Mario Zappia

Orcid: 0000-0002-8298-9486

According to our database1, Mario Zappia authored at least 13 papers between 2016 and 2023.

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

Timeline

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Bibliography

2023
Machine Learning Approach to Classify Postural Sway Instabilities.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2023

2022
A Comparison among Different Strategies to Detect Potential Unstable Behaviors in Postural Sway.
Sensors, 2022

A Neuro-Fuzzy Approach to Assess Postural Sway.
Proceedings of the IEEE Sensors Applications Symposium, 2022

2021
A Wavelet-Based Methodology for Features Extraction in Postural Instability Analysis.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2021

2020
A Measurement System to Monitor Postural Behavior: Strategy Assessment and Classification Rating.
IEEE Trans. Instrum. Meas., 2020

2019
A sensing platform for postural behavior assessment.
Proceedings of the 5th IEEE International Symposium on Measurements & Networking, 2019

2018
Measurements of Iron Compound Content in the Brain Using a Flexible Core Fluxgate Magnetometer at Room Temperature.
IEEE Trans. Instrum. Meas., 2018

A Wearable Device to Support the Pull Test for Postural Instability Assessment in Parkinson's Disease.
IEEE Trans. Instrum. Meas., 2018

Fluxgate Magnetometer and Performance for Measuring Iron Compounds.
Proceedings of the Sensors, 2018

A pressure measurement for pull test validation in postural instability assessment.
Proceedings of the 2018 IEEE Sensors Applications Symposium, 2018

2017
RTD-fluxgate sensor for measurements of metal compounds in neurodegenerative diseases.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2017

A Wearable Device to Support the Pull Test in Parkinson Disease.
Proceedings of the Ambient Assisted Living, 2017

2016
A multisensor approach to perform instrumented postural instability tests for patient with Parkinson disease.
Proceedings of the IEEE Sensors Applications Symposium, 2016


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