Bert Arnrich

Bert Arnrich
Hasso Plattner Institute · Digital Health – Connected Healthcare

Professor

About

188
Publications
69,819
Reads
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4,029
Citations
Citations since 2016
70 Research Items
2866 Citations
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Introduction
I'm looking for Doctoral Students (Ph.D.) / Postdoctoral Researchers in Digital Health with emphasis on Connected Health for our new lab. Find all details and how to apply from here: https://hpi.de/das-hpi/organisation/jobs/aktuelle-jobs/digital-health-center/doctoral-students-postdoctoral-researchers-in-digital-health-connected-health.html
Additional affiliations
August 2006 - April 2013
ETH Zurich
January 2002 - May 2006
Bielefeld University

Publications

Publications (188)
Preprint
Full-text available
Federated learning (FL) is getting increased attention for processing sensitive, distributed datasets common to domains such as healthcare. Instead of directly training classification models on these datasets, recent works have considered training data generators capable of synthesising a new dataset which is not protected by any privacy restrictio...
Preprint
Full-text available
Purpose: Increasing digitalisation in the medical domain gives rise to large amounts of healthcare data which has the potential to expand clinical knowledge and transform patient care if leveraged through artificial intelligence (AI). Yet, big data and AI oftentimes cannot unlock their full potential at scale, owing to non-standardised data formats...
Preprint
BACKGROUND Increasing digitalisation in the medical domain gives rise to large amounts of healthcare data which has the potential to expand clinical knowledge and transform patient care if leveraged through artificial intelligence (AI). Yet, big data and AI oftentimes cannot unlock their full potential at scale, owing to non-standardised data forma...
Article
Neural networks have been successfully applied to a wide range of human motion analysis topics in combination with wearable sensor data. However, their computation process is not readily comprehensible. Alternatively, many of the model interpretation efforts do not provide physiologically-relevant insights, thus still limiting their use in clinical...
Article
Full-text available
Patient monitoring technology has been used to guide therapy and alert staff when a vital sign leaves a predefined range in the intensive care unit (ICU) for decades. However, large amounts of technically false or clinically irrelevant alarms provoke alarm fatigue in staff leading to desensitisation towards critical alarms. With this systematic rev...
Article
Full-text available
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against data privacy attacks. To the best of our knowledge,...
Article
Full-text available
Quantifying neurological disorders from voice is a rapidly growing field of research and holds promise for unobtrusive and large-scale disorder monitoring. The data recording setup and data analysis pipelines are both crucial aspects to effectively obtain relevant information from participants. Therefore, we performed a systematic review to provide...
Preprint
Full-text available
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against privacy attacks on DenseNet121 and ResNet50 network...
Conference Paper
Full-text available
To monitor diet, nutritionists employ food journaling approaches, which rely on the subject’s memory. Accordingly, a real-time reminder during eating can help subjects adhere to a journaling routine more strictly. Although previous works used sensors to detect eating activities, no study accounted for the time impact of delivering notifications. Ou...
Article
Full-text available
Observational studies are an important tool for determining whether the findings from controlled experiments can be transferred into scenarios that are closer to subjects’ real-life circumstances. A rigorous approach to observational studies involves collecting data from different sensors to comprehensively capture the situation of the subject. How...
Preprint
Full-text available
Federated learning allows a group of distributed clients to train a common machine learning model on private data. The exchange of model updates is managed either by a central entity or in a decentralized way, e.g. by a blockchain. However, the strong generalization across all clients makes these approaches unsuited for non-independent and identica...
Conference Paper
Full-text available
One of the benefits of Do-it-yourself Artificial Pancreas Systems (DIYAPS) over commercially available systems is the high degree of customization possible through various features developed by the community. This paper investigates the impact of thirteen commonly used custom features on the glycemic outcomes of users with type 1 diabetes. Signific...
Conference Paper
In emergency medicine, workforce planning needs to satisfy a number of constraints. There are hard constraints regarding qualifications and soft constraints regarding the wishes of the personnel. One instance of such a planning problem is the assignment of lifeguards at the coasts of the North Sea and the Baltic Sea in Germany. These lifeguards are...
Conference Paper
Pancreatic surgery is associated with a high risk for postoperative complications and death of patients. Complications occur in a variable interval after the procedure. Often, a patient has already left the ICU and is not properly monitored anymore when the complication occurs. Risk stratification models can assist in identifying patients at risk i...
Conference Paper
Full-text available
Improving the security of the Internet of things is one of the most important and critical issues facing the modern world. With the rapid development and widespread use of the Internet of things, the ability of these devices to communicate securely without compromising their performance is a major challenge. The majority of these devices are limite...
Article
Full-text available
Wearable devices can track a multitude of parameters such as heart rate, body temperature, blood oxygen saturation, acceleration, blood glucose and many more (Kamišalić et al., 2018). Moreover, they are becoming increasingly popular with a steep increase in market presence in 2020 alone (IDC, 2020). Applications for wearable devices vary from track...
Conference Paper
Full-text available
With the COVID-19 pandemic, several research teams have reported successful advances in automated recognition of COVID-19 by voice. Resulting voice-based screening tools for COVID-19 could support large-scale testing efforts. While capabilities of machines on this task are progressing, we approach the so far unexplored aspect whether human raters c...
Article
Full-text available
Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for tr...
Article
Detection of the QRS complex is a long-standing topic in the context of electrocardiography and many algorithms build upon the knowledge of the QRS positions. Although the first solutions to this problem were proposed in the 1970s and 1980s, there is still potential for improvements. Advancements in neural network technology made in recent years al...
Article
Full-text available
Background Wearable devices are designed to capture health-related and physiological data. They may be able to improve inflammatory bowel disease management and address evolving research needs. Little is known about patient perceptions for their use in the study and management of inflammatory bowel disease.AimsThe aim of this survey study is to und...
Article
Full-text available
Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for tr...
Article
Full-text available
Recent trends in ubiquitous computing have led to a proliferation of studies that focus on human activity recognition (HAR) utilizing inertial sensor data that consist of acceleration, orientation and angular velocity. However, the performances of such approaches are limited by the amount of annotated training data, especially in fields where annot...
Conference Paper
Human Activity Recognition (HAR) of everyday activities using smartphones has been intensively researched over the past years. Despite the high detection performance, smartphones can not continuously provide reliable information about the currently conducted activity as their placement at the subject’s body is uncertain. In this study, a system is...
Article
Full-text available
Background Differences in autonomic nervous system function, measured by heart rate variability (HRV), have been observed between patients with inflammatory bowel disease and healthy control patients and have been associated in cross-sectional studies with systemic inflammation. High HRV has been associated with low stress. Methods Patients with u...
Article
Full-text available
Recent trends in ubiquitous computing have led to a proliferation of studies that focus on human activity recognition (HAR) utilizing inertial sensor data that consist of acceleration, orientation and angular velocity. However, the performances of such approaches are limited by the amount of annotated training data, especially in fields where annot...
Article
Full-text available
Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection...
Conference Paper
Full-text available
Prolonged sitting behavior and postures that cause strain on the spine and muscles have been reported to increase the probability of low back pain. To address this issue, many commercially available sensors already provide feedback about whether a person is 'slouching' or 'not slouching'. However, they do not provide information on a person's postu...
Article
The state of the art for monitoring hypertension relies on measuring blood pressure (BP) using uncomfortable cuff-based devices. Hence, for increased adherence in monitoring, a better way of measuring BP is needed. That could be achieved through comfortable wearables that contain photoplethysmography (PPG) sensors. There have been several studies s...
Article
Full-text available
Gait analysis is an important tool for the early detection of neurological diseases and for the assessment of risk of falling in elderly people. The availability of low-cost camera hardware on the market today and recent advances in Machine Learning enable a wide range of clinical and health-related applications, such as patient monitoring or exerc...
Preprint
BACKGROUND Background: Prolonged sitting postures have been reported to increase the probability of developing low back pain. Moreover, the majority of employees in the industrial world work ninety percent of their time in a seated position. OBJECTIVE This review focuses on the technologies and algorithms that have been used to classify seating po...
Preprint
Data privacy is a very important issue. Especially in fields like medicine, it is paramount to abide by the existing privacy regulations to preserve patients' anonymity. On the other hand, data is required for research and training machine learning models that could help gain insight into complex correlations or personalised treatments that may oth...
Article
Full-text available
Background: A majority of employees in the industrial world spend most of their work time in a seated position. Monitoring sitting postures can provide insights into underlying causes of occupational discomforts such as low back pain. Objective: This review focuses on the technologies and algorithms used to classify sitting postures on a chair wit...
Article
Full-text available
Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection...
Conference Paper
Full-text available
Gait is an essential function for humans, and gait patterns in daily life provide meaningful information about a person’s cognitive and physical health conditions. Inertial measurement units (IMUs) have emerged as a promising tool for low-cost, unobtrusive gait analysis. However, large varieties of IMU gait analysis algorithms and the lack of conse...
Preprint
Full-text available
The state of the art for monitoring hypertension relies on measuring blood pressure (BP) using uncomfortable cuff-based devices. Hence, for increased adherence in monitoring, a better way of measuring BP is needed. That could be achieved through comfortable wearables that contain photoplethysmography (PPG) sensors. There have been several studies s...
Conference Paper
Full-text available
The quarantine situation inflicted by the COVID-19 pandemic has left many people around the world isolated at home. Despite the large variety of mobile device-based self exercise tools for training plans, activity recognition or repetition counts, it remains challenging for an inexperienced person to perform fitness workouts or learn a new sport wi...
Article
Full-text available
Activity recognition systems utilise data from sensors in mobile, environmental and wearable devices, ubiquitously available to individuals. It is a growing research area within intelligent systems that aims to model and identify human physical, cognitive and social actions, patterns and skills. They typically rely on supervised machine-learning ap...
Article
Full-text available
INTRODUCTION: Dementia is a syndrome characterised by a decline in memory, language, and problem-solving thataffects the ability of patients to perform everyday activities. Patients with dementia tend to experience episodes of anxietyand remain for extended periods, which affects their quality of life.OBJECTIVES: To design AnxiDetector, a system ca...
Poster
Full-text available
Hypertension is one of the most prevalent chronic diseases worldwide. Early diagnosis of this condition can prevent the incidence of stroke and also, cardiovascular diseases (CVDs) such as myocardial infarction and heart failure. Lifestyle interventions, such as intermittent fasting (IF), aim to lower blood pressure (BP) levels and increase the hea...
Article
Full-text available
Walking is a fundamental part of a physically active lifestyle, it is one of everyday activities that positively impacts health and wellbeing. In this paper we describe the challenges and experiences of conducting a sensing campaign in the wild. We make use of mk-sense; a software platform to facilitate the deployment of collaborative sensing campa...
Conference Paper
Mobile sensing technology is allowing us to investigate human behaviour while performing day-to-day activities. In study we examined temporal orientation, which refers to the capacity of thinking or talking about personal events in the past and future. We utilize mk-sense platform that allow us to use experience-sampling method in daily life. Indiv...
Poster
Hypertension is one of the most prevalent chronic diseases world-wide. Early diagnosis of this condition can prevent the incidenceof stroke and also, cardiovascular diseases (CVDs) such as myocar-dial infarction and heart failure. Lifestyle interventions, such asintermittent fasting (IF), aim to lower blood pressure (BP) levelsand increase the heal...
Article
Stress has become a significant cause for many diseases in the modern society. Recently, smartphones, smartwatches and smart wrist-bands have become an integral part of our lives and have reached a widespread usage. This raised the question of whether we can detect and prevent stress with smartphones and wearable sensors. In this survey, we will ex...
Conference Paper
Full-text available
We present a smartwatch application that recognizes important sign sentences. We make use of modern smart watches like Samsung Gear that are equipped with inbuilt sensors including accelerometer, gyroscope and magnetometer. We show how well a smartwatch can recognize important sign sentences. We have implemented a smartwatch app that collects 3d ac...
Article
Full-text available
The gold standards for gait analysis are instrumented walkways and marker-based motion capture systems, which require costly infrastructure and are only available in hospitals and specialized gait clinics. Even though the completeness and the accuracy of these systems are unquestionable, a mobile and pervasive gait analysis alternative suitable for...