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Siegmund, Dirk; Prajapati, Ashok; Kirchbuchner, Florian; Kuijper, Arjan

An Integrated Deep Neural Network for Defect Detection in DynamicTextile Textures

2018

Progress in Artificial Intelligence and Pattern Recognition

International Workshop on Artificial Intelligence and Pattern Recognition (IWAIPR) <6, 2018, Havana, Cuba>

Lecture Notes in Computer Science (LNCS), 11047

This paper presents a comprehensive defect detection method for two common fabric defects groups. Most existing systems require textiles to be spread out in order to detect defects. This method can be applied when the textiles are not spread out and does not require any pre- processing. The deep learning architecture we present is based on transfer learning and localizes and recognizes cuts, holes and stain defects. Classification and localization is combined into a single system combining two different networks. The experiments this paper presents show that even without adding depth information, the network was able to distinguish between stain and shadow. This method has been successful even for textiles in voluminous shape and is less computationally intensive than other state-of-the-art methods.

978-3-030-01131-4

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Ivanov, Ivelin; Kuijper, Arjan [Betreuer]; Wilmsdorff, Julian von [Betreuer]; Kirchbuchner, Florian [Betreuer]

CapBed - Preventive Assistance System for the Bed Area Based on Capacitive Sensing

2018

Darmstadt, TU, Master Thesis, 2018

Over the past decades, human activity recognition systems have become a major input modality for building automation. However, those systems also found recent applications in emergency detection, such as recognizing patient activities that may lead to life-threatening situations like falls or heart attacks. The aim of this thesis is to develop a sensor that recognizes whether a person wants to get out of bed. This is to prevent falls by illuminating the path or calling a nurse in time. In addition, such a system can also provide insights into the behavior of the user in the long term. Therefore, a concept of preventive assistance system for the bed area based on capacitive sensing is developed within the scope of this work. To this end, a comparison to other sensor technologies will be established, followed by a detailed overview of the technical background of capacitive proximity sensing. An innovative concept of a device that offers decent performance at an affordable price is proposed. Based on this concept a prototype system was developed and evaluated to investigate its sensing performance and identify possible limitations. As a future outlook, this thesis summarizes the occurred problems and suggests possible modifications that might improve the overall performance of the system.

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Wilmsdorff, Julian von; Kirchbuchner, Florian; Braun, Andreas; Kuijper, Arjan

Eliminating the Ground Reference for Wireless Electric Field Sensing

2018

Ambient Intelligence

European Conference on Ambient Intelligence (AmI) <14, 2018, Larnaca, Cyprus>

Capacitive systems are getting more and more attention these days. But many systems today like smart-phone screens, laptops, and non-mechanical buttons use capacitive techniques to measure events within several centimeters of distance. The reason that battery-powered devices don’t have high measurement ranges lies in the principle of capacitive measurement itself - the electrical ground is an inherent part of the measurement. In this paper, we present a method for passive and wireless capacitive systems to eliminate the reference to ground. This bears a couple of advantages for mobile, battery-powered capacitive sensor designs in the field of ambient intelligence. We compare the detection range of normal passive capacitive systems with our new approach. The results show that our improvements result in a higher detection range and higher power efficiency.

978-3-030-03061-2

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Fu, Biying; Kirchbuchner, Florian; Kuijper, Arjan; Braun, Andreas; Gangatharan, Dinesh Vaithyalingam

Fitness Activity Recognition on Smartphones Using Doppler Measurements

2018

Informatics

Quantified Self has seen an increased interest in recent years, with devices including smartwatches, smartphones, or other wearables that allow you to monitor your fitness level. This is often combined with mobile apps that use gamification aspects to motivate the user to perform fitness activities, or increase the amount of sports exercise. Thus far, most applications rely on accelerometers or gyroscopes that are integrated into the devices. They have to be worn on the body to track activities. In this work, we investigated the use of a speaker and a microphone that are integrated into a smartphone to track exercises performed close to it. We combined active sonar and Doppler signal analysis in the ultrasound spectrum that is not perceivable by humans. We wanted to measure the body weight exercises bicycles, toe touches, and squats, as these consist of challenging radial movements towards the measuring device. We have tested several classification methods, ranging from support vector machines to convolutional neural networks. We achieved an accuracy of 88% for bicycles, 97% for toe-touches and 91% for squats on our test set.

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Rus, Silvia; Hammacher, Felix; Wilmsdorff, Julian von; Braun, Andreas; Große-Puppendahl, Tobias; Kirchbuchner, Florian; Kuijper, Arjan

Prototyping Shape-Sensing Fabrics Through Physical Simulation

2018

Ambient Intelligence

European Conference on Ambient Intelligence (AmI) <14, 2018, Larnaca, Cyprus>

Lecture Notes in Computer Science (LNCS), 11249

Embedding sensors into fabrics can leverage substantial improvements in application areas like working safety, 3D modeling or health-care, for example to recognize the risk of developing skin ulcers. Finding a suitable setup and sensor combination for a shape-sensing fabric currently relies on the intuition of an application engineer. We introduce a novel approach: Simulating the shape-sensing fabric first and optimize the design to achieve better real-world implementations. In order to enable developers to easily prototype their shape-sensing scenario, we have implemented a framework that enables soft body simulation and virtual prototyping. To evaluate our approach, we investigate the design of a system detecting sleeping postures. We simulate potential designs first, and implement a bed cover consisting of 40 distributed acceleration sensors. The validity of our framework is confirmed by comparing the simulated and real evaluation results. We show that both approaches achieve similar performances, with an F-measure of 85% for the virtual prototype and 89% for the real-world implementation.

978-3-030-03061-2

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Scherf, Lisa; Kirchbuchner, Florian; Wilmsdorff, Julian von; Fu, Biying; Braun, Andreas; Kuijper, Arjan

Step by Step: Early Detection of Diseases Using an Intelligent Floor

2018

Ambient Intelligence

European Conference on Ambient Intelligence (AmI) <14, 2018, Larnaca, Cyprus>

Lecture Notes in Computer Science (LNCS), 11249

The development of sensor technologies in smart homes helps to increase user comfort or to create safety through the recognition of emergency situations. For example, lighting in the home can be controlled or an emergency call can be triggered if sensors hidden in the floor detect a fall of a person. It makes sense to also use these technologies regarding prevention and early detection of diseases. By detecting deviations and behavioral changes through long-term monitoring of daily life activities it is possible to identify physical or cognitive diseases. In this work, we first examine in detail the existing possibilities to recognize the activities of daily life and the capability of such a system to conclude from the given data on illnesses. Then we propose a model for the use of floor-based sensor technology to help diagnose diseases and behavioral changes by analyzing the time spent in bed as well as the walking speed of users. Finally, we show that the system can be used in a real environment.

978-3-030-03061-2

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Fu, Biying; Mettel, Matthias Ruben; Kirchbuchner, Florian; Braun, Andreas; Kuijper, Arjan

Surface Acoustic Arrays to Analyze Human Activities in Smart Environments

2018

Ambient Intelligence

European Conference on Ambient Intelligence (AmI) <14, 2018, Larnaca, Cyprus>

Smart Environments should be able to understand a user’s need without explicit interaction. In order to do that, one step is to build a system that is able to recognize and track some common activities of the user. This way, we can provide a system that provides various services for controlling installed appliances and offering help for every day activities. Applying these services in the users’ environment should make his life more comfortable, easier, and safer. In this paper, we will introduce an embedded sensor system using surface acoustic arrays to analyze human activities in a smart environment. We divided basic activity groups ranging from walking, cupboard closing to falling, including their extended sub-activity groups. We expanded walking into walking barefoot, with shoes and with high heels and further extended closing cupboard with three cupboards locating on different positions. We further investigated the usage of single pickup or a combination of 4 pickups with their effect on the recognition precision. We achieved an overall precision of 97.23% with 10-fold cross validation using support vector machine (SVM) for all sub-activity group combined. Even using one pickup only, we can achieve an overall precision of more than 93%, but we can further increase the precision by using a combination of pickups up to 97.23%.

978-3-030-03061-2

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Wilmsdorff, Julian von; Kirchbuchner, Florian; Fu, Biying; Braun, Andreas; Kuijper, Arjan

An Exploratory Study on Electric Field Sensing

2017

Ambient Intelligence

European Conference on Ambient Intelligence (AmI) <13, 2017, Malaga, Spain>

Electric fields are influenced by the human body and other conducting materials. Capacitive measurement techniques are used in touch-screens, in the automobile industry, and for presence and activity recognition in Ubiquitous Computing. However, a drawback of the capacitive technology is the energy consumption, which is an important aspect for mobile devices. In this paper we explore possible applications of electric field sensing, a purely passive capacitive measurement technique, which can be implemented with an extremely low power consumption. To cover a wide range of applications, we examine five possible use cases in more detail. The results show that the application is feasible both in interior spaces and outdoors. Moreover, due to the low energy consumption, mobile usage is also possible.

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Fu, Biying; Gangatharan, Dinesh Vaithyalingam; Kuijper, Arjan; Kirchbuchner, Florian; Braun, Andreas

Exercise Monitoring On Consumer Smart Phones Using Ultrasonic Sensing

2017

iWOAR 2017

International Workshop on Sensor-based Activity Recognition (iWOAR) <4, 2017, Rostock, Germany>

Quantified self has been a trend over the last several years. An increasing number of people use devices, such as smartwatches or smartphones to log activities of daily life, including step count or vital information. However, most of these devices have to be worn by the user during the activities, as they rely on integrated motion sensors. Our goal is to create a technology that enables similar precision with remote sensing, based on common sensors installed in every smartphone, in order to enable ubiquitous application. We have created a system that uses the Doppler effect in ultrasound frequencies to detect motion around the smartphone. We propose a novel use case to track exercises, based on several feature extraction methods and machine learning classification. We conducted a study with 14 users, achieving an accuracy between 73% and 92% for the different exercises.

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Scherf, Lisa Katharina; Kuijper, Arjan [1. Gutachten]; Kirchbuchner, Florian [2. Gutachten]

Human Behavior Analysis and Prediction Based on a Smart Floor

2017

Darmstadt, TU, Bachelor Thesis, 2017

Older adults have the desire to live independently in their own homes for as long as possible. The development of sensor technologies in Smart Homes support this aim by providing sufficient security standards in case of emergencies. For example, a call of emergency can be triggered if a fall of a person is detected by sensors hidden in the floor. However, it is often not only about urgent situations, but also about gradual changes in behavior. Especially when a user is not able to follow his or her daily routine, long-term activity recognition based on location tracking allows for early detection of diseases such as Alzheimer's and dementia and can generally reveal a decrease in the ability to live independently. The focus of this work was the investigation of health related activities and their most accurate measurement only using an intelligent floor based system. Based on these considerations, a method to extrapolate from the collected sensor data to the chosen values is proposed. In addition, a model to detect gradual changes in these health indicators is developed and tested on the smart floor in the Living Lab of Fraunhofer IGD as well as in two apartments in everyday life. The findings of these thesis show a way of using smart floors for health monitoring. The applicability in everyday life could not be shown due to independent problems with the location tracking of the floor during the evaluation period and the lack of additional data for the validation. However, the evaluation under testing conditions showed promising results and an untapped potential of smart floors in health monitoring.

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Fu, Biying; Kirchbuchner, Florian; Wilmsdorff, Julian von; Große-Puppendahl, Tobias; Braun, Andreas; Kuijper, Arjan

Indoor Localization Based on Passive Electric Field Sensing

2017

Ambient Intelligence

European Conference on Ambient Intelligence (AmI) <13, 2017, Malaga, Spain>

The ability to perform accurate indoor positioning opens a wide range of opportunities, including smart home applications and location-based services. Smart floors are a well-established technology to enable marker-free indoor localization within an instrumented environment. Typically, they are based on pressure sensors or varieties of capacitive sensing. These systems, however, are often hard to deploy as mechanical or electrical features are required below the surface. They might also have a limited range or not be compatible with different floor materials. In this paper, we present a novel indoor positioning system using an uncommon form of passive electric field sensing, which detects the change in body electric potential during movement. It is easy to install by deploying a grid of passive wires underneath any non-conductive floor surface. The proposed architecture achieves a high position accuracy and an excellent spatial resolution. In our evaluation, we measure a mean positioning error of only 12.7 cm. The proposed system also combines the advantages of very low power consumption, easy installation, easy maintenance, and the preservation of privacy.

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Kirchbuchner, Florian; Fu, Biying; Braun, Andreas; Wilmsdorff, Julian von

New Approaches for Localization and Activity Sensing in Smart Environments

2017

Ambient Assisted Living

Ambient Assisted Living (AAL) <9, 2016, Frankfurt, Germany>

Smart environments need to be able to fulfill the wishes of its occupants unobtrusively. To achieve this goal, it has to be guaranteed that the current state environment is perceived at all times. One of the most important aspects is to find the current position of the in- habitants and to perceive how they move in this environment. Numerous technologies enable such supervision. Particularly challenging are marker-free systems that are also privacy-preserving. In this paper, we present two such systems for localizing inhabitants in a Smart Environment using - electrical potential sensing and ultrasonic Doppler sensing. We present methods that infer location and track the user, based on the acquired sensor data. Finally, we discuss the advantages and challenges of these sensing technologies and provide an overview of future research directions.

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Braun, Andreas; Kirchbuchner, Florian; Wichert, Reiner

Ambient Assisted Living

2016

eHealth in Deutschland

Das Anwendungsfeld Ambient Assisted Living (AAL) beschreibt technische Systeme zur Unterstützung hilfsbedürftiger Personen im Alltag. In den vergangenen Jahren wurde in Deutschland und Europa viel in die Entwicklung und Erprobung von Technologien zur Unterstützung in der häuslichen Umgebung investiert, jedoch häufig ohne nachhaltige Effekte am Markt. Ein fehlender Aspekt war häufig die mangelnde Involvierung aller notwendigen Parteien. In diesem Kapitel werden die Potenziale assistiver Technologien beleuchtet, eine Studie zur Akzeptanz derartiger Technologien bei Senioren vorgestellt sowie ein Ausblick auf zukünftige Entwicklungen in diesem Bereich präsentiert.

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Kutlucan, Osman; Kuijper, Arjan [Prüfer]; Kirchbuchner, Florian [Betreuer]

Barrierefreies Lagersystem zur Unterstützung von Menschen mit eingeschränkter visueller Wahrnehmungsfähigkeit

2016

Darmstadt, TU, Master Thesis, 2016

Im Mittelpunkt dieser Masterarbeit steht die Realisierung eines Lagersystems für Menschen mit eingeschränkter visueller Wahrnehmungsfähigkeit. Das in diesem Rahmen entwickelte Lagersystem verwendet Hand- und Gestenerkennung, Spracherkennung, Sprachsynthese und Sonifikation. Das Ziel des Systems ist es, sowohl eine pervasive Benutzerschnittstelle anzubieten, welche es blinden Benutzern ermöglicht, mit dem Lagerbereich auf eine natürliche Weise zu interagieren, und ein Lagersystem zu haben, welches mit geringem Aufwand konfiguriert werden kann. Daher werden in der Thesis in erster Linie verschiedene verwandte Ansätze und Konzepte betrachtet, woraufhin beschrieben wird, wie das vorgeschlagene Konzept der Thesis entwickelt wurde und warum dieses Konzept sich besser für blinde Benutzer eignet. Um dies zu analysieren, wird das vorgeschlagene System iterativ evaluiert. Im Rahmen der Evaluation wurden Verbesserungsvorschläge aufgenommen, und die Präzision und Effizienz der Implementierung gemessen. Die Ergebnisse der Evaluation dieser Thesis zeigen, dass das Konzept des vorgeschlagenen Systems angemessen ist und von blinden Benutzern gut aufgenommen wird, was z.B. durch einen Teilnehmer der Evaluation bei der Beurteilung eines Subworkflows des Systems mit folgenden Worten bestätigt wurde: "Die Interaktion fühlt sich so an, als wäre man nicht blind". Aber die Implementierung des Systems weist einige Probleme auf, welche sich vorwiegend in der Hand- und Gestenerkennung des Systems zeigen. Mit Behebung dieser Probleme könnte die User Experience einen höheren Grad erreichen, wodurch das System im alltäglichen Leben einsetzbar werden könnte.

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Kirchbuchner, Florian; Große-Puppendahl, Tobias; Hastall, Matthias R.; Distler, Martin; Kuijper, Arjan

Ambient Intelligence from Senior Citizens' Perspectives: Understanding Privacy Concerns, Technology Acceptance, and Expectations

2015

Ambient Intelligence

European Conference on Ambient Intelligence (AmI) <12, 2015, Athens, Greece>

Especially for seniors, Ambient Intelligence can provide assistance in daily living and emergency situations, for example by automatically recognizing critical situations. The use of such systems may involve trade-offs with regard to privacy, social stigmatization, and changes of the well-known living environment. This raises the question of how older adults perceive restrictions of privacy, accept technology, and which requirements are placed on Ambient Intelligent systems. In order to better understand the related concerns and expectations, we surveyed 60 senior citizens. The results show that experience with Ambient Intelligence increases technology acceptance and reduces fears regarding privacy violations and insufficient system reliability. While participants generally tolerate a monitoring of activities in their home, including bathrooms, they do not accept commercial service providers as data recipients. A comparison between four exemplary systems shows that camera-based solutions are perceived with much greater fears than wearable emergency solutions. Burglary detection was rated as similarly important assigned as health features, whereas living comfort features were considered less useful.

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Pavlov, Alexander; Große-Puppendahl, Tobias [Betreuer]; Kirchbuchner, Florian [Betreuer]

Erkennung von Aufstehsituationen mit multimodaler Sensorik

2015

Darmstadt, TU, Master Thesis, 2015

In dieser Arbeit wurde die Erkennung von sechs ausgewählten Aktivitäten mit dem multimodalen Bettsystem untersucht. Bei der multimodalen Sensorik handelt es sich um eine Kombination aus einem Elektropotentialsensor, einem kapazitiven Sensor, einem Passiv-Infrarot-Sensor und einem 3-Achsen-Beschleunigungssensor. Es wurde ein prototypisches System im Multimedia Appliances Lab am Fraunhofer IGD aufgebaut. Anschließend wurden Aufzeichnungen mit zehn Personen durchgeführt und die Trainings- und Testdaten für den Machine-Learning-Algorithmus gesammelt. Aus den aufgenommenen Daten wurden die Merkmale im Zeitbereich, im Zeit-Frequenzbereich und im Frequenzbereich extrahiert. Die beste Klassifikationsgenauigkeit des entwickelten Systems, abgeschätzt mit dem F-Maß, berechnet sich zu 0,999 und wurde bei der Aktivität "Epilepsie" beobachtet. Das über alle Aktivitäten gemittelte F-Maß ist zufriedenstellend und erreicht einen Wert von 0,870.

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Kirchbuchner, Florian; Kuijper, Arjan [Prüfer]; Große-Puppendahl, Tobias [Betreuer]

User Tracking and Behavior Recognition Based on a Capacitive Indoor Localization System

2014

Darmstadt, TU, Master Thesis, 2014

This thesis focused on tracking and analyzing the behavior of elderly people by using in-home monitoring systems. The goal was to add a localization component to an existing system for fall detection as well as to assess the elderly's acceptance of such systems and the corresponding loss of privacy. Therefore, this thesis analyzed the demands on monitoring and technical assistance systems and discussed different models of acceptance measuring. Furthermore, existing approaches to user tracking and behavior analysis are examined. On this basis, an implementation of the tracking functionality, based on a capacitive sensor system, was proposed and evaluated. In addition, a survey among elderly people was conducted by the author and the results are presented in detail. The findings of this thesis showed that capacitive sensing in combination with particle filtering was suitable for user tracking. Moreover, the results of the study emphasized that senior citizens were indeed willing to accept a certain loss of privacy but distinguished between different services and systems. It was also shown that the capacitive system used for this study was received positively in comparison to other systems.