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12. Message from the organizing committee

Author

Haase, Jan, primary, Gomez, Jorge Tomes, additional, Spicher, Nicolai, additional, Apostolatos, Andreas, additional, Kaplan, Shaun, additional, and Chituc, Claudia-Melania, additional

Published
2023
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14. Fully Time-Based PID Controller for a High Frequency Buck Converter

Author

Dahl, Nicolai Jerram, Muntal, Pere L., Andersen, Michael A. E., Dahl, Nicolai Jerram, Muntal, Pere L., and Andersen, Michael A. E.

Abstract

With the shrinkage of process nodes for integrated circuits, analog circuits, like analog feedback control, have become increasingly expensive and more challenging to design. Here timebased control is a compelling alternative to traditional analog feedback control circuits due to its better scaling with the process node. Several publications about time-based PID-type controllers exist. There the PI-part is implemented in the time domain, but the D-part remains in the analog domain thereby limiting the process scaling benefits. This paper proposes a new PID structure that fully integrates the PID in the time domain. The proposed structure has improved ripple attenuation and maps directly to a typical PID. Simulations shows that the performance of the theoretical small signal controller translates well to the large signal time-based response

Published
2023

26. Open-Source Chip Design in Academic Education

Author

Syed Anas Alam, Jakob Furbo Enevoldsen, Andreas Alkjaer Eriksen, Niels William Hartmann, Ulrik Helk, Jorgen Kragh Jakobsen, Christa Skytte Jensen, Nicolai Dyre Bulow Jespersen, Karl Herman Krause, Mads Rumle Nordstrom, Tjark Petersen, Luca Pezzarossa, Simon Winther Rasmussen, Martin Schoeberl, and Jonas Ingerslev Sorensen

Published
2022
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27. Open-Source Chip Design in Academic Education

Author

Alam, Syed Anas, primary, Enevoldsen, Jakob Furbo, additional, Eriksen, Andreas Alkjaer, additional, Hartmann, Niels William, additional, Helk, Ulrik, additional, Jakobsen, Jorgen Kragh, additional, Jensen, Christa Skytte, additional, Bulow Jespersen, Nicolai Dyre, additional, Krause, Karl Herman, additional, Nordstrom, Mads Rumle, additional, Petersen, Tjark, additional, Pezzarossa, Luca, additional, Rasmussen, Simon Winther, additional, Schoeberl, Martin, additional, and Sorensen, Jonas Ingerslev, additional

Published
2022
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30. Lambert Function in the Determining of the Noise Equilibrium Frequency for Radiation Detectors

Author

Teodorescu, Horia-Nicolai L. and Pinker, Jiří

Subjects
radiation detector, optimalizace, zesilovač, optimal frequency bandwidth, Lambert function, amplifier, detektor záření, optimální frekvenční pásmo, Lambertova funkce, equilibrium noise frequency, optimization
Abstract

We analyze several cases of combined noise in sensors for radiation and in sensor-amplifier circuits. Solutions are shown to involve the Lambert function of various variables when the unknown is a frequency limit of the bandwidth. The coverage of the paper is essentially theoretical and its two aims are to exemplify the use of Lambert function in noise analysis and to help improving the design of pre-amplifiers, especially for radiation detectors.

Published
2022
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33. Seismic Energy Harvester for High Current Emergency Applications: Gas Valves and Alarms

Author

Teodorescu, Horia-Nicolai L. and Pinker, Jiří

Subjects
energy harvesting, zemětřesení, nouzový uzavírací ventil, blasts, asistovaný nouzový ventil, výbuchy, sklizení energie, mergency shut-off valve, inductive coil, assisted emergency valve, earthquakes, indukční cívka
Abstract

The paper explores if an energy harvester can be used as a sensor for the detection of waves from events such as earthquakes and blasts and at the same time produce high currents for use in an emergency gas valve. A design is proposed for an energy harvester and device that can improve the reliable operation of such valves. The same energy harvester is usable in alarms for seismic events.

Published
2022
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42. Human activity recognition from textile electrocardiograms

Author

Arne Klingenberg, Valentin Purrucker, Willi Schuler, Nagarajan Ganapathy, Nicolai Spicher, and Thomas M. Deserno

Subjects
Electrocardiography, Heart Rate, Textiles, Humans, Human Activities, Neural Networks, Computer
Abstract

Textile sensors for physiological signals bear the potential of unobtrusive and continuous application in daily life. Recently, textile electrocardiography (ECG) sensors became available which are of particular interest for physical activity monitoring due to the high effect of exercise on the heart rate. In this work, we evaluate the effectiveness of a single-lead ECG signal acquired using a non-medical-grade ECG shirt for human activity recognition (HAR). Healthy volunteers (N=10) wore the shirt during four different activities (sleeping, sitting, walking, running) in an uncontrolled environment and ECG data (256 Hz, 12 Bit) was stored, manually checked, and unusable segments (e.g. no sensor contact) were removed, resulting in a total of 228 hours of recording. Signals were split in short segments of different duration (10, 30, 60s), transformed using the Short-time Fourier Transform (STFT) to a spectrogram image and fed into a state-of-the-art convolutional neural network (CNN). The best configuration results in an F'l-Score of 73% and an accuracy of 77% on the test set. Results with leave-one-subject-out cross-validation show F'l-Scores ranging from 41 % to 80%. Thus, a single-lead, wearable-generated ECG has an informative value for HAR to a certain extent. In future work, we aim at using more sensors of the smart shirt and sensor fusion.

Published
2022
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43. Sensor Fusion for Robust Heartbeat Detection during Driving

Author

Joana M Warnecke, Nicolai Boeker, Nicolai Spicher, Ju Wang, Maximilian Flormann, and Thomas M Deserno

Subjects
Ballistocardiography, Electrocardiography, Heart Rate, Humans, Neural Networks, Computer, Photoplethysmography
Abstract

Private spaces like apartments and vehicles are not yet fully exploited for health monitoring, which includes continuous measurement of biosignals. This work proposes sensor fusion for robust heartbeat detection in the noisy and dynamic driving environment. We use four sensors: electrocardiography (ECG), ballistocardiography (BCG), photoplethysmography (PPG), and image-based PPG (iPPG). As ground truth, we record a 3-lead ECG with wet electrodes attached to the chest. Twelve healthy volunteers are monitored in rest and during driving, each for 11 min. We propose sensor fusion using convolutional neural networks to detect the sensor combination delivering the most accurate heart rate measurement. For rest, we achieve scores of 95.16% (BCG + iPPG), 96.08% (ECG + iPPG), 96.35% (ECG + BCG), 96.53% (ECG + PPG), 96.58% (PPG + iPPG), and 97.15% (BCG + PPG). In motion, the highest scores are 92.46% (BCG + iPPG, PPG + iPPG, ECG + iPPG), 92.83% (ECG + PPG), 93.03% (BCG + PPG), and 93.08% (ECG + BCG). Fusing all four signals with the best fusion approach results in scores of 97.24% (rest) and 94.38% (motion). We conclude that sensor fusion allows robust heartbeat measurement of car drivers to support continuous and unobtrusive health monitoring for early disease detection.

Published
2021
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