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Sandra Hellmers

M.Sc. Sandra Hellmers

Leiterin der Gruppe Robotische Assistenzsysteme der Abteilung Assistenzsysteme und Medizintechnik, Department für Versorgungsforschung, Fakultät VI, Medizin und Gesundheitswissenschaften.

Universität Oldenburg
Department für Versorgungsforschung
Abteilung Assistenzsysteme und Medizintechnik
Ammerländer Heerstr. 140 
26129 Oldenburg 

Tel.: +49-(0)441-798-2667
Raum: V04 0-018

Sprechzeiten: nach Vereinbarung 
E-Mail: sand5wlxra.hilt8tellmerrhs@uni-olda4wenb6jprdurg.dgjers

Lehrveranstaltungen:

inf210: Signal- und Bildverarbeitung / inf960: Signals & Dynamical Systems ab WiSe 2020/2021

 

Publikationen

  • [conference] bibtex
    C. Lübbe, B. Friedrich, S. Fudickar, S. Hellmers, und A. Hein, "Feature Based Random Forest Nurse Care Activity Recognition using Accelerometer Data," in Proc. Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers, 2020.
    @conference{nurse,
      author={Lübbe, Carolin and Friedrich, Björn and Fudickar, Sebastian and Hellmers, Sandra and Hein, Andreas},
      title={Feature Based Random Forest Nurse Care Activity Recognition using Accelerometer Data},
      booktitle={Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers},
      year={2020},
      organization={ACM} }
  • R. Diekmann, S. Hellmers, L. Elgert, S. Fudickar, A. Heinks, S. Lau, J. Bauer, T. Zieschang, und A. Hein, "Minimizing comprehensive geriatric assessment to identify deterioration of physical performance in a healthy community-dwelling older cohort: longitudinal data of the AEQUIPA Versa study," Aging clinical and experimental research, 2020.
    @article{diekmann2020minimizing, title={Minimizing comprehensive geriatric assessment to identify deterioration of physical performance in a healthy community-dwelling older cohort: longitudinal data of the AEQUIPA Versa study},
      author={Diekmann, R and Hellmers, S and Elgert, L and Fudickar, S and Heinks, A and Lau, S and Bauer, JM and Zieschang, T and Hein, A},
      journal={Aging clinical and experimental research},
      year={2020},
      publisher={Springer},
      url="https://link.springer.com/article/10.1007/s40520-020-01562-8"
  • [conference] bibtex
    S. Hellmers, L. Peng, S. Lau, R. Diekmann, L. Elgert, J. M. Bauer, A. Hein, und S. Fudickar, "Activity Scores of Older Adults Based on Inertial Measurement Unit Data in Everyday Life," in Proc. Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2020), 2020, pp. 579-585.
    @conference{healthinf20,
      author={Sandra Hellmers and Lianying Peng and Sandra Lau and Rebecca Diekmann and Lena Elgert and Jürgen M. Bauer and Andreas Hein and Sebastian Fudickar},
      title={Activity Scores of Older Adults Based on Inertial Measurement Unit Data in Everyday Life},
      booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2020)},
      year={2020},
      publisher={SciTePress},
      organization={INSTICC},
      pages={579-585},
      sortkey = {10} }
  • S. Fudickar, S. Hellmers, S. Lau, R. Diekmann, J. M. Bauer, und A. Hein, "Measurement System for Unsupervised Standardized Assessment of Timed “Up \& Go” and Five Times Sit to Stand Test in the Community—A Validity Study," Sensors, vol. 20, iss. 10, p. 2824, 2020.
    @article{fudickar2020measurement, title={Measurement System for Unsupervised Standardized Assessment of Timed “Up \& Go” and Five Times Sit to Stand Test in the Community—A Validity Study},
      author={Fudickar, Sebastian and Hellmers, Sandra and Lau, Sandra and Diekmann, Rebecca and Bauer, J{\"u}rgen M and Hein, Andreas},
      journal={Sensors},
      volume={20},
      number={10},
      pages={2824},
      year={2020},
      publisher={Multidisciplinary Digital Publishing Institute},
      url="https://www.mdpi.com/1424-8220/20/10/2824" }
  • C. Lins, D. Eckhoff, A. Klausen, S. Hellmers, A. Hein, und S. Fudickar, "Cardiopulmonary resuscitation quality parameters from motion capture data using Differential Evolution fitting of sinusoids," Applied Soft Computing, 2019.
    @article{LINS2019, title = "Cardiopulmonary resuscitation quality parameters from motion capture data using Differential Evolution fitting of sinusoids", journal = "Applied Soft Computing", year = "2019", issn = "1568-4946", doi = "https://doi.org/10.1016/j.asoc.2019.03.023", url = "http://www.sciencedirect.com/science/article/pii/S1568494619301413",
      author = "Christian Lins and Daniel Eckhoff and Andreas Klausen and Sandra Hellmers and Andreas Hein and Sebastian Fudickar", keywords = "CPR training, Resuscitation, Differential Evolution, Cardiac arrest, Motion capture, Kinect, Sinusoid regression model", abstract = "Cardiopulmonary resuscitation (CPR) is alongside electrical defibrillation the most crucial countermeasure for sudden cardiac arrest, which affects thousands of individuals every year. In this paper, we present a novel approach including sinusoid models that use skeletal motion data from an RGB-D (Kinect) sensor and the Differential Evolution (DE) optimization algorithm to dynamically fit sinusoidal curves to derive frequency and depth parameters for cardiopulmonary resuscitation training. It is intended to be part of a robust and easy-to-use feedback system for CPR training, allowing its use for unsupervised training. The accuracy of this DE-based approach is evaluated in comparison with data of 28 participants recorded by a state-of-the-art training mannequin. We optimized the DE algorithm hyperparameters and showed that with these optimized parameters the frequency of the CPR is recognized with a median error of ±2.9 compressions per minute compared to the reference training mannequin." }
  • S. Hellmers, S. Fudickar, S. Lau, L. Elgert, R. Diekmann, J. M. Bauer, und A. Hein, "Measurement of the Chair Rise Performance of Older People Based on Force Plates and IMUs," Sensors, vol. 19, iss. 6, 2019.
    @article{Hellmers2019, abstract = {An early detection of functional decline with age is important to start interventions at an early state and to prolong the functional fitness. In order to assure such an early detection, functional assessments must be conducted on a frequent and regular basis. Since the five time chair rise test (5CRT) is a well-established test in the geriatric field, this test should be supported by technology. We introduce an approach that automatically detects the execution of the chair rise test via an inertial sensor integrated into a belt. The system{\&}rsquo;s suitability was evaluated via 20 subjects aged 72{\&}ndash;89 years (78.2 {\&}plusmn; 4.6 years) and was measured by a stopwatch, the inertial measurement unit (IMU), a Kinect{\&}reg; camera and a force plate. A Multilayer Perceptrons-based classifier detects transitions in the IMU data with an F1-Score of around 94.8{\%}. Valid executions of the 5CRT are detected based on the correct occurrence of sequential movements via a rule-based model. The results of the automatically calculated test durations are in good agreement with the stopwatch measurements (correlation coefficient r = 0.93 (p {\textless} 0.001)). The analysis of the duration of single test cycles indicates a beginning fatigue at the end of the test. The comparison of the movement pattern within one person shows similar movement patterns, which differ only slightly in form and duration, whereby different subjects indicate variations regarding their performance strategies.},
      author = {Hellmers, Sandra and Fudickar, Sebastian and Lau, Sandra and Elgert, Lena and Diekmann, Rebecca and Bauer, J{\"{u}}rgen M and Hein, Andreas},
      doi = {10.3390/s19061370},
      issn = {1424-8220},
      journal = {Sensors},
      number = {6},
      title = {{Measurement of the Chair Rise Performance of Older People Based on Force Plates and IMUs}},
      url = {http://www.mdpi.com/1424-8220/19/6/1370},
      volume = {19},
      year = {2019},
      sortkey = {08} }
  • [inproceedings] bibtex | Dokument aufrufen Dokument aufrufen
    S. Hellmers, S. Lau, R. Diekmann, L. Dasenbrock, T. Kromke, J. M. Bauer, S. Fudickar, und A. Hein, "Evaluation of Power-Based Stair Climb Performance via Inertial Measurement Units," in Proc. Biomedical Engineering Systems and Technologies, Cham, 2019, pp. 238-261.
    @InProceedings{SpringerStair,
      author="Hellmers, Sandra and Lau, Sandra and Diekmann, Rebecca and Dasenbrock, Lena and Kromke, Tobias and Bauer, J{\"u}rgen M. and Fudickar, Sebastian and Hein, Andreas", editor="Cliquet Jr., Alberto and Wiebe, Sheldon and Anderson, Paul and Saggio, Giovanni and Zwiggelaar, Reyer and Gamboa, Hugo and Fred, Ana and Berm{\'u}dez i Badia, Sergi", title="Evaluation of Power-Based Stair Climb Performance via Inertial Measurement Units", booktitle="Biomedical Engineering Systems and Technologies", year="2019", publisher="Springer International Publishing", address="Cham", pages="238--261", abstract="The stair climbing test (SCT) is a standard geriatric assessment to measure lower-limb strength being one of the essential components of physical function. To detect functional decline as early as possible, regular assessments of mobility, balance, and strength are necessary. Inertial measurement units (IMU) are a promising technology for flexible and unobtrusive measurements of the SCTs. We introduce an automated assessment via IMUs in a study of 83 participants aged 70--87 (75.64 {\textpm} 4,17) years. The activity of stair ascending has been automatically classified via a k-nearest-neighbor classifier and the performance was evaluated regarding the power. Therefore, we considered both, stair climb average power and peak power. Stair ascending was correctly classified in 93{\%} of the cases with a mean deviation of 2.35{\%} of the average power value in comparison to conventional measurements. Additionally, we showed the medical sensitivity of our system regarding the detection of transitions towards the frail status in controlled conditions and also confirmed the general suitability of automated stair climb analyses in unsupervised home-assessments.", isbn="978-3-030-29196-9", url="https://link.springer.com/chapter/10.1007/978-3-030-29196-9_13" }
  • [conference] bibtex
    C. Lins, A. Klausen, S. Fudickar, S. Hellmers, M. Lipprandt, R. Röhrig, und A. Hein, "Determining Cardiopulmonary Resuscitation Parameters with Differential Evolution Optimization of Sinusoidal Curves," in Proc. Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: AI4Health,, 2018, pp. 665-670.
    @conference{ai4health18,
      author={Christian Lins and Andreas Klausen and Sebastian Fudickar and Sandra Hellmers and Myriam Lipprandt and Rainer Röhrig and Andreas Hein},
      title={Determining Cardiopulmonary Resuscitation Parameters with Differential Evolution Optimization of Sinusoidal Curves},
      booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: AI4Health,},
      year={2018},
      pages={665-670},
      publisher={SciTePress},
      organization={INSTICC},
      doi={10.5220/0006732806650670},
      isbn={978-989-758-281-3} }
  • [inproceedings] bibtex | Dokument aufrufen Dokument aufrufen
    S. Hellmers, S. Fudickar, L. Dasenbrock, A. Heinks, J. M. Bauer, und A. Hein, "A Model-Based Approach for Jump Analyses Regarding Strength and Balance," in Proc. Biomedical Engineering Systems and Technologies, Cham, 2018, pp. 354-375.
    @InProceedings{SpringerJump,
      author="Hellmers, Sandra and Fudickar, Sebastian and Dasenbrock, Lena and Heinks, Andrea and Bauer, J{\"u}rgen M. and Hein, Andreas", editor="Peixoto, Nathalia and Silveira, Margarida and Ali, Hesham H. and Maciel, Carlos and van den Broek, Egon L.", title="A Model-Based Approach for Jump Analyses Regarding Strength and Balance", booktitle="Biomedical Engineering Systems and Technologies", year="2018", publisher="Springer International Publishing", address="Cham", pages="354--375", isbn="978-3-319-94806-5", url="https://www.springerprofessional.de/a-model-based-approach-for-jump-analyses-regarding-strength-and-/15901736" }
  • S. Hellmers., T. Kromke., L. D. ., A. Heinks., J. M. Bauer., A. Hein., und S. Fudickar., "Stair Climb Power Measurements via Inertial Measurement Units - Towards an Unsupervised Assessment of Strength in Domestic Environments," in Proc. Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, 2018, pp. 39-47.
    @conference{healthinf18,
      author={Sandra Hellmers. and Tobias Kromke. and Lena Dasenbrock . and Andrea Heinks. and Jürgen M. Bauer. and Andreas Hein. and Sebastian Fudickar.},
      title={Stair Climb Power Measurements via Inertial Measurement Units - Towards an Unsupervised Assessment of Strength in Domestic Environments},
      booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF},
      year={2018},
      pages={39-47},
      publisher={SciTePress},
      organization={INSTICC},
      doi={10.5220/0006543900390047},
      isbn={978-989-758-281-3},
      sortkey = {05},
      url="https://www.scitepress.org/papers/2018/65439/65439.pdf" }
  • S. Hellmers, B. Izadpanah, L. Dasenbrock, R. Diekmann, J. M. Bauer, A. Hein, und S. Fudickar, "Towards an Automated Unsupervised Mobility Assessment for Older People Based on Inertial TUG Measurements," Sensors, vol. 18, iss. 10, 2018.
    @article{Hellmers2018, abstract = {One of the most common assessments for the mobility of older people is the Timed Up and Go test (TUG). Due to its sensitivity regarding the indication of Parkinson's disease (PD) or increased fall risk in elderly people, this assessment test becomes increasingly relevant, should be automated and should become applicable for unsupervised self-assessments to enable regular examinations of the functional status. With Inertial Measurement Units (IMU) being well suited for automated analyses, we evaluate an IMU-based analysis-system, which automatically detects the TUG execution via machine learning and calculates the test duration. as well as the duration of its single components. The complete TUG was classified with an accuracy of 96{\%} via a rule-based model in a study with 157 participants aged over 70 years. A comparison between the TUG durations determined by IMU and criterion standard measurements (stopwatch and automated/ambient TUG (aTUG) system) showed significant correlations of 0.97 and 0.99, respectively. The classification of the instrumented TUG (iTUG)-components achieved accuracies over 96{\%},
      as well. Additionally, the system's suitability for self-assessments was investigated within a semi-unsupervised situation where a similar movement sequence to the TUG was executed. This preliminary analysis confirmed that the self-selected speed correlates moderately with the speed in the test situation, but differed significantly from each other.},
      author = {Hellmers, Sandra and Izadpanah, Babak and Dasenbrock, Lena and Diekmann, Rebecca and Bauer, J{\"{u}}rgen M and Hein, Andreas and Fudickar, Sebastian},
      doi = {10.3390/s18103310},
      file = {::},
      issn = {1424-8220},
      journal = {Sensors},
      number = {10},
      title = {{Towards an Automated Unsupervised Mobility Assessment for Older People Based on Inertial TUG Measurements}},
      url = {http://www.mdpi.com/1424-8220/18/10/3310},
      volume = {18},
      year = {2018},
      sortkey = {06} }
  • [incollection] bibtex | Dokument aufrufen Dokument aufrufen
    S. Hellmers, S. Fudickar, C. Büse, L. Dasenbrock, A. Heinks, J. M. Bauer, und A. Hein, "Technology supported geriatric assessment," in Ambient Assisted Living, Springer, 2017, pp. 85-100.
    @incollection{hellmers2017technology, title={Technology supported geriatric assessment},
      author={Hellmers, Sandra and Fudickar, Sebastian and B{\"u}se, Clemens and Dasenbrock, Lena and Heinks, Andrea and Bauer, J{\"u}rgen M and Hein, Andreas},
      booktitle={Ambient Assisted Living},
      pages={85--100},
      year={2017},
      publisher={Springer},
      url="https://link.springer.com/chapter/10.1007/978-3-319-52322-4_6" }
  • S. Hellmers, S. Fudickar, L. Dasenbrock, A. Heinks, J. M. Bauer, und A. Hein, "Understanding Jump Landing as an Oscillating System: A Model-based Approach of Balance and Strength Analyses," in Proc. Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017), 2017, pp. 159-168.
    @conference{healthinf17,
      author={Sandra Hellmers and Sebastian Fudickar and Lena Dasenbrock and Andrea Heinks and Jürgen M. Bauer and Andreas Hein},
      title={Understanding Jump Landing as an Oscillating System: A Model-based Approach of Balance and Strength Analyses},
      booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017)},
      year={2017},
      pages={159-168},
      publisher={SciTePress},
      organization={INSTICC},
      doi={10.5220/0006171101590168},
      isbn={978-989-758-213-4},
      url="https://www.scitepress.org/Papers/2017/61711/pdf/index.html" }
  • [inproceedings] bibtex | Dokument aufrufen Dokument aufrufen
    S. Hellmers, E. Steen, L. Dasenbrock, A. Heinks, J. M. Bauer, S. Fudickar, und A. Hein, "Towards a Minimized Unsupervised Technical Assessment of Physical Performance in Domestic Environments," in Proc. Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare, New York, NY, USA, 2017, pp. 207-216.
    @inproceedings{HellmersPH17,
      author = {Hellmers, Sandra and Steen, Enno-Edzard and Dasenbrock, Lena and Heinks, Andrea and Bauer, J\"{u}rgen M. and Fudickar, Sebastian and Hein, Andreas},
      title = {Towards a Minimized Unsupervised Technical Assessment of Physical Performance in Domestic Environments},
      booktitle = {Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare},
      series = {PervasiveHealth '17},
      year = {2017},
      isbn = {978-1-4503-6363-1},
      location = {Barcelona, Spain},
      pages = {207--216},
      numpages = {10},
      url = {http://doi.acm.org/10.1145/3154862.3154882},
      doi = {10.1145/3154862.3154882},
      acmid = {3154882},
      publisher = {ACM},
      address = {New York, NY, USA},
      keywords = {ambient sensors, domestic environment, factor analysis, functional decline, home assessment, home monitoring, technical assessment, walking speed},
      sortkey = {03} }
  • [inproceedings] bibtex | Dokument aufrufen Dokument aufrufen
    S. Hellmers, S. Fudickar, E. Lange, C. Lins, und A. Hein, "Validation of a Motion Capture Suit for Clinical Gait Analysis," in Proc. Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare, New York, NY, USA, 2017, pp. 120-126.
    @inproceedings{HellmersPHMotion,
      author = {Hellmers, Sandra and Fudickar, Sebastian and Lange, Eugen and Lins, Christian and Hein, Andreas},
      title = {Validation of a Motion Capture Suit for Clinical Gait Analysis},
      booktitle = {Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare},
      series = {PervasiveHealth '17},
      year = {2017},
      isbn = {978-1-4503-6363-1},
      location = {Barcelona, Spain},
      pages = {120--126},
      numpages = {7},
      url = {http://doi.acm.org/10.1145/3154862.3154884},
      doi = {10.1145/3154862.3154884},
      acmid = {3154884},
      publisher = {ACM},
      address = {New York, NY, USA},
      keywords = {IMU, gait analysis, joint angles, joint coordinate system, low-cost, motion capture, validation},
      sortkey = {04} }
  • [inproceedings] bibtex
    L. Dasenbrock, A. Heinks, S. Hellmers, L. Böhmer, B. Sahlmann, S. Fudickar, A. Hein, und J. M. Bauer, "Sarkopenie und Muskelpower bei selbständig lebenden Senioren – Erste Ergebnisse der Versa Studie," in Proc. Zeitschrift für Gerontologie und Geriatrie, 2016, p. 121.
    @inproceedings{Lena, title={Sarkopenie und Muskelpower bei selbständig lebenden Senioren – Erste Ergebnisse der Versa Studie},
      author={Dasenbrock, Lena and Heinks, Andrea and Hellmers, Sandra and Böhmer, Linda and Sahlmann, Bianca and Fudickar, Sebastian and Hein, Andreas and Bauer, Jürgen M.},
      booktitle={Zeitschrift für Gerontologie und Geriatrie},
      volume={49},
      pages={121},
      year={2016},
      sortkey = {10} }
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