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Dominik Schuldhaus
University of Erlangen-Nuremberg
20Publications
8H-index
269Citations
Publications 20
Newest
Jul 1, 2018 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Stefan Grad (FAU: University of Erlangen-Nuremberg)
#2Markus Zrenner (FAU: University of Erlangen-Nuremberg)H-Index: 2
Last.Bjoern M. Eskofier (FAU: University of Erlangen-Nuremberg)H-Index: 18
view all 7 authors...
Wearable sensors are important in today’s athlete training ecosystems and also for the monitoring of therapeutic rehabilitation processes or even the diagnosis of diseases. In the future, wearables will be integrated directly into clothing and require dedicated, low-energy consuming algorithms that still maintain high accuracy. We developed a novel algorithm for the task of movement speed determination based on wearables that track only the acceleration of one foot. It consists of three algorith...
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Sep 12, 2016 in UbiComp (Ubiquitous Computing)
#1Christine F. Martindale (FAU: University of Erlangen-Nuremberg)H-Index: 5
#2Markus Wirth (FAU: University of Erlangen-Nuremberg)H-Index: 4
Last.Bjoern M. Eskofier (FAU: University of Erlangen-Nuremberg)H-Index: 18
view all 9 authors...
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Sep 12, 2016 in UbiComp (Ubiquitous Computing)
#2Markus WirthH-Index: 4
Last.Bjoern M. EskofierH-Index: 18
view all 9 authors...
Wearables are becoming mainstream technology, however there is still room for improvement in the sports domain of this field. Monitoring performance and collecting large scale data are of high interest among athletes - amateurs and professionals alike. The current state-of-the art wearable solutions for sports analysis are able to provide individual statistics to the user, however they have shortcomings in certain aspects, such as isolating and visualizing important information for the user, bey...
4 CitationsSource
Sep 12, 2016 in ISWC (International Symposium on Wearable Computers)
#1Dominik Schuldhaus (FAU: University of Erlangen-Nuremberg)H-Index: 8
#2Carolin Jakob (FAU: University of Erlangen-Nuremberg)H-Index: 3
Last.Bjoern M. Eskofier (FAU: University of Erlangen-Nuremberg)H-Index: 18
view all 5 authors...
Manually browsing through high amount of sports videos, selecting interesting highlight scenes, and applying video effects are time-consuming and one major burden these days. Automatic approaches are preferred, but currently require high-quality TV broadcast material which is usually not available in recreational sports. Thus, the purpose of this paper was to develop a personal low-cost movie producer for highlight videos using wearables. The feasibility of the proposed approach was shown for so...
2 CitationsSource
Sep 7, 2015 in ISWC (International Symposium on Wearable Computers)
#1Eva Dorschky (FAU: University of Erlangen-Nuremberg)H-Index: 3
#2Dominik Schuldhaus (FAU: University of Erlangen-Nuremberg)H-Index: 8
Last.Bjoern M. Eskofier (FAU: University of Erlangen-Nuremberg)H-Index: 18
view all 4 authors...
A considerable number of wearable system applications necessitate early event detection (EED). EED is defined as the detection of an event with as much lead time as possible. Applications include physiological (e.g., epileptic seizure or heart stroke) or biomechanical (e.g., fall movement or sports event) monitoring systems. EED for wearable systems is under-investigated in literature. Therefore, we introduce a novel EED framework for wearable systems based on hybrid Hidden Markov Models. Our st...
6 CitationsSource
Sep 7, 2015 in ISWC (International Symposium on Wearable Computers)
#1Peter Blank (FAU: University of Erlangen-Nuremberg)H-Index: 5
#2Julian Hoßbach (FAU: University of Erlangen-Nuremberg)H-Index: 1
Last.Bjoern M. Eskofier (FAU: University of Erlangen-Nuremberg)H-Index: 18
view all 4 authors...
In this paper we present a sensor-based table tennis stroke detection and classification system. We attached inertial sensors to table tennis rackets and collected data of 8 different basic stroke types from 10 amateur and professional players. Firstly, single strokes were detected by a event detection algorithm. Secondly, features were computed and used as input for stroke type classification. Multiple classifiers were compared regarding classification rates and computational effort. The overal...
17 CitationsSource
#1Jens BarthH-Index: 10
Last.Björn EskofierH-Index: 11
view all 11 authors...
Changes in gait patterns provide important information about individuals’ health. To perform sensor based gait analysis, it is crucial to develop methodologies to automatically segment single strides from continuous movement sequences. In this study we developed an algorithm based on time-invariant template matching to isolate strides from inertial sensor signals. Shoe-mounted gyroscopes and accelerometers were used to record gait data from 40 elderly controls, 15 patients with Parkinson’s disea...
61 CitationsSource
#1Dominik Schuldhaus (FAU: University of Erlangen-Nuremberg)H-Index: 8
#2Heike Leutheuser (FAU: University of Erlangen-Nuremberg)H-Index: 9
Last.Bjoern M. Eskofier (FAU: University of Erlangen-Nuremberg)H-Index: 18
view all 3 authors...
Activity recognition is mandatory in order to provide feedback about the individual quality of life. Usually, activity recognition algorithms are evaluated on one specific database which is limited in the number of subjects, sensors and type of activities. In this paper, a novel database fusion strategy was proposed which fused three different publicly available databases to one large database consisting of 42 subjects. The fusion of databases addresses the two attributes high volume and high va...
7 CitationsSource
#1Peter Blank (FAU: University of Erlangen-Nuremberg)H-Index: 5
#2Patrick Kugler (FAU: University of Erlangen-Nuremberg)H-Index: 13
Last.Bjoern M. Eskofier (FAU: University of Erlangen-Nuremberg)H-Index: 18
view all 4 authors...
Wearable body sensors have become an important basis for today's medical and fitness applications. To assist athletes or to take care of elderly people in everyday life situations, sensor data can be collected and processed to give helpful feedback. However, the data collection process of multiple or different sensor systems still had to be done manually by the user or an expert, which usually takes a lot of time and can lead to errors. This paper presents an embedded data collection and communi...
1 CitationsSource
Jun 16, 2014 in BSN (Wearable and Implantable Body Sensor Networks)
#1Robert RicherH-Index: 4
#2Peter BlankH-Index: 5
Last.Bjoern M. EskofierH-Index: 18
view all 4 authors...
We developed an application for Android-based mobile devices that enables a real-time calculation of heart rate and cadence for biking. Therefore, both ECG and EMG data are acquired in real time by Shimmer sensors and transmitted via Bluetooth, as well as processed and evaluated on the mobile device. The ECG algorithm is based on the Pan-Tompkins algorithm for QRS-Detection and offers a heart beat detection rate of more than 94%. The EMG algorithm offers a treadle detection rate of more than 91%...
9 CitationsSource
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