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Publikationen

  • L. C. Büker, F. Zuber, A. Hein, und S. Fudickar, "HRDepthNet: Depth Image-Based Marker-Less Tracking of Body Joints" Sensors, vol. 21, iss. 4, 2021.
    @Article{Bueker2021,
      author = {Büker, Linda Christin and Zuber, Finnja and Hein, Andreas and Fudickar, Sebastian},
      TITLE = {HRDepthNet: Depth Image-Based Marker-Less Tracking of Body Joints},
      JOURNAL = {Sensors},
      VOLUME = {21},
      YEAR = {2021},
      NUMBER = {4},
      ARTICLE-NUMBER = {1356},
      URL = {https://www.mdpi.com/1424-8220/21/4/1356},
      ISSN = {1424-8220},
      ABSTRACT = {With approaches for the detection of joint positions in color images such as HRNet and OpenPose being available, consideration of corresponding approaches for depth images is limited even though depth images have several advantages over color images like robustness to light variation or color- and texture invariance. Correspondingly, we introduce High- Resolution Depth Net (HRDepthNet)—a machine learning driven approach to detect human joints (body, head, and upper and lower extremities) in purely depth images. HRDepthNet retrains the original HRNet for depth images. Therefore, a dataset is created holding depth (and RGB) images recorded with subjects conducting the timed up and go test—an established geriatric assessment. The images were manually annotated RGB images. The training and evaluation were conducted with this dataset. For accuracy evaluation, detection of body joints was evaluated via COCO’s evaluation metrics and indicated that the resulting depth image-based model achieved better results than the HRNet trained and applied on corresponding RGB images. An additional evaluation of the position errors showed a median deviation of 1.619 cm (x-axis), 2.342 cm (y-axis) and 2.4 cm (z-axis).},
      DOI = {10.3390/s21041356} }
  • C. Lins, S. Fudickar, und A. Hein, "OWAS inter-rater reliability" Applied Ergonomics, vol. 93, p. 103357, 2021.
    @article{LINS2021, title = "OWAS inter-rater reliability", journal = "Applied Ergonomics", volume = "93", pages = "103357", year = "2021", issn = "0003-6870", doi = "https://doi.org/10.1016/j.apergo.2021.103357", url = "http://www.sciencedirect.com/science/article/pii/S0003687021000041",
      author = "Christian Lins and Sebastian Fudickar and Andreas Hein", keywords = "OWAS, Working postures, Risk assessment, Reliability analysis", abstract = "The Ovako Working posture Assessment System (OWAS) is a commonly used observational assessment method for determining the risk of work-related musculoskeletal disorders. OWAS claims to be suitable in the application for untrained persons but there is not enough evidence for this assumption. In this paper, inter-rater (inter-observer) reliability (agreement) is examined down to the level of individual postures and categories. For this purpose, the postures of 20 volunteers have been observed by 3 varying human raters in a laboratory setting and the inter-rater agreement against reference values was determined. A high agreement of over 98% (κ=0.98) was found for the postures of the arms but lower agreements were found for posture classification of the legs (66−97%,κ=0.85) and the upper body (80−96%,κ=0.85). No significant difference was found between raters with and without intense prior training in physical therapy. Consequently, the results confirm the general reliability of the OWAS method especially for raters with non-specialized background but suggests weaknesses in the reliable detection of a few particular postures." }
  • S. Fudickar, J. Kiselev, C. Stolle, T. Frenken, E. Steinhagen-Thiessen, S. Wegel, und A. Hein, "Validation of a Laser Ranged Scanner-Based Detection of Spatio-Temporal Gait Parameters Using the aTUG Chair" Sensors, vol. 21, iss. 4, 2021.
    @Article{SFu2021,
      author = {Fudickar, Sebastian and Kiselev, Jörn and Stolle, Christian and Frenken, Thomas and Steinhagen-Thiessen, Elisabeth and Wegel, Sandra and Hein, Andreas},
      TITLE = {Validation of a Laser Ranged Scanner-Based Detection of Spatio-Temporal Gait Parameters Using the aTUG Chair},
      JOURNAL = {Sensors},
      VOLUME = {21},
      YEAR = {2021},
      NUMBER = {4},
      ARTICLE-NUMBER = {1343},
      URL = {https://www.mdpi.com/1424-8220/21/4/1343},
      ISSN = {1424-8220},
      ABSTRACT = {This article covers the suitability to measure gait-parameters via a Laser Range Scanner (LRS) that was placed below a chair during the walking phase of the Timed Up&Go Test in a cohort of 92 older adults (mean age 73.5). The results of our study demonstrated a high concordance of gait measurements using a LRS in comparison to the reference GAITRite walkway. Most of aTUG’s gait parameters demonstrate a strong correlation coefficient with the GAITRite, indicating high measurement accuracy for the spatial gait parameters. Measurements of velocity had a correlation coefficient of 99%, which can be interpreted as an excellent measurement accuracy. Cadence showed a slightly lower correlation coefficient of 96%, which is still an exceptionally good result, while step length demonstrated a correlation coefficient of 98% per leg and stride length with an accuracy of 99% per leg. In addition to confirming the technical validation of the aTUG regarding its ability to measure gait parameters, we compared results from the GAITRite and the aTUG for several parameters (cadence, velocity, and step length) with results from the Berg Balance Scale (BBS) and the Activities-Specific Balance Confidence-(ABC)-Scale assessments. With confidence coefficients for BBS and velocity, cadence and step length ranging from 0.595 to 0.798 and for ABC ranging from 0.395 to 0.541, both scales demonstrated only a medium-sized correlation. Thus, we found an association of better walking ability (represented by the measured gait parameters) with better balance (BBC) and balance confidence (ABC) overall scores via linear regression. This results from the fact that the BBS incorporates both static and dynamic balance measures and thus, only partly reflects functional requirements for walking. For the ABC score, this effect was even more pronounced. As this is to our best knowledge the first evaluation of the association between gait parameters and these balance scores, we will further investigate this phenomenon and aim to integrate further measures into the aTUG to achieve an increased sensitivity for balance ability.},
      DOI = {10.3390/s21041343} }
  • R. Diekmann, S. Hellmers, L. Elgert, S. Fudickar, A. Heinks, S. Lau, J. M. 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{Diekmann2020, abstract = {It is important to identify the relevant parameters of physical performance to prevent early functional decline and to prolong independent living. The aim of this study is to describe the development of physical performance in a healthy community-dwelling older cohort aged 70+ years using comprehensive assessment over two years and to subsequently identify the most relevant predictive tests for physical decline to minimize assessment. Physical performance was measured by comprehensive geriatric assessment. Predictors for the individual decline of physical performance by Principal Component and k-means Cluster Analysis were developed, and sensitivity and specificity determined accordingly. 251 subjects ({\O} 75.4 years) participated in the study. Handgrip strength was low in 21.1{\%}. The follow-up results of tests were divergent. Handgrip strength [− 16.95 (SD 11.55)] and the stair climb power test (power) [− 9.15 (SD 16.84)] yielded the highest percentage changes. Four most relevant tests (handgrip strength, stair climb power time, timed up {\&} go and 4-m gait speed) were identified. A predictor based on baseline data was determined (sensitivity 82{\%},
      specificity 96{\%}) to identify subjects characterized by a high degree of physical decline within two years. Although the cohort of older adults is heterogeneous, most of the individuals in the study exhibited high levels of physical performance; only a few subjects suffered a relevant decline within the 2-year follow-up. Four most relevant tests were identified to predict relevant decline of physical function. In spite of ceiling effects of the geriatric assessment in high-performers, we assume that it is possible to predict an individual's risk of physical decline within 2 years with four tests of a comprehensive geriatric assessment.},
      author = {Diekmann, R. and Hellmers, S. and Elgert, L. and Fudickar, S. and Heinks, A. and Lau, S. and Bauer, J. M. and Zieschang, T. and Hein, A.},
      doi = {10.1007/s40520-020-01562-8},
      issn = {17208319},
      journal = {Aging Clinical and Experimental Research},
      pmid = {32358730},
      publisher = {Springer International Publishing},
      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}},
      year = {2020},
      url = {https://doi.org/10.1007/s40520-020-01562-8} }
  • S. Fudickar, R. Kappes, M. Horstmann, M. Isken, und A. Hein, "Cycling Monitoring System - Sensing Cycling Performance via a Pedal-Integrated IMU" Nanomaterials and Energy, vol. 9, iss. 1, pp. 1-6, 2020.
    @article{Fudickar2020, abstract = {With increasing accident rates for elderly cyclists when using electrically powered bicycles, behavioural models for cyclists that consider the underlying functional and cognitive processes are required. Such models must be generated based on experiments conducted in realistic driving conditions, since laboratory studies can cover the complex influences of cycling only to a limited degree. Consequently, this paper introduces a bicycle-monitoring system that was designed to capture all relevant external and internal states to be considered for the conduction of driving behavioural studies in realistic (uncontrolled) environments. Furthermore, algorithms for detecting the turning behaviour and the pedalling frequency by way of a pedal-integrated inertial measurement unit are introduced, and their sensitivity is evaluated in a pilot study.},
      author = {Fudickar, Sebastian and Kappes, Raphael and Horstmann, Marten and Isken, Melvin and Hein, Andreas},
      doi = {10.1680/jnaen.19.00024},
      issn = {2045-9831},
      journal = {Nanomaterials and Energy},
      keywords = {processing,sensors,system},
      number = {1},
      pages = {1--6},
      title = {{Cycling Monitoring System - Sensing Cycling Performance via a Pedal-Integrated IMU}},
      volume = {9},
      year = {2020},
      url = {https://doi.org/10.1680/jnaen.19.00024} }
  • A. Brinkmann, C. Fifelski, S. Lau, C. Kowalski, O. Meyer, R. Diekmann, M. Isken, S. Fudickar, und A. Hein, "The AAL/Care Laboratory – A Healthcare Prevention System for Caregivers" Nanomaterials and Energy, vol. 9, iss. 1, pp. 1-10, 2020.
    @article{Brinkmann2020, abstract = {The demographic change in Europe causes an imbalance between the potential recipients and providers of the services of healthcare systems. Additionally, the high number of sick leaves and days of inability to work in the profession of elderly care are worsening this situation. Manual patient handling is one of the risk factors and leads to high mechanical stress in the lower back. Understanding how physically demanding activities impact caregivers requires quantification of the potential risk factors. In a laboratory, transfer techniques, ambient assisted living (AAL) systems and tools for analysing the physical burden of caregiving are evaluated. A case study was conducted in a laboratory setting to examine the kinematics, kinetics and muscle activities of a caregiver in different regions of the lower extremity and spine during a standardised manual patient-transfer task. Results showed that with the effect of an ergonomic way of caregiving, the mean muscle activity of the lumbar erector spinae was reduced by 42{\%}. The aim of this exploratory trial was to test the methods for use on a larger scale in future studies. The case study demonstrates the suitability of the utilised sensors for the quantification of musculoskeletal burden among healthcare workers.},
      author = {Brinkmann, Anna and Fifelski, Conrad and Lau, Sandra and Kowalski, Christian and Meyer, Ole and Diekmann, Rebecca and Isken, Melvin and Fudickar, Sebastian and Hein, Andreas},
      doi = {10.1680/jnaen.19.00021},
      file = {:Volumes/Data/UniSync/Paper/Mendeley/2020 - The AALCare Laboratory – A Healthcare Prevention System for Caregivers.pdf:pdf},
      issn = {2045-9831},
      journal = {Nanomaterials and Energy},
      keywords = {biological,medical physics},
      number = {1},
      pages = {1--10},
      title = {{The AAL/Care Laboratory – A Healthcare Prevention System for Caregivers}},
      url = {https://doi.org/10.1680/jnaen.19.00021},
      volume = {9},
      year = {2020} }
  • 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{Fudickar2020a, abstract = {Comprehensive and repetitive assessments are needed to detect physical changes in an older population to prevent functional decline at the earliest possible stage and to initiate preventive interventions. Established instruments like the Timed “Up {\&} Go” (TUG) Test and the Sit-to-Stand Test (SST) require a trained person (e.g., physiotherapist) to assess physical performance. More often, these tests are only applied to a selected group of persons already functionally impaired and not to those who are at potential risk of functional decline. The article introduces the Unsupervised Screening System (USS) for unsupervised self-assessments by older adults and evaluates its validity for the TUG and SST. The USS included ambient and wearable movement sensors to measure the user's test performance. Sensor datasets of the USS's light barriers and Inertial Measurement Units (IMU) were analyzed for 91 users aged 73 to 89 years compared to conventional stopwatch measurement. A significant correlation coefficient of 0.89 for the TUG test and of 0.73 for the SST were confirmed among USS's light barriers. Correspondingly, for the inertial data-based measures, a high and significant correlation of 0.78 for the TUG test and of 0.87 for SST were also found. The USS was a validated and reliable tool to assess TUG and SST.},
      author = {Fudickar, Sebastian and Hellmers, Sandra and Lau, Sandra and Diekmann, Rebecca and Bauer, J{\"{u}}rgen M. and Hein, Andreas},
      doi = {10.3390/s20102824},
      issn = {14248220},
      journal = {Sensors},
      keywords = {5xsst,assessment,evaluation,five times sit-to-stand test,functional,go,inertial,machine learning,measurement units,system usability,technology,test,timed,tug,unsupervised,up,validity analysis},
      number = {10},
      pages = {2824},
      pmid = {32429306},
      title = {{Measurement System for Unsupervised Standardized Assessment of Timed “Up {\&} Go” and Five Times Sit to Stand Test in the Community—A Validity Study}},
      volume = {20},
      year = {2020},
      url = {https://doi.org/10.3390/s20102824} }
  • 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." }
  • B. Friedrich, B. Cauchi, A. Hein, und S. Fudickar, "Transportation mode classification from smartphone sensors via a long-short-term-memory network" UbiComp/ISWC 2019- - Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers, pp. 709-713, 2019.
    @article{Friedrich2019, abstract = {This article introduce the architecture of a Long-Short-Term-Memory network for classifying transportation-modes via smartphone data and evaluates its accuracy. By using a Long-Short-Term-Memory with common preprocessing steps such as normalisation for classification tasks an F1-Score accuracy of 63.68 {\%} was achieved with an internal test dataset. We participated as team "GanbareAMT" in the “SHL recognition challenge".},
      author = {Friedrich, Bj{\"{o}}rn and Cauchi, Benjamin and Hein, Andreas and Fudickar, Sebastian},
      doi = {10.1145/3341162.3344855},
      isbn = {9781450368698},
      journal = {UbiComp/ISWC 2019- - Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers},
      keywords = {Classification,IMU,Inertial,LSTM,Mode of Transportation,Phones,Supervised Machine Learning},
      pages = {709--713},
      title = {{Transportation mode classification from smartphone sensors via a long-short-term-memory network}},
      year = {2019},
      url = {https://doi.org/10.1145/3341162.3344855} }
  • J. Bornhorst, E. Nustede, und S. Fudickar, "Mass Surveilance of C. elegans - Smartphone-Based DIY Microscope and Machine-Learning-Based Approach for Worm Detection" Sensors, vol. 19, iss. 6, p. 1468, 2019.
    @article{Bornhorst_2019, doi = {10.3390/s19061468},
      url = {https://doi.org/10.3390%2Fs19061468},
      year = 2019, month = {mar},
      publisher = {{MDPI} {AG}},
      volume = {19},
      number = {6},
      pages = {1468},
      author = {Bornhorst, Julia and Nustede, Eike and Fudickar, Sebastian },
      title = {Mass Surveilance of C. elegans - Smartphone-Based {DIY} Microscope and Machine-Learning-Based Approach for Worm Detection},
      journal = {Sensors} }
  • 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, p. 1370, 2019.
    @Article{Hellmers2019,
      author = {Hellmers, Sandra and Fudickar, Sebastian and Lau, Sandra and Elgert, Lena and Diekmann, Rebecca and Bauer, Jürgen M. and Hein, Andreas},
      TITLE = {Measurement of the Chair Rise Performance of Older People Based on Force Plates and IMUs},
      JOURNAL = {Sensors},
      VOLUME = {19},
      YEAR = {2019},
      NUMBER = {6},
      pages = {1370},
      URL = {http://www.mdpi.com/1424-8220/19/6/1370},
      ISSN = {1424-8220},
      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’s suitability was evaluated via 20 subjects aged 72–89 years (78.2 ± 4.6 years) and was measured by a stopwatch, the inertial measurement unit (IMU), a Kinect® 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 < 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.},
      DOI = {10.3390/s19061370} }
  • B. Löffler, H. I. Stecher, S. Fudickar, D. de Sordi, F. Otto-Sobotka, A. Hein, und C. Herrmann, "Counteracting the Slowdown of Reaction Times in a Vigilance Experiment with 40-Hz Transcranial Alternating Current Stimulation" IEEE - Transactions on Neural Systems & Rehabilitation Engineering, 2018.
    @article{ALofflerBSStecherHIFudickarSdeSordiDOtto-SobotkaFHeinA2018, abstract = {Indicators for a decrement in vigilance are a slowdown in reaction times and an increase in alpha power in the electroencephalogram (EEG) in posterior regions of the brain. Transcranial alternating current stimulation (tACS) is a neuropsychological technique that has been found to interact with intrinsic brain oscillations and is able to enhance cognitive and behavioral performance. Recent studies showed that tACS in the gamma frequency range (30-80 Hz) is able to downregulate amplitudes in the alpha frequency range (8-12 Hz), in accordance to the effect referred to as cross-frequency coupling, where intrinsic alpha and gamma waves modulate each other. We applied 40 Hz gamma-tACS to the visual cortex during a vigilance experiment and investigated if stimulation improves reaction times and error rates with time-on-task. In our sham controlled experiment, participants completed two blocks of 30 minutes duration while performing the same visual two-choice task. The first block was used as BASELINE. A statistical analysis with a linear mixed model (LMM) revealed a significantly lower increase of modeled reaction times over time in the INTERVENTION-block of the tACS-group as compared to their BASELINE-block whereas there was no significant change between the BASELINE- and INTERVENTION-block for the SHAM-group. Error rates did not differ between groups. This study indicates that gamma-tACS can enhance performance in vigilance tasks as it significantly decreased the slowdown of reaction times in our study.},
      author = {L\"{o}ffler, BS and Stecher, H I and Fudickar, S and de Sordi, D and Otto-Sobotka, F and Hein, A and Herrmann, CH},
      journal = {IEEE - Transactions on Neural Systems {\&} Rehabilitation Engineering},
      title = {{Counteracting the Slowdown of Reaction Times in a Vigilance Experiment with 40-Hz Transcranial Alternating Current Stimulation}},
      year = {2018},
      url = {https://ieeexplore.ieee.org/document/8458158} }
  • C. Lins, S. Fudickar, und A. Hein, "XML Skeleton Definitions for Human Posture Assessments" Studies in Health Technology and Informatics, 2018.
    @article{Lins2018b, abstract = {In this paper, we show how the XML dialect SKAML (Skeletal Assessment Markup Language) can be used to use data from one or more Motion Capture systems to perform human posture assessments with multiple assessment methods. We show an implementation example using an inertial measuring suit and both OWAS and REBA assessment methods. SKAML makes it possible to implement classifiers for a Motion Capture system once and adapt the classifier by-configuration to various ergonomics assessment methods. We anticipate our work as help for researchers and developers that implement new assessment methods or motion capture systems.},
      author = {Lins, Christian and Fudickar, Sebastian and Hein, Andreas},
      file = {:home/s/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Lins, Fudickar, Hein - 2018 - XML Skeleton Definitions for Human Posture Assessments.pdf:pdf},
      journal = {Studies in Health Technology and Informatics},
      keywords = {Motion Capture,Musculoskeletal Disorders,OWAS,Posture Assessment,Posture Classification,REBA,SKAML,Skeleton Markup,UNIAMT,Unpublished},
      title = {{XML Skeleton Definitions for Human Posture Assessments}},
      year = {2018},
      url = {http://doi.org/10.3233/978-1-61499-896-9-225} }
  • 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{AHellmers2018, 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 = {:home/s/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Hellmers et al. - 2018 - Towards an Automated Unsupervised Mobility Assessment for Older People Based on Inertial TUG Measurements.pdf:pdf},
      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} }
  • S. Fudickar, J. Kiselev, T. Frenken, S. Wegel, S. Dimitrowska, E. Steinhagen-Thiessen, und A. Hein, "Validation of the ambient TUG chair with light barriers and force sensors in a clinical trial" Assistive Technology, iss. ja, 2018.
    @article{AFudickar10.1080/10400435.2018.1446195,
      author = { Fudickar, Sebastian and Kiselev, J{\"{o}}rn and Frenken, Thomas and Wegel, Sandra and Dimitrowska, Slavica and Steinhagen-Thiessen, Elisabeth and Hein, Andreas },
      title = {Validation of the ambient TUG chair with light barriers and force sensors in a clinical trial},
      journal = {Assistive Technology},
      volume = {0},
      number = {ja},
      pages = {null},
      year = {2018},
      publisher = {Taylor & Francis},
      doi = {10.1080/10400435.2018.1446195},
      note ={PMID: 29482463},
      URL = {https://doi.org/10.1080/10400435.2018.1446195},
      eprint = {https://doi.org/10.1080/10400435.2018.1446195},
      abstract = {ABSTRACTIntroduction. To initiate appropriate interventions and avoid physical decline, comprehensive measurements are needed to detect functional changes in elderly people at the earliest possible stage. The established Timed Up\&Go (TUG) test takes little time and, due to its standardized and easy procedure, can be conducted by elderly people in their own homes without clinical guidance. Therefore, cheap light barriers and force sensors are well suited ambient sensors that could easily be attached to existing (arm)chairs to measure and report TUG times in order to identify functional decline.Methods. We validated the sensitivity of these sensors in a clinical trial with 100 elderlies aged 58-“92 with a mean of 74 (±6.78) years by comparing the sensor-based results with standard TUG measurements using a stopwatch. We further evaluated the accuracy-enhancement when calibrating the algorithm via a mixed linear model.Results. With calibration, the light barriers achieved a Root Mean Square Error of 0.83 s, compared to 1.90 s without, and the force sensors achieved 0.90 s compared to 2.12 s, respectively. Discussion. The suitability of measuring accurate TUG times with each of the ambient sensors and of measuring TUG regularly in the homes of elderly people could be confirmed. } }
  • S. Fudickar, C. Stolle, N. Volkening, und A. Hein, "Scanning Laser Rangefinders for the Unobtrusive Monitoring of Gait Parameters in Unsupervised Settings" Sensors, vol. 18, iss. 10, p. 3424, 2018.
    @article{AFudickar2018, abstract = {Since variations in common gait parameters (such as cadence, velocity and stride-length) of elderly people are a reliable indicator of functional and cognitive decline in aging and increased fall risks, such gait parameters have to be monitored continuously to enable preventive interventions as early as possible. With scanning laser rangefinders (SLR) having been shown to be suitable for standardised (frontal) gait assessments, this article introduces an unobtrusive gait monitoring (UGMO) system for lateral gait monitoring in homes for the elderly. The system has been evaluated in comparison to a GAITRite (as reference system) with 86 participants (ranging from 21 to 82 years) passing the 6-min walk test twice. Within the considered 56,351 steps within an overall 7877 walks and approximately 34 km distance travelled, it has been shown that the SLR Hokuyo UST10-LX is more sensitive than the cheaper URG-04LX version in regard to the correct (automatic) detection of lateral steps (98% compared to 77%) and walks (97% compared to 66%). Furthermore, it has been confirmed that the UGMO (with the SLR UST10-LX) can measure gait parameters such as gait velocity and stride length with sufficient sensitivity to determine age- and disease-related functional (and cognitive) decline.},
      author = {Fudickar, Sebastian and Stolle, Christian and Volkening, Nils and Hein, Andreas},
      doi = {10.3390/s18103424},
      file = {:home/s/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Fudickar et al. - 2018 - Scanning Laser Rangefinders for the Unobtrusive Monitoring of Gait Parameters in Unsupervised Settings.pdf:pdf},
      journal = {Sensors},
      month = {oct},
      number = {10},
      pages = {3424},
      publisher = {Multidisciplinary Digital Publishing Institute},
      title = {{Scanning Laser Rangefinders for the Unobtrusive Monitoring of Gait Parameters in Unsupervised Settings}},
      url = {http://www.mdpi.com/1424-8220/18/10/3424},
      volume = {18},
      year = {2018} }
  • S. Blum, S. Debener, R. Emkes, N. Volkening, S. Fudickar, und M. G. Bleichner, "EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone" BioMed Research International Hindawi, vol. 2017, p. 12, 2017.
    @article{Blum2017, abstract = {Objective. Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. Approach. In order to implement a closed-loop brain-computer interface (BCI) on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. Main Results. We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. Significance. We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms.},
      author = {Blum, Sarah and Debener, Stefan and Emkes, Reiner and Volkening, Nils and Fudickar, Sebastian and Bleichner, Martin G},
      doi = {10.1155/2017/3072870},
      journal = {BioMed Research International Hindawi},
      pages = {12},
      title = {{EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone}},
      url = {https://www.hindawi.com/journals/bmri/2017/3072870/},
      volume = {2017},
      year = {2017} }
  • [article] bibtex
    S. Fudickar und B. Schnor, "Automated Network Protocol Evaluation - the Potsdam Wireless Testbed" International Journal of Computing, vol. 10, pp. 337-343, 2011.
    @article{Testbed11, abstract = {The Potsdam Wireless Testbed supports validation and evaluation of Wi-Fi radio stacks and wireless applications in environments with heterogeneous hardware. In contrast to simulators, wireless testbeds support the network stack validation with specific radio chipsets and radio signal propagations. Furthermore, wireless testbeds unburden programmers from manually updating software on nodes. Scheduled test-runs are executed automatically for a defined duration including compilation and deployment of the protocols and measurement scripts as well as collection of measurement results and log files. The testbed supports heterogeneous processor architectures and radio chipsets via internal cross compilation. The developer can overview the visualized results of its validation and therefore can focus on the code and the results. Next to the support of several device and processor architectures, the Potsdam Wireless Testbed is intended to support additional radio frequency ranges as well as mobile device.},
      author = {Fudickar, Sebastian and Schnor, Bettina},
      journal = {International Journal of Computing},
      pages = {337--343},
      title = {{Automated Network Protocol Evaluation - the Potsdam Wireless Testbed}},
      volume = {10},
      year = {2011} }
  • S. Fudickar und B. Schnor, "KopAL - A Mobile Orientation System for Dementia Patients" Intelligent Interactive Assistance and Mobile Multimedia Computing, pp. 109-118, 2009.
    @article{Fudickar2009, abstract = {In the aging sectors of societies in the western world, dementia and its characteristics such as disorientation and obliviousness are becoming a significant problem to an increasing number of people and health systems. In order to enable such dementia patients to regain a self-determined life, we have developed a mobile orientation system with a focus on minimal operational costs and a speech based human computer interface. This system assists dementia patients in everyday problems, such as remembering appointments and staying on track within their familiar surroundings as well as informing caretakers in critical situations.},
      author = {Fudickar, Sebastian and Schnor, Bettina},
      journal = {Intelligent Interactive Assistance and Mobile Multimedia Computing},
      pages = {109--118},
      title = {{KopAL - A Mobile Orientation System for Dementia Patients}},
      url = {http://dx.doi.org/10.1007/978-3-642-10263-9{\_}10},
      year = {2009} }
  • [article] bibtex
    K. Nurzynska und S. Fudickar, "Multiple Language, User-Friendly Sign Language Chat" International Journal of Emerging Technologies in Learning, vol. 2, 2007.
    @article{Fudickar07b,
      author = {Nurzynska, Karolina and Fudickar, Sebastian},
      journal = {International Journal of Emerging Technologies in Learning},
      title = {{Multiple Language, User-Friendly Sign Language Chat}},
      volume = {2},
      year = {2007} }
(Stand: 25.06.2021)