Bjoern M. Eskofier is German Research Foundation (DFG) funded Heisenberg-Professor for "Digital Support Systems in Sports and Medical Engineering". He heads the Machine Learning and Data Analytics Lab and the Central Institute for Medical Engineering at the Friedrich-Alexander-University Erlangen-Nuernberg (FAU). Currently, his lab has 40 co-workers, who do research in machine learning for wearable systems with applications in sports and health care. Dr. Eskofier authored more than 180 peer reviewed articles, submitted 6 patent applications, started three spinoff startup companies, and won several medical-technical research awards. He was a visiting professor at Harvard Medical School (2016) and MIT (2018). His research and entrepreneurial agenda revolves around contributions to a Digital Health Ecosystem, where patients are connected to other stakeholders within the Healthcare system using digital support tools. Supervisors: Dr. Benno Nigg and Dr. Joachim Hornegger
Long-term studies in rodents are the benchmark method to assess carcinogenicity of single substan... more Long-term studies in rodents are the benchmark method to assess carcinogenicity of single substances, mixtures, and multi-compounds. In such a study, mice and rats are exposed to a test agent at different dose levels for a period of two years and the incidence of neoplastic lesions is observed. However, this two-year study is also expensive, time-consuming, and burdensome to the experimental animals. Consequently, various alternatives have been proposed in the literature to assess carcinogenicity on basis of short-term studies. In this paper, we investigated if effects on the rodents' liver weight in short-term studies can be exploited to predict the incidence of liver tumors in long-term studies. A set of 138 paired short- and long-term studies was compiled from the database of the U.S. National Toxicology Program (NTP), more precisely, from (long-term) two-year carcinogenicity studies and their preceding (short-term) dose finding studies. In this set, data mining methods revea...
ABSTRACT In many sports and medical applications small and wearable sensors are used that capture... more ABSTRACT In many sports and medical applications small and wearable sensors are used that capture motion and physiological signals. Yet, commonly such sensor are only capable of acquiring raw data, which is afterwards transmitted to a smartphone or other mobile computing device where processing and classification is carried out. This results in limited usability because another device has to be worn. Moreover, high power consumption due to continuous transmission is a main disadvantage. Therefore, we propose a smart sensor approach that can alleviate these problems by carrying out the processing on the sensor itself. To house the processing schemes in the sensor node we developed a new computer architecture utilizing an FPGA and an ASIC. To show the benefits of the in-sensor processing, we chose two representative biosensor applications: a movement and fall detection system for the elderly and a swimming style recognition system for professional athletes. Compared to conventional approaches the same classification rate can be achieved while saving space, power, weight and setup costs.
Abstract Embedded microcontrollers are employed in an increasing number of applications as a targ... more Abstract Embedded microcontrollers are employed in an increasing number of applications as a target for the implementation of classification systems. This is true for example for the fields of sports, automotive and medical engineering. However, important challenges arise when implementing classification systems on embedded microcontrollers, which is mainly due to limited hardware resources.
With the increase of computational power in the last decades, tracking of objects or human beings... more With the increase of computational power in the last decades, tracking of objects or human beings has become a growing research area in the image processing and engineering fields. Its applications range from military and security to medicine and sports. In particular, tracking applications in sports have the main purpose of extracting useful information for the analysis of a player's or team's performance through video analysis based on statistical measures (Kristan et al. 2009).
Abstract Embedded mobile systems for analysis and classification become more and more important i... more Abstract Embedded mobile systems for analysis and classification become more and more important in the field of sports and sports science. Small and lightweight sensors in sportswear offer the possibility to monitor the athletes in a realistic environment, eg during an outdoor run. During the activity, the sportswear can automatically adapt to the current environment and hence optimizes the performance of the athlete. A major need is a running shoe, which can automatically be adapted to the current ground.
Abstract: Dieser Artikel beschreibt die Anwendung eines tragbaren Sensor-Netzwerks im Feedback-Tr... more Abstract: Dieser Artikel beschreibt die Anwendung eines tragbaren Sensor-Netzwerks im Feedback-Training am Beispiel von Kniebeugen. Hierzu wurden zwei Sensorknoten mit integrierten Beschleunigungssensoren genutzt, um den Knie-Winkel von 5 Probanden zu messen und direkt anzuzeigen. Diese berechneten Winkel zeigten im Vergleich zu einer Videoanalyse eine hohe Korrelation von 0.96. Das Feedback selbst hatte einen messbaren Effekt auf die Ubungsdurchführung der Probanden.
Abstract The measurement of video quality for lossy and low-bitrate network transmissions is a ch... more Abstract The measurement of video quality for lossy and low-bitrate network transmissions is a challenging topic. Especially, the temporal artifacts which are introduced by video transmission systems and their effects on the viewer's satisfaction have to be addressed. This paper focuses on a framework that adds a temporal distortion awareness to typical video quality measurement algorithms. A motion estimation is used to track image areas over time.
Abstract In the evaluation of video quality often a full reference approach is used, thus calcula... more Abstract In the evaluation of video quality often a full reference approach is used, thus calculating some measure of difference between the reference frames and the distorted frames. Often this measure returns one value per pixel, in the simplest case the squared difference. Conventionally, this pixel based measure is averaged over space and time. This paper introduces a psychophysically derived algorithm for this step.
Long-term studies in rodents are the benchmark method to assess carcinogenicity of single substan... more Long-term studies in rodents are the benchmark method to assess carcinogenicity of single substances, mixtures, and multi-compounds. In such a study, mice and rats are exposed to a test agent at different dose levels for a period of two years and the incidence of neoplastic lesions is observed. However, this two-year study is also expensive, time-consuming, and burdensome to the experimental animals. Consequently, various alternatives have been proposed in the literature to assess carcinogenicity on basis of short-term studies. In this paper, we investigated if effects on the rodents' liver weight in short-term studies can be exploited to predict the incidence of liver tumors in long-term studies. A set of 138 paired short- and long-term studies was compiled from the database of the U.S. National Toxicology Program (NTP), more precisely, from (long-term) two-year carcinogenicity studies and their preceding (short-term) dose finding studies. In this set, data mining methods revea...
ABSTRACT In many sports and medical applications small and wearable sensors are used that capture... more ABSTRACT In many sports and medical applications small and wearable sensors are used that capture motion and physiological signals. Yet, commonly such sensor are only capable of acquiring raw data, which is afterwards transmitted to a smartphone or other mobile computing device where processing and classification is carried out. This results in limited usability because another device has to be worn. Moreover, high power consumption due to continuous transmission is a main disadvantage. Therefore, we propose a smart sensor approach that can alleviate these problems by carrying out the processing on the sensor itself. To house the processing schemes in the sensor node we developed a new computer architecture utilizing an FPGA and an ASIC. To show the benefits of the in-sensor processing, we chose two representative biosensor applications: a movement and fall detection system for the elderly and a swimming style recognition system for professional athletes. Compared to conventional approaches the same classification rate can be achieved while saving space, power, weight and setup costs.
Abstract Embedded microcontrollers are employed in an increasing number of applications as a targ... more Abstract Embedded microcontrollers are employed in an increasing number of applications as a target for the implementation of classification systems. This is true for example for the fields of sports, automotive and medical engineering. However, important challenges arise when implementing classification systems on embedded microcontrollers, which is mainly due to limited hardware resources.
With the increase of computational power in the last decades, tracking of objects or human beings... more With the increase of computational power in the last decades, tracking of objects or human beings has become a growing research area in the image processing and engineering fields. Its applications range from military and security to medicine and sports. In particular, tracking applications in sports have the main purpose of extracting useful information for the analysis of a player's or team's performance through video analysis based on statistical measures (Kristan et al. 2009).
Abstract Embedded mobile systems for analysis and classification become more and more important i... more Abstract Embedded mobile systems for analysis and classification become more and more important in the field of sports and sports science. Small and lightweight sensors in sportswear offer the possibility to monitor the athletes in a realistic environment, eg during an outdoor run. During the activity, the sportswear can automatically adapt to the current environment and hence optimizes the performance of the athlete. A major need is a running shoe, which can automatically be adapted to the current ground.
Abstract: Dieser Artikel beschreibt die Anwendung eines tragbaren Sensor-Netzwerks im Feedback-Tr... more Abstract: Dieser Artikel beschreibt die Anwendung eines tragbaren Sensor-Netzwerks im Feedback-Training am Beispiel von Kniebeugen. Hierzu wurden zwei Sensorknoten mit integrierten Beschleunigungssensoren genutzt, um den Knie-Winkel von 5 Probanden zu messen und direkt anzuzeigen. Diese berechneten Winkel zeigten im Vergleich zu einer Videoanalyse eine hohe Korrelation von 0.96. Das Feedback selbst hatte einen messbaren Effekt auf die Ubungsdurchführung der Probanden.
Abstract The measurement of video quality for lossy and low-bitrate network transmissions is a ch... more Abstract The measurement of video quality for lossy and low-bitrate network transmissions is a challenging topic. Especially, the temporal artifacts which are introduced by video transmission systems and their effects on the viewer's satisfaction have to be addressed. This paper focuses on a framework that adds a temporal distortion awareness to typical video quality measurement algorithms. A motion estimation is used to track image areas over time.
Abstract In the evaluation of video quality often a full reference approach is used, thus calcula... more Abstract In the evaluation of video quality often a full reference approach is used, thus calculating some measure of difference between the reference frames and the distorted frames. Often this measure returns one value per pixel, in the simplest case the squared difference. Conventionally, this pixel based measure is averaged over space and time. This paper introduces a psychophysically derived algorithm for this step.
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Papers by Bjoern Eskofier