Marco Ghislieri

Orcid: 0000-0001-7626-1563

Affiliations:
  • Polytechnic University of Turin, Italy


According to our database1, Marco Ghislieri authored at least 13 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Statistical Approach for Functional Reach-to-Grasp Segmentation Using a Single Inertial Measurement Unit.
Sensors, September, 2024

2023
Deep Learning for Real-Time Neural Decoding of Grasp.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

2022
U-Turn Detection during Walking.
Proceedings of the IEEE International Symposium on Medical Measurements and Applications, 2022

Automatic Identification of the Best Auscultation Area for the Estimation of the Time of Closure of Heart Valves through Multi-Source Phonocardiography.
Proceedings of the Computing in Cardiology, 2022

2021
Evaluation of Muscle Function by Means of a Muscle-Specific and a Global Index.
Sensors, 2021

Atypical Gait Cycles in Parkinson's Disease.
Sensors, 2021

An Algorithm for Choosing the Optimal Number of Muscle Synergies during Walking.
Sensors, 2021

Influence of Gait Cycle Normalization on Principal Activations.
Proceedings of the IEEE International Symposium on Medical Measurements and Applications, 2021

The Effect of Number of Gait Cycles on Principal Activation Extraction.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

2020
Methodological issues in the assessment of motor control during single-leg stance.
Proceedings of the 2020 IEEE International Symposium on Medical Measurements and Applications, 2020

2019
Wearable Inertial Sensors to Assess Standing Balance: A Systematic Review.
Sensors, 2019

How to Improve Robustness in Muscle Synergy Extraction.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

2018
Muscle synergies in patients with low back pain : A statistical gait analysis study pre- and post-rehabilitation.
Proceedings of the 2018 IEEE International Symposium on Medical Measurements and Applications, 2018


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