Malte Ollenschläger
Malte Ollenschläger, M. Sc.
Malte Ollenschläger’s Research Focus
Wearable sensor systems using inertial measurement units (IMUs) enable objective and ubiquitous gait analysis. Being technically validated and able to report spatio-temporal gait parameters (e.g. stride length, stride time, rotation angles) with a high resolution, they are still not used in clinical practice, for example in geriatrics. Most clinicians use more traditional methods like questionnaires or macro gait parameters such as walked distance within a certain time as measured by stopwatches.
My research focuses on applications of IMU-based gait analysis in geriatric wards to bridge the gap between research and clinical practice. Closing this gap is important because researchers could use the tremendous amount of data that is generated in everyday practice and thus build reliable models and algorithms. Furthermore, closing the gap can accelerate the translation of the developed methods into innovation in medicine.
Since 06/2020 | Research Assistant Molekulare Neurologie Universitätsklinik Erlangen (UKER) |
05/2020 – 11/2020 | Fellow of Catalyst Europe |
Since 01/2018 | Research Assistant and Ph.D. candidate Machine Learning and Data Analytics Lab Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) |
06/2017 – 09/2017 | Research Assistant Softwarelab Universidade do Vale do Rio dos Sinos (Unisinos) São Leopoldo, Brazil |
10/2014 – 10/2016 | M.Sc. in Medical Engineering Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)Master Thesis: “Benchmarking Foot Trajectory Estimation Methods“ |
06/2011 – 01/2013 | Student Assistant Medical Sensors and Devices Laboratory Technische Hochschule Lübeck |
09/2010 – 08/2014 | B.Sc. in Biomedical Engineering Technische Hochschule Lübeck, University of Applied Sciences Bachelor Thesis: “Entwicklung von Algorithmen zur Unterdrückung von Bewegungsartefakten in der Photoplethysmographie“ |
10/2017 | Winner of the Open Research Challenge “IMAGINE” Development of a visualization tool for inertial sensor based gait analysis Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) |
02/2015 | Bookprize Best student of the year award in the faculty of applied science Technische Hochschule Lübeck |
09/2012 – 02/2014 | Deutschlandstipendium Scholarship for excellent academic performance and volunter work Bundesministerium für Bildung und Forschung |
03/2006 | Rudolf-Hellebrandt-Preis In honor of volunteer work Fördergemeinschaft Kinderkrebs-Zentrum Hamburg e.V. |
2024
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
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Which Comprehensive Geriatric Assessment (CGA) instruments are currently used in Germany: a survey
In: BMC Geriatrics 24 (2024), Article No.: 347
ISSN: 1471-2318
DOI: 10.1186/s12877-024-04913-6
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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
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2023
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
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Mobile digital gait analysis objectively measures progression in hereditary spastic paraplegia
In: Annals of Clinical and Translational Neurology 10 (2023)
ISSN: 2328-9503
DOI: 10.1002/acn3.51725
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Automated assessment of foot elevation in adults with hereditary spastic paraplegia using inertial measurements and machine learning
In: Orphanet Journal of Rare Diseases 18 (2023), Article No.: 249
ISSN: 1750-1172
DOI: 10.1186/s13023-023-02854-8
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2022
MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data
In: Sensors 22 (2022)
ISSN: 1424-8220
DOI: 10.3390/s22155849
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Correction to: Wearable gait analysis systems: ready to be used by medical practitioners in geriatric wards? (European Geriatric Medicine, (2022), 10.1007/s41999-022-00629-1)
In: European Geriatric Medicine (2022)
ISSN: 1878-7649
DOI: 10.1007/s41999-022-00646-0
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Wearable gait analysis systems: ready to be used by medical practitioners in geriatric wards?
In: European Geriatric Medicine (2022)
ISSN: 1878-7649
DOI: 10.1007/s41999-022-00629-1
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Inertial Gait Sensors to Measure Mobility and Functioning in Hereditary Spastic Paraplegia A Cross-sectional Multicenter Clinical Study
In: Neurology 99 (2022), p. E1079-E1089
ISSN: 0028-3878
DOI: 10.1212/WNL.0000000000200819
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2021
Improving Dyspnoea Symptom Control of Patients in Palliative Care Using a Smart Patch-A Proof of Concept Study
In: Frontiers in Digital Health 3 (2021)
ISSN: 2673-253X
DOI: 10.3389/fdgth.2021.765867
URL: https://www.frontiersin.org/articles/10.3389/fdgth.2021.765867/full?&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&field=&journalName=Frontiers_in_Digital_Health&id=765867#h6
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2020
Entwicklung einer Applikation zum Home-Monitoring des Gesundheitszustandes von Palliativpatienten - eine Proof-of-Concept-Studie
13. DGP Kongress Deutsche Gesellschaft für Palliativmedizin (Wiesbaden, 9. September 2020 - 12. September 2020)
In: Zeitschrift für Palliativmedizin 2020; 21(05) 2020
DOI: 10.1055/s-0040-1714998
URL: https://www.thieme-connect.com/products/ejournals/abstract/10.1055/s-0040-1714998#info
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2019
Toward analyzing mutual interference on infrared-enabled depth cameras
In: Computer Vision and Image Understanding (2019)
ISSN: 1077-3142
DOI: 10.1016/j.cviu.2018.09.010
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A wearable obstacle detection system for visually impaired people
41st International Engineering in Medicine and Biology Conference (Berlin, 23. July 2019 - 27. July 2019)
In: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2019
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2018
A Survey of Sensors in Healthcare Workflow Monitoring
In: ACM Computing Surveys 51 (2018), Article No.: 42
ISSN: 0360-0300
DOI: 10.1145/3177852
URL: https://dl.acm.org/citation.cfm?id=3177852
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FallRiskPD: Long-term fall risk classification for Parkinson’s disease via intelligent sensor-based gait analysis in the home environment (Talk)
European Falls Festival 2018 (Manchester, 2. July 2018 - 3. July 2018)
In: European Falls Festival, 2nd and 3rd July 2018, Manchester, United Kingdom, ABSTRACT BOOKLET 2018
URL: http://eufallsfest.eu/documents/Abstract Booklet.pdf
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2017
Benchmarking Foot Trajectory Estimation Methods for Mobile Gait Analysis.
In: Sensors 17 (2017)
ISSN: 1424-8220
DOI: 10.3390/s17091940
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2020
- “IMU Data Processing and its Application in Gait Analysis”, Lightning Talks Computer Science, FAU, Erlangen.
- “Ganganalyse bei geriatrischen Patienten mittels mobiler Sensoren”, Sitzung AGAPLESION Arbeitsbereich Geriatrie, Frankfurt am Main.