Background Deep brain stimulation of the subthalamic nucleus (STN-DBS) is a successful treatment option in Parkinson’s disease (PD) for different motor and non-motor symptoms, but has been linked to postoperative cognitive impairment. Aim Since both dopaminergic and norepinephrinergic neurotransmissions play important roles in symptom development, we analysed STN-DBS effects on dopamine and norepinephrine availability in different brain regions and morphological alterations of catecholaminergic neurons in the 6-hydroxydopamine PD rat model. Methods We applied one week of continuous unilateral STN-DBS or sham stimulation, respectively, in groups of healthy and 6-hydroxydopamine-lesioned rats to quantify dopamine and norepinephrine contents in the striatum, olfactory bulb and dentate gyrus. In addition, we analysed dopaminergic cell counts in the substantia nigra pars compacta and area tegmentalis ventralis and norepinephrinergic neurons in the locus coeruleus after one and six weeks of STN-DBS. Results In 6-hydroxydopamine-lesioned animals, one week of STN-DBS did not alter dopamine levels, while striatal norepinephrine levels were decreased. However, neither one nor six weeks of STN-DBS altered dopaminergic neuron numbers in the midbrain or norepinephrinergic neuron counts in the locus coeruleus. Dopaminergic fibre density in the dorsal and ventral striatum also remained unchanged after six weeks of STN-DBS. In healthy animals, one week of STN-DBS resulted in increased dopamine levels in the olfactory bulb and decreased contents in the dentate gyrus, but had no effects on norepinephrine availability. Conclusions STN-DBS modulates striatal norepinephrinergic neurotransmission in a PD rat model. Additional behavioural studies are required to investigate the functional impact of this finding.

Adaptive Voltage Scaling (AVS) is a well-known technique in ASICs. However, the requirements for its application in FPGAs are quite different. AVS uses run-time knowledge to determine a favorable voltage/frequency operating point. There are many suggestions in the literature for the sensors to be used to gain this run-time knowledge. However, the specific placement and routing of each sensor instance is either ignored or manually defined by hard macros or directed routing. In this paper, we propose a new approach to sensor placement. We are able to omit strict constraints like directed routing and give more freedom to the EDA tool without compromising sensor accuracy by using a proper sensor calibration. As a result, we are able to avoid placement and routing conflicts between sensors and application design. This allows the use of larger sensors with significant routing delay. An extensive experimental evaluation proves the validity of our approach.

Indoor positioning plays an increasingly important role in industrial spaces. Self-localizing autonomous machines are already well established and indoor positioning for pedestrians increases safety and productivity when interacting with (semi) autonomous machines. Positioning methods for pedestrians commonly use wearable or handheld sensors that rely on extensive calibration to tune gait detection heuristics. We present a method to automatically derive the target variables of these heuristics, stride length and stride orientation, for each individual user stride by using parallel location measurements during normal operation. We show that our method fits real world measurements of stride length. Additionally, we conduct simulations to verify the variance and bias of the derived stride length and orientation at varying accuracies of the reference position measurements. Our method provides a means for online annotation of raw data for pedestrian positioning, enabling both the online calibration of gait detection heuristics as well as data annotation for machine learning applications.

The focus of this paper is the feasibility of Visible Light Communication (VLC) for the monitoring of implants in rodents by example of two approaches. One of the VLC variants is intended for manually triggered transmission and takes advantage of the CMOS sensor rolling shutter principle. The second approach is designed mainly for autonomous monitoring. Trials with freely moving animals have shown that the first approach provides a throughput of 148 bit/s. For the automatic monitoring a transmission every 6 hours is sufficient for a reliable daily update of the implant status.VLC exhibits limited range and channel capacity in comparison to radio frequency (RF) based telemetry. However, the advantage of VLC solutions is the minimal space requirement as only a single LED is needed in addition to the microcontroller on the transmitter side.

The growing capabilities of wireless communication technologies such as WLAN-based systems enable their successful adoption in an ever-increasing range of applications. Particularly in the domain of the internet of things, the trend towards wireless interconnection is driven by its improved scalability and flexible, low-cost deployment compared to wired systems such as Ethernet. To handle the growing complexity of their design, developers need a process for early performance evaluation of these communication-intensive networked embedded systems. For this, established network simulation frameworks like ns-3 and ${OMNeT}++$ are often utilized. These frameworks require developers to model every part of their system, including the protocol stack and the target application they are developing. From the developers’ perspective, a workflow that would enable them to use real target software as much as possible is desirable. The available solutions to couple real target software with a network simulation, however, often exhibit several limitations. These range from a lacking detail level of the channel simulation to the requirement of access to the source code of every part of the system under design, and often prevent adoption of these coupling solutions. In this paper, we propose a data interface for the established simulator ns-3 that allows coupling to the Linux kernel at a very low level of the protocol stack, namely the lower WLAN MAC layer. This interface allows the performance evaluation of WLAN-based systems, in which real target code of almost the entire software stack can be used. With such an interface, developers can write real target software and test it under different wireless network scenarios and channel conditions, powered by a simulation using ns-3. We show the practicality of our interface by comparing it to a simulation solely performed in ns-3, as well as to another framework for coupling real target software to a channel simulation.

Load control for consumer devices offers great potential in terms of power grid stabilization. Utilizing power adaptation capabilities of modern electronics allows a wide range of devices to participate in the grid stabilization. Certain electronic devices, like lighting, are directly perceived by humans or part of larger installations. Therefore, a minimum impact on perception and system integrity facilitates acceptance and allows a wide distribution. Taking advantage of the human properties for perceiving changes in light we propose an effective grid stabilization method for considerable network imbalances in order to utilize the high share of the total power demand in Europe that lighting accounts for. With regard to the results, we can assume a considerable stabilizing effect with hardly noticeable perception.

Context. Long-term deep brain stimulation (DBS) studies in rodents are of crucial importance for research progress in this field. However, most stimulation devices require jackets or large head-mounted systems which severely affect mobility and general welfare influencing animals’ behavior. Objective. To develop a preclinical neurostimulation implant system for long-term DBS research in small animal models. Approach. We propose a low-cost dual-channel DBS implant called software defined implantable platform (STELLA) with a printed circuit board size of Ø13 × 3.3 mm, weight of 0.6 g and current consumption of 7.6 µA/3.1 V combined with an epoxy resin-based encapsulation method. Main results. STELLA delivers charge-balanced and configurable current pulses with widely used commercial electrodes. While in vitro studies demonstrate at least 12 weeks of error-free stimulation using a CR1225 battery, our calculations predict a battery lifetime of up to 3 years using a CR2032. Exemplary application for DBS of the subthalamic nucleus in adult rats demonstrates that fully-implanted STELLA neurostimulators are very well-tolerated over 42 days without relevant stress after the early postoperative phase resulting in normal animal behavior. Encapsulation, external control and monitoring of function proved to be feasible. Stimulation with standard parameters elicited c-Fos expression by subthalamic neurons demonstrating biologically active function of STELLA. Significance. We developed a fully implantable, scalable and reliable DBS device that meets the urgent need for reverse translational research on DBS in freely moving rodent disease models including sensitive behavioral experiments. We thus add an important technology for animal research according to ‘The Principle of Humane Experimental Technique’—replacement, reduction and refinement (3R). All hardware, software and additional materials are available under an open source license.

In modern applications such as in the prospective smart factory, timely and faultfree communication is one of the main concerns. Communication failures may lead to huge economic losses. Moreover, they can even endanger human life. Therefore, the TimeSensitive Networking (TSN) task group has introduced new standards for real-time capable Ethernet, which also include a fault tolerance mechanism called Frame Replication and Elimination for Reliability (FRER) as IEEE standard 802.1CB. This standard introduces procedures and protocols for bridges and end stations in time-sensitive networks. It also provides mechanisms for the identification and duplication of frames to enable redundant transmissions. In this paper, a simulation model is developed that implements the IEEE 802.1CB standard in OMNeT++. In addition, as supplement to the standard we propose a reliability mechanism for establishing redundant paths and an error model to model transient and permanent errors. As proof of concept, we evaluate the model with different topologies under various conditions.

The regulation and stabilization of the power grid requires various system services that have been provided so far primarily by conventional power plants. With the future shutdown of coal-fired and nuclear power plants, investigations into the provision of these services will become all the more important in order to ensure the safe operation of the grid. Currently, photovoltaic and wind can only provide limited so-called control power, so that new methods such as the regulation of large consumers will become interesting. Adapting the electricity requirements of consumers to the current grid situation has a comparable effect to the provision of additional balancing power on the generation side. Some consumers like data centers can provide primary control power at high speed. In this paper we present how data centers can autonomously support grid stabilization with minimal impact on the daily operation. Additional benefits include an higher efficiency and the ability to take advantage of any future financial bonuses by regulation authorities or electricity suppliers.

The ability to locate assets and humans will lead to many services such as location based services especially in the material handling domain. The development of Industrial Internet of Things (IIoT) necessitates precise positioning, especially for moving objects in industrial environment. This way, automation processes with less human errors, and more safe environments are feasible. In order to achieve a wide reaching penetration of new control and tracking schemes in the Material Handling Domain (MHD), localization of assets needs to be realized in a cost efficient way with sufficient quality of positioning. The cost and quality of localization need to be weighted against each other and depend on the use case. We investigate variations of a indoor localization system, this is done through acquiring raw measurements from an Ultra Wide-Band (UWB) ranging system and comparing various processing approaches to achieve accurate positioning. We then compare the computational cost and quality of positioning of these approaches. Three multilateration algorithms are compared: gradient descent, least square, and recursive least square. Additionally, we investigate the impact of anchor node placement and additional filtering through a Kalman filter. We show that the maximum positioning error is mitigated by up to 30 % and the mean error by up to 4 % when using additional Kalman filtering of multilateration position estimates at comparably low additional computation cost. Our results suggest there are significant differences of localization quality and computational cost between the examined multilateration methods with no clear correlation of computational cost and positioning quality. We also show that the positioning quality and filtering improvement strongly depends on the UWB anchor height.

Publish/subscribe is a flexible communication pattern for loosely coupled distributed applications. The content-based variant matches each published notification against active subscriptions to determine a set of interested subscribers to which the notification is to be delivered. Since the recipient set can be different for each notification, it is challenging to find and install profitable forwarding rules on the network switches. In this paper, we present novel notification forwarding schemes implemented in P4 that use virtual trees (VTs) installed on switches and additional forwarding information encoded in notification packets that is used to connect VTs, to extend VT branches, or to cut off VT subtrees. For deriving beneficial VTs, we consider (i) topological properties of the physical network, (ii) publisher/subscriber relationships, and (iii) notification statistics. We present a generic algorithm for encoding distribution trees and evaluate our forwarding schemes in a data center network. The results show that our schemes perform well and save network bandwidth by reducing the notification header length.

Current control processes in the material handling domain are generally not automated but require manual human intervention. However, the ongoing development towards the Industry 4.0 involves new models and concepts and hence more and more automated control functions will become necessary. That is, devices such as cranes in the material handling domain will become smarter and will also be networked to a larger extent. However, it will be required that control messages passed to the cranes through a network, possibly shared with other traffic, are guaranteed to arrive in time. In this paper, we present an OPC UA-based model of an overhead travelling crane as part of a material handling scenario. The crane can be controlled by a crane remote controller, which we model as well. We use time-sensitive networking technology to ensure deterministic communication between the crane remote controller and the crane. To demonstrate the crane movement, we illustrate it in a simulation before we prove the deterministic communication in a real testbed.

Modern Building Automation Systems (BAS) consist of sensors and actuators that are connected via an IP-based network and offer their functionality via RESTful APIs. Because a single device can be exploited by an attacker to perform attacks within the local network, we put devices into isolated groups. These groups are isolated MAC-layer Trust Zones to reduce the attack surface in contrast to a BAS with fully connected devices. We propose an algorithm that leverages the so far neglected potential of Building Information Modeling (BIM) to compute Trust Zones. We assure unimpaired operation of all applications while limiting the number of infrastructure devices. The proposed mechanisms are demonstrated considering sensors and actuators that are connected via wired Ethernet and the IEEE 802.11s WLAN mesh standard. At the application layer we make exemplary use of the Constrained Application Protocol (CoAP). Finally, we experimentally evaluate the device acquisition and selection based on our network partitioning algorithm.

Deep Brain Stimulation is an indispensable therapy option for severe neurodegenerative diseases like parkinson. However, the lack of understanding of the functional principle hinders an optimal clinical application. Therefore, basic research in animal models is crucial. For the development of neurostimulators in rodents, physical prototyping alone is not feasible anymore due to the growing complexity and necessary optimization of the overall implants. However, there is no scientific approach for virtual prototyping of neurostimulators. This work proposes a power model for a developed neurostimulator, based on a time continuous battery model and power-state-machines. The model was implemented in SystemC and SystemC-AMS and validated against measurements. The model helped us understand and find power optimal working points of the implant and thus achieve a runtime gain of 44% with a given battery. Consequently, this work shows that we can use virtual prototyping in SystemC-AMS to aid design decisions for future implant versions.

In the age of digitalization, data protection plays an important role. Data is created, modified and shared over the Internet between data owners and data users. A key issue in this context is the respect of data sovereignty. The International Data Spaces (IDS) Reference Architecture has been developed in order to preserve data sovereignty. In this regard, Internet of Things (IoT) devices, such as sensors, play an important role for providing data. However, an IoT device is not capable of being integrated directly into the IDS by default. We propose an approach to enable the IDS for vendor independent IoT devices, using an open interoperability standard for the IoT specified by the Open Geospatial Consortium (OGC). This allows data owners to benefit from providing their own data while retaining control over it.

Currently, Open Platform Communication Unified Architecture (OPC UA) is nominated as a reference standard to meet all Industry 4.0 demands with one protocol, enabling an efficient communication between devices in industrial systems. Recently, OPC UA has been extended by a publish/subscribe pattern to support multicast communication since there is a need for an efficient data aggregation and distribution to cope with the increasing number of controllers, sensors, and measured values in industries. Message Queuing Telemetry Transport (MQTT) is the most widely used publish/subscribe communication protocol and is based on a central broker for message exchange. In this paper, the communication latency of OPC UA end devices exchanging data over MQTT as a broker-based middleware is investigated and compared to the client/server-based communication. In particular, we analyze the use case of one-to-many communication for a crane model from the material handling domain. We provide a prototype implementation of the OPC UA MQTT extension and our evaluation results show the reduced traffic overhead and communication latency compared to client/server-based communication.

Modern surgical devices are full of innovations and provide plenty of functionalities. However, they only perform to their full potential if they are properly configured. Only a small subset of surgical device functionalities is used due to the high complexity of today's device systems and the omnipresent situation that only the circulating nurses can (re-)configure non-sterile devices. Hence, there is a huge need for safe and effective assistance supporting the operating room (OR) staff to continuously work with the potentially best device setting to increase patient's safety and clinical outcome. Therefore, we propose a concept for situation-aware parameter recommendations and automatic (re-)configuration. Free access to adequate data is a prerequisite to extract knowledge for assistive systems and to provide situation awareness during execution. Thus, manufacturer-independent medical device interoperability is a basic requirement. Consequently, we use the new IEEE 11073 Service-oriented Device Connectivity (SDC) standards family, including Device Specializations. As part of the developing committee we introduce the idea and concept behind Device Specializations and highlight their use for assistive systems in the domain of minimal invasive surgery. To ensure safety and effectiveness of the assistive functionalities, our concept enforces deterministic rules providing a predictable and approvable behavior. We demonstrate our concept by the use case of a smart surgical double roller pump using an interpreter-based Rule Execution Engine.

Nowadays, VLSI systems suffer from increasing impacts of aging and variability. Traditionally, this is treated by applying extensive guard bands. As those guard bands are chosen at design time, they are necessarily worst case guard bands. Thus, most often they are too pessimistic. Current research tries to mitigate this by means of in-situ performance measurement based Adaptive Voltage Scaling (AVS). AVS typically relies on assumptions regarding the timing behavior of the application logic in relation to the behavior of a specific canary or sensor logic. Most published approaches use manually gained empirical data of just a few test chips and application designs for this purpose. However, to practically apply these techniques, an automatic calibration flow is needed. We propose such an automated calibration flow and test it on multiple FPGAs. We achieve an average power saving of 67%.

Due to the fact that every smart building is a unique composition of devices, services, and users there is no one-fits-all security architecture. With our proposal we address this problem by using Building Information Modeling (BIM) as source of information for our security concept. Using BIM, models are created throughout the planning of a building, which do not consist only of 3D information such as typical CAD drawings, but also provide a rich set of metadata about the building elements including devices, their interrelationships and networking. Thus, BIM can be used to derive security configurations for each individual embedded device, its services and the network as a whole. We demonstrate the function of a general Security Controller to partition the network on MAC layer. Furthermore, we draw an overall picture of the proposed architecture and the range of possible applications.