal of Applied Biomechanics)
- Static and dynamic optimization solutions for gait are practically equivalent. (Journal of Biomechanics)
- Muscle contributions to propulsion and support during running (Journal of Biomechanics)
- GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
- OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement (IEEE Transactions on Biomedical Engineering)
- A Human--Exoskeleton Interface Utilizing Electromyography (IEEE Transactions on robotics)
- A neural interface provides long-term stable natural touch perception (Science Translational Medicine)
- An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. (Journal of Biomechanics)
- Dynamic optimization of human walking. (Journal of Biomechanical Engineering)
- Generating dynamic simulations of movement using computed muscle control. (Journal of Biomechanics)
Their papers
- Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation (2017) — 311 citations
- CEINMS: a toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks (2015) — 328 citations
- EMG-Driven Forward-Dynamic Estimation of Muscle Force and Joint Moment about Multiple Degrees of Freedom in the Human Lower Extremity (2012) — 320 citations