---
_id: '58701'
abstract:
- lang: eng
text: Laboratory studies have limitations in screening for anterior cruciate
ligament (ACL) injury risk due to their lack of ecological validity. Machine learning
(ML) methods coupled with wearable sensors are state-of-art approaches for joint
load estimation outside the laboratory in athletic tasks. The aim of this study
was to investigate ML approaches in predicting knee joint loading during sport-specific
agility tasks. We explored the possibility of predicting high and low knee abduction
moments (KAMs) from kinematic data collected in a laboratory setting through wearable
sensors and of predicting the actual KAM from kinematics. Xsens MVN Analyze and
Vicon motion analysis, together with Bertec force plates, were used. Talented
female football (soccer) players (n = 32, age 14.8 ± 1.0 y, height 167.9 ± 5.1
cm, mass 57.5 ± 8.0 kg) performed unanticipated sidestep cutting movements (number
of trials analyzed = 1105). According to the findings of this technical note,
classification models that aim to identify the players exhibiting high or low
KAM are preferable to the ones that aim to predict the actual peak KAM magnitude.
The possibility of classifying high versus low KAMs during agility with good approximation
(AUC 0.81–0.85) represents a step towards testing in an ecologically valid environment.
article_number: '3652'
author:
- first_name: Anne
full_name: Benjaminse, Anne
last_name: Benjaminse
- first_name: Eline M.
full_name: Nijmeijer, Eline M.
last_name: Nijmeijer
- first_name: Alli
full_name: Gokeler, Alli
last_name: Gokeler
- first_name: Stefano
full_name: Di Paolo, Stefano
last_name: Di Paolo
citation:
ama: 'Benjaminse A, Nijmeijer EM, Gokeler A, Di Paolo S. Application of Machine
Learning Methods to Investigate Joint Load in Agility on the Football Field: Creating
the Model, Part I. Sensors. 2024;24(11). doi:10.3390/s24113652'
apa: 'Benjaminse, A., Nijmeijer, E. M., Gokeler, A., & Di Paolo, S. (2024).
Application of Machine Learning Methods to Investigate Joint Load in Agility on
the Football Field: Creating the Model, Part I. Sensors, 24(11),
Article 3652. https://doi.org/10.3390/s24113652'
bibtex: '@article{Benjaminse_Nijmeijer_Gokeler_Di Paolo_2024, title={Application
of Machine Learning Methods to Investigate Joint Load in Agility on the Football
Field: Creating the Model, Part I}, volume={24}, DOI={10.3390/s24113652},
number={113652}, journal={Sensors}, publisher={MDPI AG}, author={Benjaminse, Anne
and Nijmeijer, Eline M. and Gokeler, Alli and Di Paolo, Stefano}, year={2024}
}'
chicago: 'Benjaminse, Anne, Eline M. Nijmeijer, Alli Gokeler, and Stefano Di Paolo.
“Application of Machine Learning Methods to Investigate Joint Load in Agility
on the Football Field: Creating the Model, Part I.” Sensors 24, no. 11
(2024). https://doi.org/10.3390/s24113652.'
ieee: 'A. Benjaminse, E. M. Nijmeijer, A. Gokeler, and S. Di Paolo, “Application
of Machine Learning Methods to Investigate Joint Load in Agility on the Football
Field: Creating the Model, Part I,” Sensors, vol. 24, no. 11, Art. no.
3652, 2024, doi: 10.3390/s24113652.'
mla: 'Benjaminse, Anne, et al. “Application of Machine Learning Methods to Investigate
Joint Load in Agility on the Football Field: Creating the Model, Part I.” Sensors,
vol. 24, no. 11, 3652, MDPI AG, 2024, doi:10.3390/s24113652.'
short: A. Benjaminse, E.M. Nijmeijer, A. Gokeler, S. Di Paolo, Sensors 24 (2024).
date_created: 2025-02-18T14:50:05Z
date_updated: 2025-02-18T14:50:12Z
department:
- _id: '172'
doi: 10.3390/s24113652
intvolume: ' 24'
issue: '11'
language:
- iso: eng
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
publisher: MDPI AG
status: public
title: 'Application of Machine Learning Methods to Investigate Joint Load in Agility
on the Football Field: Creating the Model, Part I'
type: journal_article
user_id: '46'
volume: 24
year: '2024'
...
---
_id: '48781'
abstract:
- lang: eng
text: In a punch-bending machine, wire products are manufactured for a wide range
of industrial sectors, such as the electronics industry. The raw material for
this process is flat wire made of high-strength steel. During the manufacturing
process of the flat wire, residual stresses and plastic deformations are induced
into the wire. These residual stresses and deformations fluctuate over the length
of the semi-finished product and have a negative effect on the final product quality.
Straightening machines are used to reduce this influence to a minimum. So far,
the adjustment of a straightening machine has been performed manually, which is
a lengthy and complex task even for an experienced worker. This inevitably leads
to the use of inefficient straightening strategies and causes high rejection rates
in the entire production process. Due to a lack of sensor information from the
straightening operation, application of modern feedback control methods has not
been practicable. This paper presents a novel design for a straightening machine
with an integrated, precise straightening force measurement. By simultaneously
monitoring the position of the straightening rollers, state variables of the straightening
operation can be derived. Additionally, a tension control for feeding the flat
wire is introduced. This is implemented to mitigate the disturbing effects caused
by irregularities in the wire-feeding process. In the results of this article,
the high precision of the developed force measurement design and its possible
applications are shown.
author:
- first_name: Lukas
full_name: Bathelt, Lukas
last_name: Bathelt
- first_name: Maximilian
full_name: Scurk, Maximilian
last_name: Scurk
- first_name: Eugen
full_name: Djakow, Eugen
id: '7904'
last_name: Djakow
- first_name: Christian
full_name: Henke, Christian
last_name: Henke
- first_name: Ansgar
full_name: Trächtler, Ansgar
id: '552'
last_name: Trächtler
citation:
ama: Bathelt L, Scurk M, Djakow E, Henke C, Trächtler A. Novel Straightening-Machine
Design with Integrated Force Measurement for Straightening of High-Strength Flat
Wire. Sensors. 2023;23(22). doi:10.3390/s23229091
apa: Bathelt, L., Scurk, M., Djakow, E., Henke, C., & Trächtler, A. (2023).
Novel Straightening-Machine Design with Integrated Force Measurement for Straightening
of High-Strength Flat Wire. Sensors, 23(22). https://doi.org/10.3390/s23229091
bibtex: '@article{Bathelt_Scurk_Djakow_Henke_Trächtler_2023, title={Novel Straightening-Machine
Design with Integrated Force Measurement for Straightening of High-Strength Flat
Wire}, volume={23}, DOI={10.3390/s23229091},
number={22}, journal={Sensors}, author={Bathelt, Lukas and Scurk, Maximilian and
Djakow, Eugen and Henke, Christian and Trächtler, Ansgar}, year={2023} }'
chicago: Bathelt, Lukas, Maximilian Scurk, Eugen Djakow, Christian Henke, and Ansgar
Trächtler. “Novel Straightening-Machine Design with Integrated Force Measurement
for Straightening of High-Strength Flat Wire.” Sensors 23, no. 22 (2023).
https://doi.org/10.3390/s23229091.
ieee: 'L. Bathelt, M. Scurk, E. Djakow, C. Henke, and A. Trächtler, “Novel Straightening-Machine
Design with Integrated Force Measurement for Straightening of High-Strength Flat
Wire,” Sensors, vol. 23, no. 22, 2023, doi: 10.3390/s23229091.'
mla: Bathelt, Lukas, et al. “Novel Straightening-Machine Design with Integrated
Force Measurement for Straightening of High-Strength Flat Wire.” Sensors,
vol. 23, no. 22, 2023, doi:10.3390/s23229091.
short: L. Bathelt, M. Scurk, E. Djakow, C. Henke, A. Trächtler, Sensors 23 (2023).
date_created: 2023-11-10T14:25:34Z
date_updated: 2023-11-10T14:28:15Z
department:
- _id: '241'
- _id: '153'
doi: 10.3390/s23229091
intvolume: ' 23'
issue: '22'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.mdpi.com/1424-8220/23/22/9091
oa: '1'
publication: Sensors
publication_identifier:
issn:
- 1424-8220
quality_controlled: '1'
status: public
title: Novel Straightening-Machine Design with Integrated Force Measurement for Straightening
of High-Strength Flat Wire
type: journal_article
user_id: '41470'
volume: 23
year: '2023'
...
---
_id: '45134'
abstract:
- lang: eng
text: 'The aim of the present study was to investigate if the presence of
anterior cruciate ligament (ACL) injury risk factors depicted in the laboratory
would reflect at-risk patterns in football-specific field data. Twenty-four female
footballers (14.9 ± 0.9 year) performed unanticipated cutting maneuvers in a laboratory
setting and on the football pitch during football-specific exercises (F-EX) and
games (F-GAME). Knee joint moments were collected in the laboratory and grouped
using hierarchical agglomerative clustering. The clusters were used to investigate
the kinematics collected on field through wearable sensors. Three clusters emerged:
Cluster 1 presented the lowest knee moments; Cluster 2 presented high knee extension
but low knee abduction and rotation moments; Cluster 3 presented the highest knee
abduction, extension, and external rotation moments. In F-EX, greater knee abduction
angles were found in Cluster 2 and 3 compared to Cluster 1 (p = 0.007). Cluster
2 showed the lowest knee and hip flexion angles (p < 0.013). Cluster 3 showed
the greatest hip external rotation angles (p = 0.006). In F-GAME, Cluster 3 presented
the greatest knee external rotation and lowest knee flexion angles (p = 0.003).
Clinically relevant differences towards ACL injury identified in the laboratory
reflected at-risk patterns only in part when cutting on the field: in the field,
low-risk players exhibited similar kinematic patterns as the high-risk players.
Therefore, in-lab injury risk screening may lack ecological validity.'
article_number: '2176'
author:
- first_name: Stefano
full_name: Di Paolo, Stefano
last_name: Di Paolo
- first_name: Eline M.
full_name: Nijmeijer, Eline M.
last_name: Nijmeijer
- first_name: Laura
full_name: Bragonzoni, Laura
last_name: Bragonzoni
- first_name: Alli
full_name: Gokeler, Alli
last_name: Gokeler
- first_name: Anne
full_name: Benjaminse, Anne
last_name: Benjaminse
citation:
ama: 'Di Paolo S, Nijmeijer EM, Bragonzoni L, Gokeler A, Benjaminse A. Definition
of High-Risk Motion Patterns for Female ACL Injury Based on Football-Specific
Field Data: A Wearable Sensors Plus Data Mining Approach. Sensors. 2023;23(4).
doi:10.3390/s23042176'
apa: 'Di Paolo, S., Nijmeijer, E. M., Bragonzoni, L., Gokeler, A., & Benjaminse,
A. (2023). Definition of High-Risk Motion Patterns for Female ACL Injury Based
on Football-Specific Field Data: A Wearable Sensors Plus Data Mining Approach.
Sensors, 23(4), Article 2176. https://doi.org/10.3390/s23042176'
bibtex: '@article{Di Paolo_Nijmeijer_Bragonzoni_Gokeler_Benjaminse_2023, title={Definition
of High-Risk Motion Patterns for Female ACL Injury Based on Football-Specific
Field Data: A Wearable Sensors Plus Data Mining Approach}, volume={23}, DOI={10.3390/s23042176}, number={42176},
journal={Sensors}, publisher={MDPI AG}, author={Di Paolo, Stefano and Nijmeijer,
Eline M. and Bragonzoni, Laura and Gokeler, Alli and Benjaminse, Anne}, year={2023}
}'
chicago: 'Di Paolo, Stefano, Eline M. Nijmeijer, Laura Bragonzoni, Alli Gokeler,
and Anne Benjaminse. “Definition of High-Risk Motion Patterns for Female ACL Injury
Based on Football-Specific Field Data: A Wearable Sensors Plus Data Mining Approach.”
Sensors 23, no. 4 (2023). https://doi.org/10.3390/s23042176.'
ieee: 'S. Di Paolo, E. M. Nijmeijer, L. Bragonzoni, A. Gokeler, and A. Benjaminse,
“Definition of High-Risk Motion Patterns for Female ACL Injury Based on Football-Specific
Field Data: A Wearable Sensors Plus Data Mining Approach,” Sensors, vol.
23, no. 4, Art. no. 2176, 2023, doi: 10.3390/s23042176.'
mla: 'Di Paolo, Stefano, et al. “Definition of High-Risk Motion Patterns for Female
ACL Injury Based on Football-Specific Field Data: A Wearable Sensors Plus Data
Mining Approach.” Sensors, vol. 23, no. 4, 2176, MDPI AG, 2023, doi:10.3390/s23042176.'
short: S. Di Paolo, E.M. Nijmeijer, L. Bragonzoni, A. Gokeler, A. Benjaminse, Sensors
23 (2023).
date_created: 2023-05-19T09:09:49Z
date_updated: 2023-05-19T09:13:42Z
department:
- _id: '17'
doi: 10.3390/s23042176
intvolume: ' 23'
issue: '4'
keyword:
- Electrical and Electronic Engineering
- Biochemistry
- Instrumentation
- Atomic and Molecular Physics
- and Optics
- Analytical Chemistry
language:
- iso: eng
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
publisher: MDPI AG
status: public
title: 'Definition of High-Risk Motion Patterns for Female ACL Injury Based on Football-Specific
Field Data: A Wearable Sensors Plus Data Mining Approach'
type: journal_article
user_id: '46'
volume: 23
year: '2023'
...
---
_id: '63230'
abstract:
- lang: eng
text: Quartz crystal microbalance with dissipation monitoring (QCM-D) is
a well-established technique for studying soft films. It can provide gravimetric
as well as nongravimetric information about a film, such as its thickness and
mechanical properties. The interpretation of sets of overtone-normalized frequency
shifts, ∆f/n, and overtone-normalized shifts in half-bandwidth, ΔΓ/n, provided
by QCM-D relies on a model that, in general, contains five independent parameters
that are needed to describe film thickness and frequency-dependent viscoelastic
properties. Here, we examine how noise inherent in experimental data affects the
determination of these parameters. There are certain conditions where noise prevents
the reliable determination of film thickness and the loss tangent. On the other
hand, we show that there are conditions where it is possible to determine all
five parameters. We relate these conditions to the mathematical properties of
the model in terms of simple conceptual diagrams that can help users understand
the model’s behavior. Finally, we present new open source software for QCM-D data
analysis written in Python, PyQTM.
article_number: '1348'
author:
- first_name: Diethelm
full_name: Johannsmann, Diethelm
last_name: Johannsmann
- first_name: Arne
full_name: Langhoff, Arne
last_name: Langhoff
- first_name: Christian
full_name: Leppin, Christian
id: '117722'
last_name: Leppin
- first_name: Ilya
full_name: Reviakine, Ilya
last_name: Reviakine
- first_name: Anna M. C.
full_name: Maan, Anna M. C.
last_name: Maan
citation:
ama: Johannsmann D, Langhoff A, Leppin C, Reviakine I, Maan AMC. Effect of Noise
on Determining Ultrathin-Film Parameters from QCM-D Data with the Viscoelastic
Model. Sensors. 2023;23(3). doi:10.3390/s23031348
apa: Johannsmann, D., Langhoff, A., Leppin, C., Reviakine, I., & Maan, A. M.
C. (2023). Effect of Noise on Determining Ultrathin-Film Parameters from QCM-D
Data with the Viscoelastic Model. Sensors, 23(3), Article 1348.
https://doi.org/10.3390/s23031348
bibtex: '@article{Johannsmann_Langhoff_Leppin_Reviakine_Maan_2023, title={Effect
of Noise on Determining Ultrathin-Film Parameters from QCM-D Data with the Viscoelastic
Model}, volume={23}, DOI={10.3390/s23031348},
number={31348}, journal={Sensors}, publisher={MDPI AG}, author={Johannsmann, Diethelm
and Langhoff, Arne and Leppin, Christian and Reviakine, Ilya and Maan, Anna M.
C.}, year={2023} }'
chicago: Johannsmann, Diethelm, Arne Langhoff, Christian Leppin, Ilya Reviakine,
and Anna M. C. Maan. “Effect of Noise on Determining Ultrathin-Film Parameters
from QCM-D Data with the Viscoelastic Model.” Sensors 23, no. 3 (2023).
https://doi.org/10.3390/s23031348.
ieee: 'D. Johannsmann, A. Langhoff, C. Leppin, I. Reviakine, and A. M. C. Maan,
“Effect of Noise on Determining Ultrathin-Film Parameters from QCM-D Data with
the Viscoelastic Model,” Sensors, vol. 23, no. 3, Art. no. 1348, 2023,
doi: 10.3390/s23031348.'
mla: Johannsmann, Diethelm, et al. “Effect of Noise on Determining Ultrathin-Film
Parameters from QCM-D Data with the Viscoelastic Model.” Sensors, vol.
23, no. 3, 1348, MDPI AG, 2023, doi:10.3390/s23031348.
short: D. Johannsmann, A. Langhoff, C. Leppin, I. Reviakine, A.M.C. Maan, Sensors
23 (2023).
date_created: 2025-12-18T17:05:00Z
date_updated: 2025-12-18T17:39:52Z
doi: 10.3390/s23031348
extern: '1'
intvolume: ' 23'
issue: '3'
language:
- iso: eng
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
publisher: MDPI AG
quality_controlled: '1'
status: public
title: Effect of Noise on Determining Ultrathin-Film Parameters from QCM-D Data with
the Viscoelastic Model
type: journal_article
user_id: '117722'
volume: 23
year: '2023'
...
---
_id: '45859'
abstract:
- lang: eng
text: Sport-related concussions (SRC) are characterized by impaired autonomic
control. Heart rate variability (HRV) offers easily obtainable diagnostic approaches
to SRC-associated dysautonomia, but studies investigating HRV during sleep, a
crucial time for post-traumatic cerebral regeneration, are relatively sparse.
The aim of this study was to assess nocturnal HRV in athletes during their return
to sports (RTS) after SRC in their home environment using wireless wrist sensors
(E4, Empatica, Milan, Italy) and to explore possible relations with clinical concussion-associated
sleep symptoms. Eighteen SRC athletes wore a wrist sensor obtaining photoplethysmographic
data at night during RTS as well as one night after full clinical recovery post
RTS (>3 weeks). Nocturnal heart rate and parasympathetic activity of HRV (RMSSD)
were calculated and compared using the Mann–Whitney U Test to values of eighteen;
matched by sex, age, sport, and expertise, control athletes underwent the identical
protocol. During RTS, nocturnal RMSSD of SRC athletes (Mdn = 77.74 ms) showed
a trend compared to controls (Mdn = 95.68 ms, p = 0.021, r = −0.382, p adjusted
using false discovery rate = 0.126) and positively correlated to “drowsiness”
(r = 0.523, p = 0.023, p adjusted = 0.046). Post RTS, no differences in RMSSD
between groups were detected. The presented findings in nocturnal cardiac parasympathetic
activity during nights of RTS in SRC athletes might be a result of concussion,
although its relation to recovery still needs to be elucidated. Utilization of
wireless sensors and wearable technologies in home-based settings offer a possibility
to obtain helpful objective data in the management of SRC.
article_number: '4190'
author:
- first_name: Anne Carina
full_name: Delling, Anne Carina
last_name: Delling
- first_name: Rasmus
full_name: Jakobsmeyer, Rasmus
id: '9583'
last_name: Jakobsmeyer
orcid: 0000-0002-9385-0834
- first_name: Jessica
full_name: Coenen, Jessica
last_name: Coenen
- first_name: Nele
full_name: Christiansen, Nele
last_name: Christiansen
- first_name: Claus
full_name: Reinsberger, Claus
id: '48978'
last_name: Reinsberger
citation:
ama: Delling AC, Jakobsmeyer R, Coenen J, Christiansen N, Reinsberger C. Home-Based
Measurements of Nocturnal Cardiac Parasympathetic Activity in Athletes during
Return to Sport after Sport-Related Concussion. Sensors. 2023;23(9). doi:10.3390/s23094190
apa: Delling, A. C., Jakobsmeyer, R., Coenen, J., Christiansen, N., & Reinsberger,
C. (2023). Home-Based Measurements of Nocturnal Cardiac Parasympathetic Activity
in Athletes during Return to Sport after Sport-Related Concussion. Sensors,
23(9), Article 4190. https://doi.org/10.3390/s23094190
bibtex: '@article{Delling_Jakobsmeyer_Coenen_Christiansen_Reinsberger_2023, title={Home-Based
Measurements of Nocturnal Cardiac Parasympathetic Activity in Athletes during
Return to Sport after Sport-Related Concussion}, volume={23}, DOI={10.3390/s23094190},
number={94190}, journal={Sensors}, publisher={MDPI AG}, author={Delling, Anne
Carina and Jakobsmeyer, Rasmus and Coenen, Jessica and Christiansen, Nele and
Reinsberger, Claus}, year={2023} }'
chicago: Delling, Anne Carina, Rasmus Jakobsmeyer, Jessica Coenen, Nele Christiansen,
and Claus Reinsberger. “Home-Based Measurements of Nocturnal Cardiac Parasympathetic
Activity in Athletes during Return to Sport after Sport-Related Concussion.” Sensors
23, no. 9 (2023). https://doi.org/10.3390/s23094190.
ieee: 'A. C. Delling, R. Jakobsmeyer, J. Coenen, N. Christiansen, and C. Reinsberger,
“Home-Based Measurements of Nocturnal Cardiac Parasympathetic Activity in Athletes
during Return to Sport after Sport-Related Concussion,” Sensors, vol. 23,
no. 9, Art. no. 4190, 2023, doi: 10.3390/s23094190.'
mla: Delling, Anne Carina, et al. “Home-Based Measurements of Nocturnal Cardiac
Parasympathetic Activity in Athletes during Return to Sport after Sport-Related
Concussion.” Sensors, vol. 23, no. 9, 4190, MDPI AG, 2023, doi:10.3390/s23094190.
short: A.C. Delling, R. Jakobsmeyer, J. Coenen, N. Christiansen, C. Reinsberger,
Sensors 23 (2023).
date_created: 2023-07-04T11:30:24Z
date_updated: 2025-08-28T13:41:09Z
department:
- _id: '35'
- _id: '176'
doi: 10.3390/s23094190
intvolume: ' 23'
issue: '9'
keyword:
- Electrical and Electronic Engineering
- Biochemistry
- Instrumentation
- Atomic and Molecular Physics
- and Optics
- Analytical Chemistry
language:
- iso: eng
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
publisher: MDPI AG
status: public
title: Home-Based Measurements of Nocturnal Cardiac Parasympathetic Activity in Athletes
during Return to Sport after Sport-Related Concussion
type: journal_article
user_id: '9583'
volume: 23
year: '2023'
...
---
_id: '31706'
author:
- first_name: C
full_name: Brumann, C
last_name: Brumann
- first_name: M
full_name: Kukuk, M
last_name: Kukuk
- first_name: Claus
full_name: Reinsberger, Claus
id: '48978'
last_name: Reinsberger
citation:
ama: Brumann C, Kukuk M, Reinsberger C. Evaluation of Open-Source and Pre-Trained
Deep Convolutional Neural Networks Suitable for Player Detection and Motion Analysis
in Squash. . Sensors (Basel). 2021;21(13):4550.
apa: Brumann, C., Kukuk, M., & Reinsberger, C. (2021). Evaluation of Open-Source
and Pre-Trained Deep Convolutional Neural Networks Suitable for Player Detection
and Motion Analysis in Squash. . Sensors (Basel), 21(13), 4550.
bibtex: '@article{Brumann_Kukuk_Reinsberger_2021, title={Evaluation of Open-Source
and Pre-Trained Deep Convolutional Neural Networks Suitable for Player Detection
and Motion Analysis in Squash. }, volume={21}, number={13}, journal={Sensors (Basel)},
author={Brumann, C and Kukuk, M and Reinsberger, Claus}, year={2021}, pages={4550}
}'
chicago: 'Brumann, C, M Kukuk, and Claus Reinsberger. “Evaluation of Open-Source
and Pre-Trained Deep Convolutional Neural Networks Suitable for Player Detection
and Motion Analysis in Squash. .” Sensors (Basel) 21, no. 13 (2021): 4550.'
ieee: C. Brumann, M. Kukuk, and C. Reinsberger, “Evaluation of Open-Source and Pre-Trained
Deep Convolutional Neural Networks Suitable for Player Detection and Motion Analysis
in Squash. ,” Sensors (Basel), vol. 21, no. 13, p. 4550, 2021.
mla: Brumann, C., et al. “Evaluation of Open-Source and Pre-Trained Deep Convolutional
Neural Networks Suitable for Player Detection and Motion Analysis in Squash. .”
Sensors (Basel), vol. 21, no. 13, 2021, p. 4550.
short: C. Brumann, M. Kukuk, C. Reinsberger, Sensors (Basel) 21 (2021) 4550.
date_created: 2022-06-07T09:10:15Z
date_updated: 2023-02-06T13:45:37Z
department:
- _id: '35'
- _id: '176'
- _id: '17'
external_id:
pmid:
- '34283127'
intvolume: ' 21'
issue: '13'
language:
- iso: eng
page: '4550'
pmid: '1'
publication: Sensors (Basel)
publication_identifier:
issn:
- 1424-8220
status: public
title: 'Evaluation of Open-Source and Pre-Trained Deep Convolutional Neural Networks
Suitable for Player Detection and Motion Analysis in Squash. '
type: journal_article
user_id: '33213'
volume: 21
year: '2021'
...
---
_id: '63236'
abstract:
- lang: eng
text: 'The response of the quartz crystal microbalance (QCM, also: QCM-D
for “QCM with Dissipation monitoring”) to loading with a diverse set of samples
is reviewed in a consistent frame. After a brief introduction to the advanced
QCMs, the governing equation (the small-load approximation) is derived. Planar
films and adsorbates are modeled based on the acoustic multilayer formalism. In
liquid environments, viscoelastic spectroscopy and high-frequency rheology are
possible, even on layers with a thickness in the monolayer range. For particulate
samples, the contact stiffness can be derived. Because the stress at the contact
is large, the force is not always proportional to the displacement. Nonlinear
effects are observed, leading to a dependence of the resonance frequency and the
resonance bandwidth on the amplitude of oscillation. Partial slip, in particular,
can be studied in detail. Advanced topics include structured samples and the extension
of the small-load approximation to its tensorial version.'
article_number: '3490'
author:
- first_name: Diethelm
full_name: Johannsmann, Diethelm
last_name: Johannsmann
- first_name: Arne
full_name: Langhoff, Arne
last_name: Langhoff
- first_name: Christian
full_name: Leppin, Christian
id: '117722'
last_name: Leppin
citation:
ama: 'Johannsmann D, Langhoff A, Leppin C. Studying Soft Interfaces with Shear Waves:
Principles and Applications of the Quartz Crystal Microbalance (QCM). Sensors.
2021;21(10). doi:10.3390/s21103490'
apa: 'Johannsmann, D., Langhoff, A., & Leppin, C. (2021). Studying Soft Interfaces
with Shear Waves: Principles and Applications of the Quartz Crystal Microbalance
(QCM). Sensors, 21(10), Article 3490. https://doi.org/10.3390/s21103490'
bibtex: '@article{Johannsmann_Langhoff_Leppin_2021, title={Studying Soft Interfaces
with Shear Waves: Principles and Applications of the Quartz Crystal Microbalance
(QCM)}, volume={21}, DOI={10.3390/s21103490},
number={103490}, journal={Sensors}, publisher={MDPI AG}, author={Johannsmann,
Diethelm and Langhoff, Arne and Leppin, Christian}, year={2021} }'
chicago: 'Johannsmann, Diethelm, Arne Langhoff, and Christian Leppin. “Studying
Soft Interfaces with Shear Waves: Principles and Applications of the Quartz Crystal
Microbalance (QCM).” Sensors 21, no. 10 (2021). https://doi.org/10.3390/s21103490.'
ieee: 'D. Johannsmann, A. Langhoff, and C. Leppin, “Studying Soft Interfaces with
Shear Waves: Principles and Applications of the Quartz Crystal Microbalance (QCM),”
Sensors, vol. 21, no. 10, Art. no. 3490, 2021, doi: 10.3390/s21103490.'
mla: 'Johannsmann, Diethelm, et al. “Studying Soft Interfaces with Shear Waves:
Principles and Applications of the Quartz Crystal Microbalance (QCM).” Sensors,
vol. 21, no. 10, 3490, MDPI AG, 2021, doi:10.3390/s21103490.'
short: D. Johannsmann, A. Langhoff, C. Leppin, Sensors 21 (2021).
date_created: 2025-12-18T17:25:13Z
date_updated: 2025-12-18T17:36:06Z
doi: 10.3390/s21103490
extern: '1'
intvolume: ' 21'
issue: '10'
language:
- iso: eng
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
publisher: MDPI AG
quality_controlled: '1'
status: public
title: 'Studying Soft Interfaces with Shear Waves: Principles and Applications of
the Quartz Crystal Microbalance (QCM)'
type: journal_article
user_id: '117722'
volume: 21
year: '2021'
...
---
_id: '17426'
abstract:
- lang: eng
text: The development of renewable energies and smart mobility has profoundly
impacted the future of the distribution grid. An increasing bidirectional energy
flow stresses the assets of the distribution grid, especially medium voltage switchgear.
This calls for improved maintenance strategies to prevent critical failures. Predictive
maintenance, a maintenance strategy relying on current condition data of assets,
serves as a guideline. Novel sensors covering thermal, mechanical, and partial
discharge aspects of switchgear, enable continuous condition monitoring of some
of the most critical assets of the distribution grid. Combined with machine learning
algorithms, the demands put on the distribution grid by the energy and mobility
revolutions can be handled. In this paper, we review the current state-of-the-art
of all aspects of condition monitoring for medium voltage switchgear. Furthermore,
we present an approach to develop a predictive maintenance system based on novel
sensors and machine learning. We show how the existing medium voltage grid infrastructure
can adapt these new needs on an economic scale.
article_number: '2099'
author:
- first_name: Martin W.
full_name: Hoffmann, Martin W.
last_name: Hoffmann
- first_name: Stephan
full_name: Wildermuth, Stephan
last_name: Wildermuth
- first_name: Ralf
full_name: Gitzel, Ralf
last_name: Gitzel
- first_name: Aydin
full_name: Boyaci, Aydin
last_name: Boyaci
- first_name: Jörg
full_name: Gebhardt, Jörg
last_name: Gebhardt
- first_name: Holger
full_name: Kaul, Holger
last_name: Kaul
- first_name: Ido
full_name: Amihai, Ido
last_name: Amihai
- first_name: Bodo
full_name: Forg, Bodo
last_name: Forg
- first_name: Michael
full_name: Suriyah, Michael
last_name: Suriyah
- first_name: Thomas
full_name: Leibfried, Thomas
last_name: Leibfried
- first_name: Volker
full_name: Stich, Volker
last_name: Stich
- first_name: Jan
full_name: Hicking, Jan
last_name: Hicking
- first_name: Martin
full_name: Bremer, Martin
last_name: Bremer
- first_name: Lars
full_name: Kaminski, Lars
last_name: Kaminski
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
- first_name: Philipp
full_name: zur Heiden, Philipp
id: '64394'
last_name: zur Heiden
- first_name: Tanja
full_name: Tornede, Tanja
id: '40795'
last_name: Tornede
citation:
ama: Hoffmann MW, Wildermuth S, Gitzel R, et al. Integration of Novel Sensors and
Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable
the Energy and Mobility Revolutions. Sensors. 2020. doi:10.3390/s20072099
apa: Hoffmann, M. W., Wildermuth, S., Gitzel, R., Boyaci, A., Gebhardt, J., Kaul,
H., … Tornede, T. (2020). Integration of Novel Sensors and Machine Learning for
Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility
Revolutions. Sensors. https://doi.org/10.3390/s20072099
bibtex: '@article{Hoffmann_Wildermuth_Gitzel_Boyaci_Gebhardt_Kaul_Amihai_Forg_Suriyah_Leibfried_et
al._2020, title={Integration of Novel Sensors and Machine Learning for Predictive
Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions},
DOI={10.3390/s20072099}, number={2099},
journal={Sensors}, author={Hoffmann, Martin W. and Wildermuth, Stephan and Gitzel,
Ralf and Boyaci, Aydin and Gebhardt, Jörg and Kaul, Holger and Amihai, Ido and
Forg, Bodo and Suriyah, Michael and Leibfried, Thomas and et al.}, year={2020}
}'
chicago: Hoffmann, Martin W., Stephan Wildermuth, Ralf Gitzel, Aydin Boyaci, Jörg
Gebhardt, Holger Kaul, Ido Amihai, et al. “Integration of Novel Sensors and Machine
Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the
Energy and Mobility Revolutions.” Sensors, 2020. https://doi.org/10.3390/s20072099.
ieee: M. W. Hoffmann et al., “Integration of Novel Sensors and Machine Learning
for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and
Mobility Revolutions,” Sensors, 2020.
mla: Hoffmann, Martin W., et al. “Integration of Novel Sensors and Machine Learning
for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and
Mobility Revolutions.” Sensors, 2099, 2020, doi:10.3390/s20072099.
short: M.W. Hoffmann, S. Wildermuth, R. Gitzel, A. Boyaci, J. Gebhardt, H. Kaul,
I. Amihai, B. Forg, M. Suriyah, T. Leibfried, V. Stich, J. Hicking, M. Bremer,
L. Kaminski, D. Beverungen, P. zur Heiden, T. Tornede, Sensors (2020).
date_created: 2020-07-28T09:47:36Z
date_updated: 2022-01-06T06:53:11Z
doi: 10.3390/s20072099
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.mdpi.com/1424-8220/20/7/2099
oa: '1'
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
status: public
title: Integration of Novel Sensors and Machine Learning for Predictive Maintenance
in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions
type: journal_article
user_id: '40795'
year: '2020'
...
---
_id: '35723'
abstract:
- lang: eng
text: The development of renewable energies and smart mobility has profoundly
impacted the future of the distribution grid. An increasing bidirectional energy
flow stresses the assets of the distribution grid, especially medium voltage switchgear.
This calls for improved maintenance strategies to prevent critical failures. Predictive
maintenance, a maintenance strategy relying on current condition data of assets,
serves as a guideline. Novel sensors covering thermal, mechanical, and partial
discharge aspects of switchgear, enable continuous condition monitoring of some
of the most critical assets of the distribution grid. Combined with machine learning
algorithms, the demands put on the distribution grid by the energy and mobility
revolutions can be handled. In this paper, we review the current state-of-the-art
of all aspects of condition monitoring for medium voltage switchgear. Furthermore,
we present an approach to develop a predictive maintenance system based on novel
sensors and machine learning. We show how the existing medium voltage grid infrastructure
can adapt these new needs on an economic scale.
article_number: '2099'
author:
- first_name: Martin W.
full_name: Hoffmann, Martin W.
last_name: Hoffmann
- first_name: Stephan
full_name: Wildermuth, Stephan
last_name: Wildermuth
- first_name: Ralf
full_name: Gitzel, Ralf
last_name: Gitzel
- first_name: Aydin
full_name: Boyaci, Aydin
last_name: Boyaci
- first_name: Jörg
full_name: Gebhardt, Jörg
last_name: Gebhardt
- first_name: Holger
full_name: Kaul, Holger
last_name: Kaul
- first_name: Ido
full_name: Amihai, Ido
last_name: Amihai
- first_name: Bodo
full_name: Forg, Bodo
last_name: Forg
- first_name: Michael
full_name: Suriyah, Michael
last_name: Suriyah
- first_name: Thomas
full_name: Leibfried, Thomas
last_name: Leibfried
- first_name: Volker
full_name: Stich, Volker
last_name: Stich
- first_name: Jan
full_name: Hicking, Jan
last_name: Hicking
- first_name: Martin
full_name: Bremer, Martin
last_name: Bremer
- first_name: Lars
full_name: Kaminski, Lars
last_name: Kaminski
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
- first_name: Philipp
full_name: zur Heiden, Philipp
id: '64394'
last_name: zur Heiden
- first_name: Tanja
full_name: Tornede, Tanja
last_name: Tornede
citation:
ama: Hoffmann MW, Wildermuth S, Gitzel R, et al. Integration of Novel Sensors and
Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable
the Energy and Mobility Revolutions. Sensors. 2020;20(7). doi:10.3390/s20072099
apa: Hoffmann, M. W., Wildermuth, S., Gitzel, R., Boyaci, A., Gebhardt, J., Kaul,
H., Amihai, I., Forg, B., Suriyah, M., Leibfried, T., Stich, V., Hicking, J.,
Bremer, M., Kaminski, L., Beverungen, D., zur Heiden, P., & Tornede, T. (2020).
Integration of Novel Sensors and Machine Learning for Predictive Maintenance in
Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions. Sensors,
20(7), Article 2099. https://doi.org/10.3390/s20072099
bibtex: '@article{Hoffmann_Wildermuth_Gitzel_Boyaci_Gebhardt_Kaul_Amihai_Forg_Suriyah_Leibfried_et
al._2020, title={Integration of Novel Sensors and Machine Learning for Predictive
Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions},
volume={20}, DOI={10.3390/s20072099},
number={72099}, journal={Sensors}, publisher={MDPI AG}, author={Hoffmann, Martin
W. and Wildermuth, Stephan and Gitzel, Ralf and Boyaci, Aydin and Gebhardt, Jörg
and Kaul, Holger and Amihai, Ido and Forg, Bodo and Suriyah, Michael and Leibfried,
Thomas and et al.}, year={2020} }'
chicago: Hoffmann, Martin W., Stephan Wildermuth, Ralf Gitzel, Aydin Boyaci, Jörg
Gebhardt, Holger Kaul, Ido Amihai, et al. “Integration of Novel Sensors and Machine
Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the
Energy and Mobility Revolutions.” Sensors 20, no. 7 (2020). https://doi.org/10.3390/s20072099.
ieee: 'M. W. Hoffmann et al., “Integration of Novel Sensors and Machine Learning
for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and
Mobility Revolutions,” Sensors, vol. 20, no. 7, Art. no. 2099, 2020, doi:
10.3390/s20072099.'
mla: Hoffmann, Martin W., et al. “Integration of Novel Sensors and Machine Learning
for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and
Mobility Revolutions.” Sensors, vol. 20, no. 7, 2099, MDPI AG, 2020, doi:10.3390/s20072099.
short: M.W. Hoffmann, S. Wildermuth, R. Gitzel, A. Boyaci, J. Gebhardt, H. Kaul,
I. Amihai, B. Forg, M. Suriyah, T. Leibfried, V. Stich, J. Hicking, M. Bremer,
L. Kaminski, D. Beverungen, P. zur Heiden, T. Tornede, Sensors 20 (2020).
date_created: 2023-01-10T09:39:14Z
date_updated: 2023-01-10T09:53:13Z
department:
- _id: '526'
doi: 10.3390/s20072099
intvolume: ' 20'
issue: '7'
keyword:
- Electrical and Electronic Engineering
- Biochemistry
- Instrumentation
- Atomic and Molecular Physics
- and Optics
- Analytical Chemistry
language:
- iso: eng
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
publisher: MDPI AG
status: public
title: Integration of Novel Sensors and Machine Learning for Predictive Maintenance
in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions
type: journal_article
user_id: '21671'
volume: 20
year: '2020'
...
---
_id: '63239'
abstract:
- lang: eng
text: A quartz crystal microbalance (QCM) is described, which simultaneously
determines resonance frequency and bandwidth on four different overtones. The
time resolution is 10 milliseconds. This fast, multi-overtone QCM is based on
multi-frequency lockin amplification. Synchronous interrogation of overtones is
needed, when the sample changes quickly and when information on the sample is
to be extracted from the comparison between overtones. The application example
is thermal inkjet-printing. At impact, the resonance frequencies change over a
time shorter than 10 milliseconds. There is a further increase in the contact
area, evidenced by an increasing common prefactor to the shifts in frequency,
Δf, and half-bandwidth, ΔΓ. The ratio ΔΓ/(−Δf), which quantifies the energy dissipated
per time and unit area, decreases with time. Often, there is a fast initial decrease,
lasting for about 100 milliseconds, followed by a slower decrease, persisting
over the entire drying time (a few seconds). Fitting the overtone dependence of
Δf(n) and ΔΓ(n) with power laws, one finds power-law exponents of about 1/2, characteristic
of semi-infinite Newtonian liquids. The power-law exponents corresponding to Δf(n)
slightly increase with time. The decrease of ΔΓ/(−Δf) and the increase of the
exponents are explained by evaporation and formation of a solid film at the resonator
surface.
article_number: '5915'
author:
- first_name: Christian
full_name: Leppin, Christian
id: '117722'
last_name: Leppin
- first_name: Sven
full_name: Hampel, Sven
last_name: Hampel
- first_name: Frederick Sebastian
full_name: Meyer, Frederick Sebastian
last_name: Meyer
- first_name: Arne
full_name: Langhoff, Arne
last_name: Langhoff
- first_name: Ursula Elisabeth Adriane
full_name: Fittschen, Ursula Elisabeth Adriane
last_name: Fittschen
- first_name: Diethelm
full_name: Johannsmann, Diethelm
last_name: Johannsmann
citation:
ama: 'Leppin C, Hampel S, Meyer FS, Langhoff A, Fittschen UEA, Johannsmann D. A
Quartz Crystal Microbalance, Which Tracks Four Overtones in Parallel with a Time
Resolution of 10 Milliseconds: Application to Inkjet Printing. Sensors.
2020;20(20). doi:10.3390/s20205915'
apa: 'Leppin, C., Hampel, S., Meyer, F. S., Langhoff, A., Fittschen, U. E. A., &
Johannsmann, D. (2020). A Quartz Crystal Microbalance, Which Tracks Four Overtones
in Parallel with a Time Resolution of 10 Milliseconds: Application to Inkjet Printing.
Sensors, 20(20), Article 5915. https://doi.org/10.3390/s20205915'
bibtex: '@article{Leppin_Hampel_Meyer_Langhoff_Fittschen_Johannsmann_2020, title={A
Quartz Crystal Microbalance, Which Tracks Four Overtones in Parallel with a Time
Resolution of 10 Milliseconds: Application to Inkjet Printing}, volume={20}, DOI={10.3390/s20205915}, number={205915},
journal={Sensors}, publisher={MDPI AG}, author={Leppin, Christian and Hampel,
Sven and Meyer, Frederick Sebastian and Langhoff, Arne and Fittschen, Ursula Elisabeth
Adriane and Johannsmann, Diethelm}, year={2020} }'
chicago: 'Leppin, Christian, Sven Hampel, Frederick Sebastian Meyer, Arne Langhoff,
Ursula Elisabeth Adriane Fittschen, and Diethelm Johannsmann. “A Quartz Crystal
Microbalance, Which Tracks Four Overtones in Parallel with a Time Resolution of
10 Milliseconds: Application to Inkjet Printing.” Sensors 20, no. 20 (2020).
https://doi.org/10.3390/s20205915.'
ieee: 'C. Leppin, S. Hampel, F. S. Meyer, A. Langhoff, U. E. A. Fittschen, and D.
Johannsmann, “A Quartz Crystal Microbalance, Which Tracks Four Overtones in Parallel
with a Time Resolution of 10 Milliseconds: Application to Inkjet Printing,” Sensors,
vol. 20, no. 20, Art. no. 5915, 2020, doi: 10.3390/s20205915.'
mla: 'Leppin, Christian, et al. “A Quartz Crystal Microbalance, Which Tracks Four
Overtones in Parallel with a Time Resolution of 10 Milliseconds: Application to
Inkjet Printing.” Sensors, vol. 20, no. 20, 5915, MDPI AG, 2020, doi:10.3390/s20205915.'
short: C. Leppin, S. Hampel, F.S. Meyer, A. Langhoff, U.E.A. Fittschen, D. Johannsmann,
Sensors 20 (2020).
date_created: 2025-12-18T17:29:29Z
date_updated: 2025-12-18T17:33:50Z
doi: 10.3390/s20205915
extern: '1'
intvolume: ' 20'
issue: '20'
language:
- iso: eng
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
publisher: MDPI AG
quality_controlled: '1'
status: public
title: 'A Quartz Crystal Microbalance, Which Tracks Four Overtones in Parallel with
a Time Resolution of 10 Milliseconds: Application to Inkjet Printing'
type: journal_article
user_id: '117722'
volume: 20
year: '2020'
...
---
_id: '66245'
abstract:
- lang: eng
text: A mobile system that can detect viruses in real time is urgently needed,
due to the combination of virus emergence and evolution with increasing global
travel and transport. A biosensor called PAMONO (for Plasmon Assisted Microscopy
of Nano-sized Objects) represents a viable technology for mobile real-time detection
of viruses and virus-like particles. It could be used for fast and reliable diagnoses
in hospitals, airports, the open air, or other settings. For analysis of the images
provided by the sensor, state-of-the-art methods based on convolutional neural
networks (CNNs) can achieve high accuracy. However, such computationally intensive
methods may not be suitable on most mobile systems. In this work, we propose nanoparticle
classification approaches based on frequency domain analysis, which are less resource-intensive.
We observe that on average the classification takes 29 μ s per image for
the Fourier features and 17 μ s for the Haar wavelet features. Although the
CNN-based method scores 1–2.5 percentage points higher in classification accuracy,
it takes 3370 μ s per image on the same platform. With these results, we
identify and explore the trade-off between resource efficiency and classification
performance for nanoparticle classification of images provided by the PAMONO sensor.
article_number: '4138'
author:
- first_name: Mikail
full_name: Yayla, Mikail
last_name: Yayla
- first_name: Anas
full_name: Toma, Anas
last_name: Toma
- first_name: Kuan-Hsun
full_name: Chen, Kuan-Hsun
last_name: Chen
- first_name: Jan Eric
full_name: Lenssen, Jan Eric
last_name: Lenssen
- first_name: Victoria
full_name: Shpacovitch, Victoria
last_name: Shpacovitch
- first_name: Roland
full_name: Hergenröder, Roland
last_name: Hergenröder
- first_name: Frank
full_name: Weichert, Frank
last_name: Weichert
- first_name: Jian-Jia
full_name: Chen, Jian-Jia
last_name: Chen
citation:
ama: Yayla M, Toma A, Chen K-H, et al. Nanoparticle Classification Using Frequency
Domain Analysis on Resource-Limited Platforms. Sensors. 2019;19(19). doi:10.3390/s19194138
apa: Yayla, M., Toma, A., Chen, K.-H., Lenssen, J. E., Shpacovitch, V., Hergenröder,
R., Weichert, F., & Chen, J.-J. (2019). Nanoparticle Classification Using
Frequency Domain Analysis on Resource-Limited Platforms. Sensors, 19(19),
Article 4138. https://doi.org/10.3390/s19194138
bibtex: '@article{Yayla_Toma_Chen_Lenssen_Shpacovitch_Hergenröder_Weichert_Chen_2019,
title={Nanoparticle Classification Using Frequency Domain Analysis on Resource-Limited
Platforms}, volume={19}, DOI={10.3390/s19194138},
number={194138}, journal={Sensors}, publisher={MDPI AG}, author={Yayla, Mikail
and Toma, Anas and Chen, Kuan-Hsun and Lenssen, Jan Eric and Shpacovitch, Victoria
and Hergenröder, Roland and Weichert, Frank and Chen, Jian-Jia}, year={2019} }'
chicago: Yayla, Mikail, Anas Toma, Kuan-Hsun Chen, Jan Eric Lenssen, Victoria Shpacovitch,
Roland Hergenröder, Frank Weichert, and Jian-Jia Chen. “Nanoparticle Classification
Using Frequency Domain Analysis on Resource-Limited Platforms.” Sensors
19, no. 19 (2019). https://doi.org/10.3390/s19194138.
ieee: 'M. Yayla et al., “Nanoparticle Classification Using Frequency Domain
Analysis on Resource-Limited Platforms,” Sensors, vol. 19, no. 19, Art.
no. 4138, 2019, doi: 10.3390/s19194138.'
mla: Yayla, Mikail, et al. “Nanoparticle Classification Using Frequency Domain Analysis
on Resource-Limited Platforms.” Sensors, vol. 19, no. 19, 4138, MDPI AG,
2019, doi:10.3390/s19194138.
short: M. Yayla, A. Toma, K.-H. Chen, J.E. Lenssen, V. Shpacovitch, R. Hergenröder,
F. Weichert, J.-J. Chen, Sensors 19 (2019).
date_created: 2026-07-05T14:35:15Z
date_updated: 2026-07-05T14:43:54Z
doi: 10.3390/s19194138
intvolume: ' 19'
issue: '19'
language:
- iso: eng
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
publisher: MDPI AG
status: public
title: Nanoparticle Classification Using Frequency Domain Analysis on Resource-Limited
Platforms
type: journal_article
user_id: '128464'
volume: 19
year: '2019'
...
---
_id: '13882'
author:
- first_name: Martin
full_name: Schmitt, Martin
last_name: Schmitt
- first_name: Sergei
full_name: Olfert, Sergei
last_name: Olfert
- first_name: Jens
full_name: Rautenberg, Jens
last_name: Rautenberg
- first_name: Gerhard
full_name: Lindner, Gerhard
last_name: Lindner
- first_name: Bernd
full_name: Henning, Bernd
id: '213'
last_name: Henning
- first_name: Leonhard
full_name: Reindl, Leonhard
last_name: Reindl
citation:
ama: Schmitt M, Olfert S, Rautenberg J, Lindner G, Henning B, Reindl L. Multi Reflection
of Lamb Wave Emission in an Acoustic Waveguide Sensor. Sensors. 2013:2777-2785.
doi:10.3390/s130302777
apa: Schmitt, M., Olfert, S., Rautenberg, J., Lindner, G., Henning, B., & Reindl,
L. (2013). Multi Reflection of Lamb Wave Emission in an Acoustic Waveguide Sensor.
Sensors, 2777–2785. https://doi.org/10.3390/s130302777
bibtex: '@article{Schmitt_Olfert_Rautenberg_Lindner_Henning_Reindl_2013, title={Multi
Reflection of Lamb Wave Emission in an Acoustic Waveguide Sensor}, DOI={10.3390/s130302777},
journal={Sensors}, author={Schmitt, Martin and Olfert, Sergei and Rautenberg,
Jens and Lindner, Gerhard and Henning, Bernd and Reindl, Leonhard}, year={2013},
pages={2777–2785} }'
chicago: Schmitt, Martin, Sergei Olfert, Jens Rautenberg, Gerhard Lindner, Bernd
Henning, and Leonhard Reindl. “Multi Reflection of Lamb Wave Emission in an Acoustic
Waveguide Sensor.” Sensors, 2013, 2777–85. https://doi.org/10.3390/s130302777.
ieee: M. Schmitt, S. Olfert, J. Rautenberg, G. Lindner, B. Henning, and L. Reindl,
“Multi Reflection of Lamb Wave Emission in an Acoustic Waveguide Sensor,” Sensors,
pp. 2777–2785, 2013.
mla: Schmitt, Martin, et al. “Multi Reflection of Lamb Wave Emission in an Acoustic
Waveguide Sensor.” Sensors, 2013, pp. 2777–85, doi:10.3390/s130302777.
short: M. Schmitt, S. Olfert, J. Rautenberg, G. Lindner, B. Henning, L. Reindl,
Sensors (2013) 2777–2785.
date_created: 2019-10-16T13:58:22Z
date_updated: 2022-01-06T06:51:46Z
department:
- _id: '49'
doi: 10.3390/s130302777
language:
- iso: eng
page: 2777-2785
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
status: public
title: Multi Reflection of Lamb Wave Emission in an Acoustic Waveguide Sensor
type: journal_article
user_id: '15911'
year: '2013'
...
---
_id: '25964'
abstract:
- lang: eng
text: Capacitive sensors are the most commonly used devices for the detection of
humidity because they are inexpensive and the detection mechanism is very specific
for humidity. However, especially for industrial processes, there is a lack of
dielectrics that are stable at high temperature (>200 °C) and under harsh conditions.
We present a capacitive sensor based on mesoporous silica as the dielectric in
a simple sensor design based on pressed silica pellets. Investigation of the structural
stability of the porous silica under simulated operating conditions as well as
the influence of the pellet production will be shown. Impedance measurements demonstrate
the utility of the sensor at both low (90 °C) and high (up to 210 °C) operating
temperatures.
article_type: original
author:
- first_name: Thorsten
full_name: Wagner, Thorsten
last_name: Wagner
- first_name: Sören
full_name: Krotzky, Sören
last_name: Krotzky
- first_name: Alexander
full_name: Weiß, Alexander
last_name: Weiß
- first_name: Tilman
full_name: Sauerwald, Tilman
last_name: Sauerwald
- first_name: Claus-Dieter
full_name: Kohl, Claus-Dieter
last_name: Kohl
- first_name: Jan
full_name: Roggenbuck, Jan
last_name: Roggenbuck
- first_name: Michael
full_name: Tiemann, Michael
id: '23547'
last_name: Tiemann
orcid: 0000-0003-1711-2722
citation:
ama: Wagner T, Krotzky S, Weiß A, et al. A High Temperature Capacitive Humidity
Sensor Based on Mesoporous Silica. Sensors. Published online 2011:3135-3144.
doi:10.3390/s110303135
apa: Wagner, T., Krotzky, S., Weiß, A., Sauerwald, T., Kohl, C.-D., Roggenbuck,
J., & Tiemann, M. (2011). A High Temperature Capacitive Humidity Sensor Based
on Mesoporous Silica. Sensors, 3135–3144. https://doi.org/10.3390/s110303135
bibtex: '@article{Wagner_Krotzky_Weiß_Sauerwald_Kohl_Roggenbuck_Tiemann_2011, title={A
High Temperature Capacitive Humidity Sensor Based on Mesoporous Silica}, DOI={10.3390/s110303135}, journal={Sensors},
author={Wagner, Thorsten and Krotzky, Sören and Weiß, Alexander and Sauerwald,
Tilman and Kohl, Claus-Dieter and Roggenbuck, Jan and Tiemann, Michael}, year={2011},
pages={3135–3144} }'
chicago: Wagner, Thorsten, Sören Krotzky, Alexander Weiß, Tilman Sauerwald, Claus-Dieter
Kohl, Jan Roggenbuck, and Michael Tiemann. “A High Temperature Capacitive Humidity
Sensor Based on Mesoporous Silica.” Sensors, 2011, 3135–44. https://doi.org/10.3390/s110303135.
ieee: 'T. Wagner et al., “A High Temperature Capacitive Humidity Sensor Based
on Mesoporous Silica,” Sensors, pp. 3135–3144, 2011, doi: 10.3390/s110303135.'
mla: Wagner, Thorsten, et al. “A High Temperature Capacitive Humidity Sensor Based
on Mesoporous Silica.” Sensors, 2011, pp. 3135–44, doi:10.3390/s110303135.
short: T. Wagner, S. Krotzky, A. Weiß, T. Sauerwald, C.-D. Kohl, J. Roggenbuck,
M. Tiemann, Sensors (2011) 3135–3144.
date_created: 2021-10-09T05:01:29Z
date_updated: 2023-03-09T08:30:11Z
department:
- _id: '35'
- _id: '2'
- _id: '307'
doi: 10.3390/s110303135
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.mdpi.com/1424-8220/11/3/3135/pdf?version=1403314474
oa: '1'
page: 3135-3144
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
quality_controlled: '1'
status: public
title: A High Temperature Capacitive Humidity Sensor Based on Mesoporous Silica
type: journal_article
user_id: '23547'
year: '2011'
...
---
_id: '25992'
abstract:
- lang: eng
text: We report on the synthesis and CO gas-sensing properties of mesoporous tin(IV)
oxides (SnO2). For the synthesis cetyltrimethylammonium bromide (CTABr) was used
as a structure-directing agent; the resulting SnO2 powders were applied as films
to commercially available sensor substrates by drop coating. Nitrogen physisorption
shows specific surface areas up to 160 m2·g-1 and mean pore diameters of about
4 nm, as verified by TEM. The film conductance was measured in dependence on the
CO concentration in humid synthetic air at a constant temperature of 300 °C. The
sensors show a high sensitivity at low CO concentrations and turn out to be largely
insensitive towards changes in the relative humidity. We compare the materials
with commercially available SnO2-based sensors.
article_type: original
author:
- first_name: Thorsten
full_name: Wagner, Thorsten
last_name: Wagner
- first_name: Claus-Dieter
full_name: Kohl, Claus-Dieter
last_name: Kohl
- first_name: Michael
full_name: Fröba, Michael
last_name: Fröba
- first_name: Michael
full_name: Tiemann, Michael
id: '23547'
last_name: Tiemann
orcid: 0000-0003-1711-2722
citation:
ama: Wagner T, Kohl C-D, Fröba M, Tiemann M. Gas Sensing Properties of Ordered Mesoporous
SnO2. Sensors. Published online 2006:318-323. doi:10.3390/s6040318
apa: Wagner, T., Kohl, C.-D., Fröba, M., & Tiemann, M. (2006). Gas Sensing Properties
of Ordered Mesoporous SnO2. Sensors, 318–323. https://doi.org/10.3390/s6040318
bibtex: '@article{Wagner_Kohl_Fröba_Tiemann_2006, title={Gas Sensing Properties
of Ordered Mesoporous SnO2}, DOI={10.3390/s6040318},
journal={Sensors}, author={Wagner, Thorsten and Kohl, Claus-Dieter and Fröba,
Michael and Tiemann, Michael}, year={2006}, pages={318–323} }'
chicago: Wagner, Thorsten, Claus-Dieter Kohl, Michael Fröba, and Michael Tiemann.
“Gas Sensing Properties of Ordered Mesoporous SnO2.” Sensors, 2006, 318–23.
https://doi.org/10.3390/s6040318.
ieee: 'T. Wagner, C.-D. Kohl, M. Fröba, and M. Tiemann, “Gas Sensing Properties
of Ordered Mesoporous SnO2,” Sensors, pp. 318–323, 2006, doi: 10.3390/s6040318.'
mla: Wagner, Thorsten, et al. “Gas Sensing Properties of Ordered Mesoporous SnO2.”
Sensors, 2006, pp. 318–23, doi:10.3390/s6040318.
short: T. Wagner, C.-D. Kohl, M. Fröba, M. Tiemann, Sensors (2006) 318–323.
date_created: 2021-10-09T09:45:45Z
date_updated: 2023-03-09T08:57:27Z
department:
- _id: '35'
- _id: '2'
- _id: '307'
doi: 10.3390/s6040318
extern: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.mdpi.com/1424-8220/6/4/318/pdf?version=1403301070
oa: '1'
page: 318-323
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
quality_controlled: '1'
status: public
title: Gas Sensing Properties of Ordered Mesoporous SnO2
type: journal_article
user_id: '23547'
year: '2006'
...