---
_id: '4312'
abstract:
- lang: eng
text: Computer-aided assistance systems are entering the world of work and production.
Such systems utilize augmented- and virtual-reality for operator training and
live guidance as well as mobile maintenance and support. This is particularly
important in the modern production reality of ever-changing products and `lot
size one' customization of production.This paper focuses on the application of
machine learning approach to extend the functionality of assistance systems. Machine
learning provides tools to analyse large amounts of data and extract meaningful
information. The goal here is to recognize the movement of an operator which would
enable automatic display of instructions relevant to them.We present the challenges
facing machine learning applications in human-centered assistance systems and
a framework to assess machine learning approaches feasible for this scenario.
The approach is assessed on a historical data set and then deployed in a work
station for live testing. The post-hoc, or historical, analysis yields promising
results. The ad-hoc, or live, analysis is a complex task and the results are affected
by multiple factors, most of which are introduced by the human influence.The contribution
of this paper is an approach to adapt state- of-the-art machine learning to operator
movement recognition with a special focus on approaches to spatial time series
data pre-processing. Presented experiment results validate the approach and show
that it performs well in a real-world scenario.
author:
- first_name: Marta
full_name: Fullen, Marta
last_name: Fullen
- first_name: Alexander
full_name: Maier, Alexander
id: '11158'
last_name: Maier
- first_name: Arthur
full_name: Nazarenko, Arthur
last_name: Nazarenko
- first_name: Sascha
full_name: Jenderny, Sascha
last_name: Jenderny
- first_name: Carsten
full_name: Röcker, Carsten
id: '61525'
last_name: Röcker
citation:
ama: 'Fullen M, Maier A, Nazarenko A, Jenderny S, Röcker C. Machine Learning for
Assistance Systems: Pattern-Based Approach to Online Step Recognition. In: IEEE,
ed. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN).
Piscataway, NJ : IEEE; 2019:296-302. doi:10.1109/INDIN41052.2019.8972122'
apa: 'Fullen, M., Maier, A., Nazarenko, A., Jenderny, S., & Röcker, C. (2019).
Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step
Recognition. In IEEE (Ed.), 2019 IEEE 17th International Conference on Industrial
Informatics (INDIN) (pp. 296–302). Piscataway, NJ : IEEE. https://doi.org/10.1109/INDIN41052.2019.8972122'
bjps: 'Fullen M et al. (2019) Machine Learning for Assistance Systems:
Pattern-Based Approach to Online Step Recognition. In IEEE (ed.), 2019 IEEE
17th International Conference on Industrial Informatics (INDIN). Piscataway,
NJ : IEEE, pp. 296–302.'
chicago: 'Fullen, Marta, Alexander Maier, Arthur Nazarenko, Sascha Jenderny, and
Carsten Röcker. “Machine Learning for Assistance Systems: Pattern-Based Approach
to Online Step Recognition.” In 2019 IEEE 17th International Conference on
Industrial Informatics (INDIN), edited by IEEE, 296–302. Piscataway, NJ :
IEEE, 2019. https://doi.org/10.1109/INDIN41052.2019.8972122.'
chicago-de: 'Fullen, Marta, Alexander Maier, Arthur Nazarenko, Sascha Jenderny und
Carsten Röcker. 2019. Machine Learning for Assistance Systems: Pattern-Based Approach
to Online Step Recognition. In: 2019 IEEE 17th International Conference on
Industrial Informatics (INDIN), hg. von IEEE, 296–302. Piscataway, NJ : IEEE.
doi:10.1109/INDIN41052.2019.8972122,
.'
din1505-2-1: 'Fullen, Marta ; Maier, Alexander ; Nazarenko,
Arthur ; Jenderny, Sascha
; Röcker, Carsten: Machine Learning
for Assistance Systems: Pattern-Based Approach to Online Step Recognition. In:
IEEE (Hrsg.): 2019 IEEE 17th
International Conference on Industrial Informatics (INDIN). Piscataway, NJ
: IEEE, 2019, S. 296–302'
havard: 'M. Fullen, A. Maier, A. Nazarenko, S. Jenderny, C. Röcker, Machine Learning
for Assistance Systems: Pattern-Based Approach to Online Step Recognition, in:
IEEE (Ed.), 2019 IEEE 17th International Conference on Industrial Informatics
(INDIN), IEEE, Piscataway, NJ , 2019: pp. 296–302.'
ieee: 'M. Fullen, A. Maier, A. Nazarenko, S. Jenderny, and C. Röcker, “Machine Learning
for Assistance Systems: Pattern-Based Approach to Online Step Recognition,” in
2019 IEEE 17th International Conference on Industrial Informatics (INDIN),
IEEE, Ed. Piscataway, NJ : IEEE, 2019, pp. 296–302.'
mla: 'Fullen, Marta, et al. “Machine Learning for Assistance Systems: Pattern-Based
Approach to Online Step Recognition.” 2019 IEEE 17th International Conference
on Industrial Informatics (INDIN), edited by IEEE, IEEE, 2019, pp. 296–302,
doi:10.1109/INDIN41052.2019.8972122.'
short: 'M. Fullen, A. Maier, A. Nazarenko, S. Jenderny, C. Röcker, in: IEEE (Ed.),
2019 IEEE 17th International Conference on Industrial Informatics (INDIN), IEEE,
Piscataway, NJ , 2019, pp. 296–302.'
ufg: 'Fullen, Marta et. al. (2019): Machine Learning for Assistance Systems:
Pattern-Based Approach to Online Step Recognition, in: IEEE (Hg.): 2019 IEEE
17th International Conference on Industrial Informatics (INDIN), Piscataway,
NJ , S. 296–302.'
van: 'Fullen M, Maier A, Nazarenko A, Jenderny S, Röcker C. Machine Learning for
Assistance Systems: Pattern-Based Approach to Online Step Recognition. In: IEEE,
editor. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN).
Piscataway, NJ : IEEE; 2019. p. 296–302.'
conference:
end_date: 2019-07-25
location: Helsinki, Finland,
name: 17th International Conference on Industrial Informatics (INDIN)
start_date: 2019-07-22
corporate_editor:
- IEEE
date_created: 2021-01-06T13:59:10Z
date_updated: 2023-03-15T13:49:51Z
department:
- _id: DEP5023
doi: 10.1109/INDIN41052.2019.8972122
keyword:
- augmented reality
- computer based training
- data handling
- industrial training
- learning (artificial intelligence)
- time series
language:
- iso: eng
page: 296 - 302
place: 'Piscataway, NJ '
publication: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN)
publication_identifier:
isbn:
- 978-1-7281-2927-3
issn:
- 2378-363X
publication_status: published
publisher: IEEE
status: public
title: 'Machine Learning for Assistance Systems: Pattern-Based Approach to Online
Step Recognition'
type: book_chapter
user_id: '15514'
year: 2019
...
---
_id: '4371'
abstract:
- lang: eng
text: 'A major challenge in modern data-centric medicine is the increasing amount
of time-dependent data, which requires efficient user-friendly solutions for dealing
with such data. To create an effective and efficient knowledge discovery process,
it is important to support common data manipulation tasks by creating quick, responsive
and intuitive interaction methods. In this paper we describe some methods for
interactive longitudinal data visualization with focus on the usage of mobile
multi-touch devices as interaction medium, based on our design and development
experiences. We argue that when it comes to longitudinal data this device category
offers remarkable additional interaction benefits compared to standard point-and-click
desktop computer devices. An important advantage of multi-touch devices arises
when interacting with particularly large longitudinal data sets: Complex, coupled
interactions such as zooming into a region and scrolling around almost simultaneously
is more easily achieved with the possibilities of a multi-touch device than compared
to a regular mouse-based interaction device.'
author:
- first_name: Andreas
full_name: Holzinger, Andreas
last_name: Holzinger
- first_name: Michael
full_name: Schwarz, Michael
last_name: Schwarz
- first_name: Bernhard
full_name: Ofner, Bernhard
last_name: Ofner
- first_name: Fleur
full_name: Jeanquartier, Fleur
last_name: Jeanquartier
- first_name: Andre
full_name: Calero-Valdez, Andre
last_name: Calero-Valdez
- first_name: Carsten
full_name: Röcker, Carsten
id: '61525'
last_name: Röcker
- first_name: Martina
full_name: Ziefle, Martina
last_name: Ziefle
citation:
ama: 'Holzinger A, Schwarz M, Ofner B, et al. Towards Interactive Visualization
of Longitudinal Data to Support Knowledge Discovery on Multi-Touch Tablet Computers.
In: Teufel S, Min TA, You I, Weippl E, eds. Availability, Reliability, and
Security in Information Systems . Vol 8708. Lecture Notes in Computer Science.
Cham: Springer; 2014:124-137. doi:10.1007/978-3-319-10975-6_9'
apa: 'Holzinger, A., Schwarz, M., Ofner, B., Jeanquartier, F., Calero-Valdez, A.,
Röcker, C., & Ziefle, M. (2014). Towards Interactive Visualization of Longitudinal
Data to Support Knowledge Discovery on Multi-Touch Tablet Computers. In S. Teufel,
T. A. Min, I. You, & E. Weippl (Eds.), Availability, Reliability, and
Security in Information Systems (Vol. 8708, pp. 124–137). Cham: Springer.
https://doi.org/10.1007/978-3-319-10975-6_9'
bjps: 'Holzinger A et al. (2014) Towards Interactive Visualization
of Longitudinal Data to Support Knowledge Discovery on Multi-Touch Tablet Computers.
In Teufel S et al. (eds), Availability, Reliability, and Security in Information
Systems , vol. 8708. Cham: Springer, pp. 124–137.'
chicago: 'Holzinger, Andreas, Michael Schwarz, Bernhard Ofner, Fleur Jeanquartier,
Andre Calero-Valdez, Carsten Röcker, and Martina Ziefle. “Towards Interactive
Visualization of Longitudinal Data to Support Knowledge Discovery on Multi-Touch
Tablet Computers.” In Availability, Reliability, and Security in Information
Systems , edited by Stephanie Teufel, Tjoa A Min, Ilsun You, and Edgar Weippl,
8708:124–37. Lecture Notes in Computer Science. Cham: Springer, 2014. https://doi.org/10.1007/978-3-319-10975-6_9.'
chicago-de: 'Holzinger, Andreas, Michael Schwarz, Bernhard Ofner, Fleur Jeanquartier,
Andre Calero-Valdez, Carsten Röcker und Martina Ziefle. 2014. Towards Interactive
Visualization of Longitudinal Data to Support Knowledge Discovery on Multi-Touch
Tablet Computers. In: Availability, Reliability, and Security in Information
Systems , hg. von Stephanie Teufel, Tjoa A Min, Ilsun You, und Edgar Weippl,
8708:124–137. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-319-10975-6_9,
.'
din1505-2-1: 'Holzinger, Andreas ;
Schwarz, Michael ; Ofner,
Bernhard ; Jeanquartier, Fleur
; Calero-Valdez, Andre ; Röcker,
Carsten ; Ziefle, Martina:
Towards Interactive Visualization of Longitudinal Data to Support Knowledge Discovery
on Multi-Touch Tablet Computers. In: Teufel,
S. ; Min, T. A. ; You,
I. ; Weippl, E. (Hrsg.):
Availability, Reliability, and Security in Information Systems , Lecture
Notes in Computer Science. Bd. 8708. Cham : Springer, 2014, S. 124–137'
havard: 'A. Holzinger, M. Schwarz, B. Ofner, F. Jeanquartier, A. Calero-Valdez,
C. Röcker, M. Ziefle, Towards Interactive Visualization of Longitudinal Data to
Support Knowledge Discovery on Multi-Touch Tablet Computers, in: S. Teufel, T.A.
Min, I. You, E. Weippl (Eds.), Availability, Reliability, and Security in Information
Systems , Springer, Cham, 2014: pp. 124–137.'
ieee: A. Holzinger et al., “Towards Interactive Visualization of Longitudinal
Data to Support Knowledge Discovery on Multi-Touch Tablet Computers,” in Availability,
Reliability, and Security in Information Systems , Fribourg, Switzerland,
2014, vol. 8708, pp. 124–137.
mla: Holzinger, Andreas, et al. “Towards Interactive Visualization of Longitudinal
Data to Support Knowledge Discovery on Multi-Touch Tablet Computers.” Availability,
Reliability, and Security in Information Systems , edited by Stephanie Teufel
et al., vol. 8708, Springer, 2014, pp. 124–37, doi:10.1007/978-3-319-10975-6_9.
short: 'A. Holzinger, M. Schwarz, B. Ofner, F. Jeanquartier, A. Calero-Valdez, C.
Röcker, M. Ziefle, in: S. Teufel, T.A. Min, I. You, E. Weippl (Eds.), Availability,
Reliability, and Security in Information Systems , Springer, Cham, 2014, pp. 124–137.'
ufg: 'Holzinger, Andreas et. al. (2014): Towards Interactive Visualization
of Longitudinal Data to Support Knowledge Discovery on Multi-Touch Tablet Computers,
in: Stephanie Teufel et. al. (Hgg.): Availability, Reliability, and Security
in Information Systems (=Lecture Notes in Computer Science 8708),
Cham, S. 124–137.'
van: 'Holzinger A, Schwarz M, Ofner B, Jeanquartier F, Calero-Valdez A, Röcker C,
et al. Towards Interactive Visualization of Longitudinal Data to Support Knowledge
Discovery on Multi-Touch Tablet Computers. In: Teufel S, Min TA, You I, Weippl
E, editors. Availability, Reliability, and Security in Information Systems .
Cham: Springer; 2014. p. 124–37. (Lecture Notes in Computer Science; vol. 8708).'
conference:
end_date: 2014-09-12
location: Fribourg, Switzerland
name: 5 International Cross-Domain Conference, CD-ARES 2014 and 4th International
Workshop on Security and Cognitive Informatics for Homeland Defense, SeCIHD 2014
start_date: 2014-09-08
date_created: 2021-01-14T10:13:18Z
date_updated: 2023-03-15T13:49:52Z
department:
- _id: DEP5023
doi: 10.1007/978-3-319-10975-6_9
editor:
- first_name: 'Stephanie '
full_name: 'Teufel, Stephanie '
last_name: Teufel
- first_name: 'Tjoa A '
full_name: 'Min, Tjoa A '
last_name: Min
- first_name: 'Ilsun '
full_name: 'You, Ilsun '
last_name: You
- first_name: 'Edgar '
full_name: 'Weippl, Edgar '
last_name: Weippl
intvolume: ' 8708'
keyword:
- Data Visualization
- Longitudinal Data
- Time Series
- Multi-Touch
- Mobile Computing
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
page: 124 - 137
place: Cham
publication: ' Availability, Reliability, and Security in Information Systems '
publication_identifier:
eisbn:
- 978-3-319-10975-6
isbn:
- 978-3-319-10974-9
publication_status: published
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: Towards Interactive Visualization of Longitudinal Data to Support Knowledge
Discovery on Multi-Touch Tablet Computers
type: conference
user_id: '15514'
volume: 8708
year: 2014
...