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For patients with epilepsy, automatic epilepsy monitoring, i.e., the process of direct observation of the patient’s health status in real time, is crucial. Wearable systems provide the possibility of real-time epilepsy monitoring and alerting caregivers upon the occurrence of a seizure. In the context of the ICASSP 2023 Seizure Detection Challenge, we pro- pose a lightweight machine-learning frame
Eye tracking has been used as part of software engineering and computer science research for a long time, and during this time new techniques for machine learning (ML) have emerged. Some of those techniques are applicable to the analysis of eye-tracking data, and to some extent have been applied. However, there is no structured summary available on which ML techniques are used for analysis in diff
Epilepsy is one of the most common neurological disorders that is characterized by recurrent and unpredictable seizures. Wearable systems can be used to detect the onset of a seizure and notify family members and emergency units for rescue. The majority of state-of-the-art studies in the epilepsy domain currently explore modern machine learning techniques, e.g., deep neural networks, to accurately
Clustering multiple motions from observed point trajectories is a fundamental task in understanding dynamic scenes. Most motion models require multiple tracks to estimate their parameters, hence identifying clusters when multiple motions are observed is a very challenging task. This is even aggravated for high-dimensional motion models. The starting point of our work is that this high-dimensionali
The advances in highly automated and autonomous transportation systems over the last decade have generated great interest in topics in the safe navigation of land vehicles. With distributed control strategies employed in the majority of applications of autonomous vehicles, such as traffic and formation control, the much-required resilience takes the form of fault-tolerance with respect to informat
Robotic systems for manipulation tasks are increasingly expected to be easy to configure for new tasks. While in the past, robot programs were often written statically and tuned manually, the current, faster transition times call for robust, modular and interpretable solutions that also allow a robotic system to learn how to perform a task. We propose the method Behavior-based Bayesian Optimizatio
The Storage Location Assignment Problem (SLAP) has a significant impact on the efficiency of warehouse operations. We propose a multi-phase optimizer for the SLAP, where the quality of an assignment is based on distance estimates of future-forecasted order-picking. Candidate assignments are first sampled using a Markov Chain accept/reject method. Order-picking Traveling Salesman Problems (TSPs) ar
In dynamic operational environments, particularly in collaborative robotics, the inevitability of failures necessitates robust and adaptable recovery strategies. Traditional automated recovery strategies, while effective for predefined scenarios, often lack the flexibility required for on-the-fly task management and adaptation to expected failures. Addressing this gap, we propose a novel approach
Background: MR-generated acoustic noise may be particularly concerning at 7-Tesla (T) systems. Noise levels can be reduced by altering gradient output using software optimization. However, such alterations might influence image quality or prolong scan times, and these optimizations have not been well characterized. Purpose: To evaluate image quality, sound pressure levels (SPLs), and perceived noi
We address the recognized person-to-person Brain–Computer Interface (BCI) calibration problem and tackle session-dependency through the use of unsupervised canonical polyadic (CP) tensor decomposition. For a motor imagery task, the approach reveals universal structures within EEG data, common between subjects and prominent for a certain task. Further, we develop a novel similarity measure that inc
The advent of 6G wireless communication marks a transformative era in technological connectivity, bringing forth challenges and opportunities alike. This paper unveils an innovative, open-source simulator, meticulously crafted for cell-free 6G wireless networks. This simulator is not just a tool but a gateway to the future, blending cutting-edge channel models with the simulation of both physical
The Storage Location Assignment Problem (SLAP) is of central importance in warehouse operations. An important research challenge lies in generalizing the SLAP such that it is not tied to certain order-picking methodologies, constraints, or warehouse layouts. We propose the OBP-based SLAP, where the quality of a location assignment is obtained by optimizing an Order Batching Problem (OBP). For the
Most work implies the use of digital systems and tools, thus, digital technology plays a vital role in modern work environments. Even so, ergonomics and usability of IT systems and digital tools used at work are often weak, which causes work-related health problems including physical, visual, cognitive, and stress-related issues. We pose that one important reason for these types of issues is the l
Precise patient positioning and daily anatomical verification are crucial in external beam radiotherapy to ensure accurate dose delivery and minimize harm to healthy tissues. However, Current image-guided radiotherapy techniques struggle to balance high-quality volumetric anatomical visualization and rapid low-dose imaging. Addressing this, reconstructing volumetric images from ultra-sparse X-ray
Lund University Creativity Knowledge Nätverket LUCK (Lund University Creativity Knowledge) syftar till att främja och utveckla kreativitetsforskning med fokus på kreativitetens process, villkor och utveckling inom olika verksamhetsområden, såsom näringsliv, akademi och skola. Nätverket består idag av forskare med olika inriktningar av kreativitetsforskning:Docent Eva Brodin (vetenskapspsykologi oc
https://www.psy.lu.se/forskning/forskningsnatverk/luck-network - 2025-12-19
The study aimed at examining recruiter’s experience of moral stress at recruiting and staffing companies in Sweden. Further purpose was to investigate dilemmas of four other psychological factors related to work, relevant for moral stress: cognition, emotion, control, and stress reactions. For moral stress and all other factors, differences based on sexes and work experience were investigated. An
L-DOPA-induced dyskinesia (LID) in Parkinson’s disease has been linked to oscillatory neuronal activities in the cortico-basal ganglia network. We set out to examine the pattern of cortico-basal ganglia oscillations induced by selective agonists of D1 and D2 receptors in a rat model of LID. Local field potentials were recorded in freely moving rats using large-scale electrodes targeting three moto
Songbirds have evolved diverse strategies to cope with seasonality, including long-, medium-, and short-distance migration. There is some evidence that birds with a longer migration distance deposit fuel faster. However, most studies focus on long-distance migrants. Comparisons between species with different migration distances are necessary to broaden our understanding of fueling capacity in migr
With the rapid advancement of autonomous vehicle technology, integrating mixed autonomous and non-autonomous vehicles that are not cooperative in vehicular network has become a significant challenge. This paper presents an innovative Autonomous Intersection Management (AIM) system designed to optimize traffic flow and enhance intersection safety in such mixed traffic scenarios. By utilizing vehicl
