Masoud Abdollahi

Orcid: 0000-0002-8941-0182

According to our database1, Masoud Abdollahi authored at least 12 papers between 2015 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Fall Risk Assessment in Stroke Survivors: A Machine Learning Model Using Detailed Motion Data from Common Clinical Tests and Motor-Cognitive Dual-Tasking.
Sensors, February, 2024

2023
Motor-Cognitive Dual-Task Paradigm Affects Timed Up & Go (TUG) Test Outcomes in Stroke Survivors.
Proceedings of the 11th International IEEE/EMBS Conference on Neural Engineering, 2023

2022
CMIP6-D&A: An R-based software with GUI for processing climate data available in network common data format.
SoftwareX, 2022

Kinematic Analysis of 360° Turning in Stroke Survivors Using Wearable Motion Sensors.
Sensors, 2022

2021
Kinematic Assessment of Turning and Walking Tasks Among Stroke Survivors by Employing Wearable Sensors and Pressure Platform.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

2020
Processing of Near Real Time Land Surface Temperature and Its Application in Forecasting Forest Fire Danger Conditions.
Sensors, 2020

Using a Motion Sensor to Categorize Nonspecific Low Back Pain Patients: A Machine Learning Approach.
Sensors, 2020

2019
Introducing a New Remote Sensing-Based Model for Forecasting Forest Fire Danger Conditions at a Four-Day Scale.
Remote. Sens., 2019

Applicability of Remote Sensing-Based Vegetation Water Content in Modeling Lightning-Caused Forest Fire Occurrences.
ISPRS Int. J. Geo Inf., 2019

2018
An Advanced Forest Fire Danger Forecasting System: Integration of Remote Sensing and Historical Sources of Ignition Data.
Remote. Sens., 2018

2017
A novel approach to spinal 3-D kinematic assessment using inertial sensors: Towards effective quantitative evaluation of low back pain in clinical settings.
Comput. Biol. Medicine, 2017

2015
A Mechanical model for flexible exercise bars to study the influence of the initial position of the bar on lumbar discs and muscles forces.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015


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