Bjoern M Eskofier

Bjoern M Eskofier
Friedrich-Alexander-University of Erlangen-Nürnberg | FAU · Department of Computer Science

PhD

About

384
Publications
110,779
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6,544
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Introduction
I studied Electrical Engineering at the Friedrich-Alexander University (FAU) Erlangen-Nuernberg (Germany). I did my PhD in Biomechanics in 2010 at the University of Calgary (“Application of Pattern Recognition Methods in Biomechanics”). In 2011, I became assistant professor for Computer Science in Sports (an endowed professorship of the adidas AG). In 2017, I became full professor for 'Digital Support Systems in Sports and Health' within the Heisenberg-program of the German Research Foundation (DFG). I am heading the Machine Learning and Data Analytics Lab of the FAU. Currently, this lab has 25 co-workers, working in the fields of machine learning and signal analysis for wearable computing systems with a focus on sports and health care.
Additional affiliations
March 2017 - March 2017
Friedrich-Alexander-University of Erlangen-Nürnberg
Position
  • Professor (Full)

Publications

Publications (384)
Article
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Developing machine learning algorithms for time-series data often requires manual annotation of the data. To do so, graphical user interfaces (GUIs) are an important component. Existing Python packages for annotation and analysis of time-series data have been developed without addressing adaptability, usability, and user experience. Therefore, we d...
Preprint
Optimal control simulations of musculoskeletal models can be used to reconstruct motions measured with optical motion capture to estimate joint and muscle kinematics and kinetics. These simulations are mutually and dynamically consistent, in contrast to traditional inverse methods. Commonly, optimal control simulations are generated by tracking gen...
Article
Full-text available
Efficient handwriting trajectory reconstruction (TR) requires specific writing surfaces for detecting movements of digital pens. Although several motion-based solutions have been developed to remove the necessity of writing surfaces, most of them are based on classical sensor fusion methods limited, by sensor error accumulation over time, to tracin...
Article
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Introduction Rheport is an online rheumatology referral system allowing automatic appointment triaging of new rheumatology patient referrals according to the respective probability of an inflammatory rheumatic disease (IRD). Previous research reported that Rheport was well accepted among IRD patients. Its accuracy was, however, limited, currently b...
Article
Falls are among the leading causes of injuries or death for individuals from the age of 65 and the prevalence of falls is especially high for patients suffering from neurological diseases like Parkinson's disease (PD). Due to advancements in wearable sensor technology, inertial measurement units (IMUs) can be integrated unobtrusively into patients'...
Article
Full-text available
Objective: Clinical urine tests are a key component of prenatal care. As of now, urine test strips are evaluated through a time consuming, often error-prone and operator-dependent visual color comparison of test strips and reference cards by medical staff. Methods and procedures: This work presents an automated pipeline for urinalysis with urine...
Article
Monitoring stress is relevant in many areas, including sports science. In that scope, various studies showed the feasibility of stress classification using eye tracking data. In most cases, the screen-based experimental design restricted the motion of participants. Consequently, the transferability of results to dynamic sports applications remains...
Chapter
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This paper describes the Digital Responsibility Goals, their purpose, and the associated guiding criteria and their relevance particularly for health. In addition, the document makes a first proposal for measuring digital responsibility.
Article
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Indoor localization and human activity recognition are two important sources of information to provide context-based assistance. This information is relevant in ambient assisted living (AAL) scenarios, where older adults usually need supervision and assistance in their daily activities. However, indoor localization and human activity recognition ha...
Article
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In human activity recognition har(human activity recognition (HAR)), activities are automatically recognized and classified from a continuous stream of input sensor data. Although the scientific community has developed multiple approaches for various sports in recent years, marginal sports are rarely considered. These approaches cannot directly be...
Article
Healthcare 4.0 is a new concept that originates from the evolution of hospitals due to technological advances in medical activities. Nowadays, more and more doctors and healthcare administrators require real-time data analysis obtained from sensors and surgery monitoring. Using real-time information could make the difference between death and life...
Preprint
Autonomous driving has the potential to revolutionize mobility and is hence an active area of research. In practice, the behavior of autonomous vehicles must be acceptable, i.e., efficient, safe, and interpretable. While vanilla reinforcement learning (RL) finds performant behavioral strategies, they are often unsafe and uninterpretable. Safety is...
Preprint
Many scenarios in mobility and traffic involve multiple different agents that need to cooperate to find a joint solution. Recent advances in behavioral planning use Reinforcement Learning to find effective and performant behavior strategies. However, as autonomous vehicles and vehicle-to-X communications become more mature, solutions that only util...
Preprint
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Chronic stress is linked to dysregulations of the two major stress pathways – the sympathetic nervous system (SNS) and the hypothalamic-pituitary-adrenal (HPA) axis, which could for example result from maladaptive responses to repeated acute stress. Improving recovery from acute stress could therefore help to prevent this dysregulation. One possibi...
Article
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Purpose We assess feasibility of wearable gait analysis in geriatric wards by testing the effectiveness and acceptance of the system. Methods Gait parameters of 83 patients (83.34 ± 5.88 years, 58/25 female/male) were recorded at admission and/or discharge to/from two geriatric inpatient wards. Gait parameters were tested for statistically signifi...
Article
Background Fitness trackers and smart watches are frequently used to collect data in longitudinal medical studies. They allow continuous recording in real-life settings, potentially revealing previously uncaptured variabilities of biophysiological parameters and diseases. Adequate device accuracy is a prerequisite for meaningful research. Objectiv...
Article
This work proposes metric learning for fast similarity-based scene retrieval of unstructured ensembles of trajectory data from large databases. We present a novel representation learning approach using Siamese Metric Learning that approximates a distance preserving low-dimensional representation and that learns to estimate reasonable solutions to t...
Article
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The visual depth perception is composed of monocular and binocular depth cues. Studies show that in absence of binocular depth cues the performance of visuomotor tasks like pointing to or grasping objects is limited. Thus, binocular depth cues are of great importance for motor control required in everyday life. However, binocular depth cues like re...
Article
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Different control strategies are available for human machine interfaces based on electromyography (EMG) to map voluntary muscle signals to control signals of a remote controlled device. Complex systems such as robots or multi-fingered hands require a natural commanding, which can be realized with proportional and simultaneous control schemes. Machi...
Article
The use of machine learning (ML) with electronic health records (EHR) is growing in popularity as a means to extract knowledge that can improve the decision-making process in healthcare. Such methods require training of high-quality learning models based on diverse and comprehensive datasets, which are hard to obtain due to the sensitive nature of...
Article
Background: Multiple sclerosis (MS) is a chronic autoimmune inflammatory disease of the central nervous system, affecting more than 2.3 million people worldwide. Fatigue is among the most common symptoms in MS, resulting in reduced mobility and quality of life. The six-minute walking test (6MWT) is commonly used as a measure of fatigability for the...
Conference Paper
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The adoption of artificial intelligence (AI) within organizations is experiencing growing interest. Since AI has distinctive characteristics (automation – augmentation), it is unclear how both characteristics influence the adoption. Besides, current research calls for a configurational perspective within the adoption theory. Building on these resea...
Article
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For sports scientists and coaches, its crucial to have reliable tracking systems to improve athletes. Therefore, this study aimed to examine the validity of a wearable real-time tracking system (WRRTS) for the quantification of ski jumping. The tracking system consists of wearable trackers attached to the ski bindings of the athletes and fixed ante...
Article
Full-text available
Digital technologies provide the opportunity to analyze gait patterns in patients with Parkinson’s Disease using wearable sensors in clinical settings and a home environment. Confirming the technical validity of inertial sensors with a 3D motion capture system is a necessary step for the clinical application of sensor-based gait analysis. Therefore...
Article
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Patient-centered health care information systems (PHSs) enable patients to take control and become knowledgeable about their own health, preferably in a secure environment. Current and emerging PHSs use either a centralized database, peer-to-peer (P2P) technology, or distributed ledger technology for PHS deployment. The evolving COVID-19 decentrali...
Conference Paper
Strabismus is a visual disorder characterized by eye misalignment. The extent of ocular misalignment is denoted as the deviation angle. With the advent of Virtual Reality (VR) Head-Mounted-Displays (HMD) and eye tracking technology, new possibilities measuring strabismus arise. Major research addresses the novel field of VR strabismus assessment by...
Conference Paper
Digital gait measures derived from wearable inertial sensors have been shown to support the treatment of patients with motor impairments. From a technical perspective, the detection of left and right initial foot contacts (ICs) is essential for the computation of stride-by-stride outcome measures including gait asymmetry. However, in a majority of...
Conference Paper
Driven by the advancements of wearable sensors and signal processing algorithms, studies on continuous real-world monitoring are of major interest in the field of clinical gait and motion analysis. While real-world studies enable a more detailed and realistic insight into various mobility parameters such as walking speed, confounding and environmen...
Conference Paper
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As global life expectancy is constantly rising, the early detection of age-related, neurodegenerative diseases, such as Parkinson's disease, is becoming increasingly important. Patients suffering from Parkinson's disease often show autonomic nervous system dysfunction which is why its examination is an important diagnostic tool. Measuring the respo...
Article
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Smart sensors are an integral part of the Fourth Industrial Revolution and are widely used to add safety measures to human–robot interaction applications. With the advancement of machine learning methods in resource-constrained environments, smart sensor systems have become increasingly powerful. As more data-driven approaches are deployed on the s...
Preprint
BACKGROUND Besides anti-inflammatory medication, physical exercise represents a cornerstone of modern treatment for patients with Axial Spondylarthritis (AS). Digital health applications (DHA) like the Yoga App "YogiTherapy" could empower patients to autonomously and correctly perform exercises remotely. OBJECTIVE This study aimed to develop, desi...
Article
Background: Besides anti-inflammatory medication, physical exercise represents a cornerstone of modern treatment for patients with axial spondyloarthritis (AS). Digital health apps (DHAs) such as the yoga app YogiTherapy could remotely empower patients to autonomously and correctly perform exercises. Objective: This study aimed to design and dev...
Article
Full-text available
Gait tests as part of home monitoring study protocols for patients with movement disorders may provide valuable standardized anchor-points for real-world gait analysis using inertial measurement units (IMUs). However, analyzing unsupervised gait tests relies on reliable test annotations by the patients requiring a potentially error-prone interactio...
Article
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Climbing stairs is a fundamental part of daily life, adding additional demands on the postural control system compared to level walking. Although real-world gait analysis studies likely contain stair ambulation sequences, algorithms dedicated to the analysis of such activities are still missing. Therefore, we propose a new gait analysis pipeline fo...
Conference Paper
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Artificial Intelligence (AI) as an emerging technology is increasingly applied in the healthcare sector. Moreover, the AI-related progress and technology application is not only driven by traditional companies but even more by the establishment of small and medium-sized enterprises (SME) in healthcare, the innovation process as well as dynamic prod...
Preprint
BACKGROUND Fitness trackers and smart watches are frequently used to collect data in longitudinal medical studies. They allow continuous recording in real-life settings, potentially revealing previously uncaptured variabilities of biophysiological parameters and diseases. Adequate device accuracy is a prerequisite for meaningful research. OBJECTIV...
Article
Full-text available
The most important goal of customer service is to keep the customer satisfied. However, service resources are always limited and must prioritize specific customers. Therefore, it is essential to identify customers who potentially become unsatisfied and might lead to escalations. Data science on IoT data (especially log data) for machine health moni...
Article
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Digital mobility assessment using wearable sensor systems has the potential to capture walking performance in a patient’s natural environment. It enables monitoring of health status and disease progression and evaluation of interventions in real-world situations. In contrast to laboratory settings, real-world walking occurs in non-conventional envi...
Article
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Editorial on the Research Topic Wearable and Implantable Technologies in the Rehabilitation of Patients With Sensory Impairments
Conference Paper
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The vulnerability of deep neural networks to small and even imperceptible perturbations has become a central topic in deep learning research. Although several sophisticated defense mechanisms have been introduced, most were later shown to be ineffective. However, a reliable evaluation of model robustness is mandatory for deployment in safety-critic...
Article
Full-text available
Background To objectively assess a patient’s gait, a robust identification of stride borders is one of the first steps in inertial sensor-based mobile gait analysis pipelines. While many different methods for stride segmentation have been presented in the literature, an out-of-lab evaluation of respective algorithms on free-living gait is still mis...
Article
Full-text available
Maximizing performance success in sports is about continuous learning and adaptation processes. Aside from physiological, technical and emotional performance factors, previous research focused on perceptual skills, revealing their importance for decision-making. This includes deriving relevant environmental information as a result of eye, head and...
Preprint
Full-text available
Most online handwriting recognition systems require the use of specific writing surfaces to extract positional data. In this paper we present a online handwriting recognition system for word recognition which is based on inertial measurement units (IMUs) for digitizing text written on paper. This is obtained by means of a sensor-equipped pen that p...
Article
Full-text available
Objective: Finishing a marathon requires to prepare for a 42.2 km run. Current literature describes which training characteristics are related to marathon performance. However, which training is most effective in terms of a performance improvement remains unclear. Methods: We conducted a retrospective analysis of training responses during a 16 week...
Preprint
Full-text available
Progress in making neural networks more robust against adversarial attacks is mostly marginal, despite the great efforts of the research community. Moreover, the robustness evaluation is often imprecise, making it difficult to identify promising approaches. We analyze the classification decisions of 19 different state-of-the-art neural networks tra...
Article
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Background Gait impairment is a pivotal feature of parkinsonian syndromes and increased gait variability is associated with postural instability and a higher risk of falls. Objectives We compared gait variability at different walking velocities between and within groups of patients with Parkinson-variant multiple system atrophy, idiopathic Parkins...
Article
Full-text available
The applicability of sensor-based human activity recognition in sports has been repeatedly shown for laboratory settings. However, the transferability to real-world scenarios cannot be granted due to limitations on data and evaluation methods. On the example of football shot and pass detection against a null class we explore the influence of those...
Chapter
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Predictive business process monitoring (PBPM) aims to predict future process behavior during ongoing process executions based on event log data. Especially, techniques for the next activity and timestamp prediction can help to improve the performance of operational business processes. Recently, many PBPM solutions based on deep learning were propos...
Preprint
Full-text available
The susceptibility of deep neural networks to untrustworthy predictions, including out-of-distribution (OOD) data and adversarial examples, still prevent their widespread use in safety-critical applications. Most existing methods either require a re-training of a given model to achieve robust identification of adversarial attacks or are limited to...
Preprint
Full-text available
Involuntary subject motion is the main source of artifacts in weight-bearing cone-beam CT of the knee. To achieve image quality for clinical diagnosis, the motion needs to be compensated. We propose to use inertial measurement units (IMUs) attached to the leg for motion estimation. We perform a simulation study using real motion recorded with an op...
Preprint
Full-text available
Background: To objectively assess a patient's gait, a robust identification of stride borders is one of the first steps in inertial sensor-based mobile gait analysis pipelines. While many different methods for stride segmentation have been presented in the literature, an out-of-lab evaluation of respective algorithms on free-living gait is still mi...