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Abstract: ams AG is a leading provider of sensing solutions developing semiconductor sensors in a wide variety of fields, with optical sensing as one of the key competences. Since integrated photonics is a promising technology for new sensor systems, ams AG has been developing processes for fully integrated CMOS-compatible photonic components based on Si3N4. This talk will provide an overview on the processing of basic photonic building blocks and their optical properties and performance. We will also give examples for applications in the fields of optical coherence tomography and opto-chemical gas sensing. In the 1980s photonics started its way for common use in telecommunication technology, using optical fiber technologies. In recent years, also a variety of photonic sensors has been proposed and developed. One of the major drawbacks of most of these photonic devices has been the lack of integration into existing (semiconductor) production processes, so far. This integration is feasible using SiN material systems to process monolithically integrated CMOS-compatible photonic sensors in the visible and near-infrared spectrum. We will present the basic processing steps for the SiN photonic technology, the development of some critical processing steps such as SiN deposition and SiN etching as well as several photonic components (waveguides, splitters, etc.) with their optical properties. One of the applications presented relates to optical coherence tomography (OCT), a fast growing imaging technique in ophthalmology. Drawbacks of existing OCT systems are their high costs as well as their bulkiness, which prevents a wider spread use of OCT systems.
One way to overcome both cost and size issues is to integrate optical and electrical components on a single chip.
Part of this work was carried out in the framework of the projects COHESION (funded by the Austrian Research Promotion Agency (FFG), no. 848588), OCTCHIP (funded by the EU’ Horizon 2020 research and innovation programme, no. 688173), and COLODOR (M-ERA.NET transnational Call 2015, funded by the Austrian Research Promotion Agency (FFG), no.854066, and the Bundesministerium für Bildung und Forschung, Germany).
We report resent results on the fabrication and characterization of carbon nanogap interdigitated electrode arrays (IDAs) for biosensor applications based on redox cycling. The electrochemical results of the carbon electrodes are compared to our fabricated gold electrodes with similar nanogap distances. The amplification factor and the collection efficiency were recorded by chronoamperometry. Cyclic voltammetry (CV) was utilized to determine the oxidation and reduction potentials as well as for monitoring the electron transfer process. The different deposited carbon materials were characterized by Raman spectroscopy.At present, we successfully fabricated carbon nanogaps down to 80 nm and we are convinced to reach the present fabrication limit of about 30 nm (for gold and platinum electrodes) with carbon as electrode material as well. To the best of our knowledge, this is the first IDA nanogap sensor, which features a gap distance under 100 nm with amorphous carbon as electrode material. Moreover, we present a signal amplification of 32 for carbon electrodes by redox cycling, which is the highest reported amplification so far.
Here we present the highly sensitive detection of dopamine using gold nanogap IDAs with redox-cycling amplification. Through the combination with a facile electrochemical activation and a chronoamperometric multistep protocol fouling of the gold electrode surface can be prevented and a sensitivity of 14 nA μM -1 with excellent linearity up to 10 μM is achieved. The low-cost and reproducible wafer level fabrication process of the nanogap IDAs plays a key role. Electrode and substrate materials can be nearly arbitrarily chosen. Also the gap sizes could be adjusted down to sub-100 nm dimensions with this versatile approach, allowing for very high signal amplification. In comparison to the current gold standard, fastscan cyclic voltammetry (FSCV) with carbon fiber microelectrodes (CFMEs), which suffers from high background currents, no elaborate data processing and high-end electronic equipment is needed. Employing our flexible, easy and inexpensive method, DA monitoring with a short acquisition period and a detection limit less than 200 nM is successfully demonstrated.
The electricity demand due to the increasing number of EVs presents new challenges for the operation of the electricity network, especially for the distribution grids. The existing grid infrastructure may not be sufficient to meet the new demands imposed by the integration of EVs. Thus, EV charging may possibly lead to reliability and stability issues, especially during the peak demand periods. Demand side management (DSM) is a potential and promising approach for mitigation of the resulting impacts. In this work, we developed an autonomous DSM strategy for optimal charging of EVs to minimize the charging cost and we conducted a simulation study to evaluate the impacts to the grid operation. The proposed approach only requires a one way communicated incentive. Real profiles from an Austrian study on mobility behavior are used to simulate the usage of the EVs. Furthermore, real smart meter data are used to simulate the household base load profiles and a real low voltage grid topology is considered in the load flow simulation. Day-ahead electricity stock market prices are used as the incentive to drive the optimization. The results for the optimum charging strategy is determined and compared to uncontrolled EV charging. The results for the optimum charging strategy show a potential cost saving of about 30.8% compared to uncontrolled EV charging. Although autonomous DSM of EVs achieves a shift of load as pursued, distribution grid operation may be substantially affected by it. We show that in the case of real time price driven operation, voltage drops and elevated peak to average powers result from the coincident charging of vehicles during favourable time slots.
Background: Peripheral arterial disease (PAD) is a common and severe disease with a highly increased cardiovascular morbidity and mortality. Through the circulatory disorder and the linked undersupply of oxygen carriers in the lower limbs, the ongoing decrease of the pain-free walking distance occurs with a significant reduction in patients’ quality of life. Studies including activity monitoring for patients with PAD are rare and digital support to increase activity via mobile health technologies is mainly targeted at patients with cardiovascular disease in general. The special requirement of patients with PAD is the need to reach a certain pain level to improve the pain-free walking distance. Unfortunately, both poor adherence and availability of institutional resources are major problems in patient-centered care.
Objective: The objective of this trackPAD pilot study is to evaluate the feasibility of a mobile phone–based self tracking app to promote physical activity and supervised exercise therapy (SET) in particular. We also aim for a subsequent patient centered adjustment of the app prototype based on the results of the app evaluation and process evaluation.
Methods: This study was designed as a closed user group trial, with assessors blinded, and parallel group study with face-to-face components for assessment with a follow-up of 3 months. Patients with symptomatic PAD (Fontaine stage IIa or IIb) and possession of a mobile phone were eligible. Eligible participants were randomly assigned into study and control group, stratified by their distance covered in the 6-min walk test, using the software TENALEA. Participants randomized to the study group received usual care and the mobile intervention (trackPAD) for the follow-up period of 3 months, whereas participants randomized to the control group received only usual care. TrackPAD records the frequency and duration of training sessions and pain level using manual user input. Clinical outcome data were collected at the baseline and after 3 months via validated tools (6-min walk test, ankle-brachial index, and duplex ultrasound at the lower arteries) and self-reported quality of life. Usability and quality of the app was determined using the user version of the Mobile Application Rating Scale.
Results: The study enrolled 45 participants with symptomatic PAD (44% male). Of these participants, 21 (47%) were randomized to the study group and 24 (53%) were randomized to the control group. The distance walked in the 6-min walk test was comparable in both groups at baseline (study group: mean 368.1m [SD 77.6] vs control group: mean 394.6m [SD 100.6]).
Conclusions: This is the first trial to test a mobile intervention called trackPAD that was designed especially for patients with PAD. Its results will provide important insights in terms of feasibility, effectiveness, and patient preferences of an app-based mobile intervention supporting SET for the conservative treatment of PAD.
When it comes to improving the health of the general population, mHealth technologies with self-monitoring and intervention components hold a lot of promise. We argue, however, that due to various factors such as access, targeting, personal resources or incentives, self-monitoring applications run the risk of increasing health inequalities, thereby creating a problem of social justice. We review empirical evidence for “intervention-generated” inequalities, present arguments that self-monitoring applications are still morally acceptable, and develop approaches to avoid the promotion of health inequalities through self-monitoring applications.