Alzhraa Ahmed
Alzhraa Ahmed, M. Sc.
Department Artificial Intelligence in Biomedical Engineering (AIBE)
Lehrstuhl für Maschinelles Lernen und Datenanalytik
Carl-Thiersch-Straße 2b
91052 Erlangen
- Phone number: +49 9131 85-20287
- Email: alzhraa.ahmed@fau.de
Research Focus
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system that is most common in young adulthood resulting in different gait disorders. My research focuses on identifying biomarkers in the form of gait characteristics in patients with multiple sclerosis. Patients are equipped with inertial measurement units (IMU) from which objective spatio-temporal gait parameters can be obtained and analyzed. This can be used both for the assessment of the current state of the disease and for the prediction of the further course of the disease in the form of relapses. Furthermore, this could significantly slow down the course of the disease and possibly delay the accompanying mobility impairment over a very long period of time.
| since 10/2019 | PhD Candidate Machine Learning and Data Analytics Lab, Department of Computer Science Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) |
| 04/2014 – 10/2017 | M.Sc. in Computer Science Assiut University-Egypt Master’s Thesis: “Human Activity Recognition from RGB-D videos” |
| 09/2007 – 06/2011 | B.Sc. in Computer Science Assiut University-Egypt Bachelor’s Thesis: “Content based Image Retrieval (CBIR)” |
2024
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Mobile digital gait analysis captures effects of botulinum toxin in hereditary spastic paraplegia
In: European Journal of Neurology (2024)
ISSN: 1351-5101
DOI: 10.1111/ene.16367
BibTeX: Download - , , , , , , , , , , , , , :
Gaitmap – An Open Ecosystem for IMU-based Human Gait Analysis and Algorithm Benchmarking
In: IEEE Open Journal of Engineering in Medicine and Biology (2024), p. 1-10
DOI: 10.1109/OJEMB.2024.3356791
BibTeX: Download
2023
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Association between cognition and gait in multiple sclerosis: A smartphone-based longitudinal analysis
In: International Journal of Medical Informatics 177 (2023), Article No.: 105145
ISSN: 1386-5056
DOI: 10.1016/j.ijmedinf.2023.105145
BibTeX: Download - , , , , , , , , , :
Inertial sensor acquired foot elevation parameters validated by Motion capture in a cohort of patients with Hereditary Spastic Paraplegias
In: Gait & Posture 100 (2023), p. 79-80
ISSN: 0966-6362
DOI: 10.1016/j.gaitpost.2022.11.071
BibTeX: Download - , , , :
Machine-learning-based models versus design-oriented models for predicting the axial compressive load of FRP-confined rectangular RC columns
In: Engineering Structures 285 (2023), Article No.: 116030
ISSN: 0141-0296
DOI: 10.1016/j.engstruct.2023.116030
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2022
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Short inertial sensor-based gait tests reflect perceived state fatigue in multiple sclerosis
In: Multiple Sclerosis and Related Disorders 58 (2022), Article No.: 103519
ISSN: 2211-0348
DOI: 10.1016/j.msard.2022.103519
BibTeX: Download - , , , , , , , , , , , , , , :
AB1528-HPR FULL BODY HAPTIC BODYSUIT - AN INSTRUMENT TO MEASURE THE RANGE AND SPEED OF MOTION IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS (axSpA) - PRELIMINARY RESULTS
In: Annals of the Rheumatic Diseases 81 (2022), p. 1866.2-1867
ISSN: 0003-4967
DOI: 10.1136/annrheumdis-2022-eular.3069
BibTeX: Download
2020
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Inertial sensor-based gait parameters reflect patient-reported fatigue in multiple sclerosis
In: Journal of neuroEngineering and rehabilitation 17 (2020), Article No.: 165
ISSN: 1743-0003
DOI: 10.1186/s12984-020-00798-9
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- 09/2019 – Present: Postgraduate Scholarship at PhD Level from Egyptian Mission Sector