User profiles for Artur Piet
Artur PietexpandAI GmbH | University of Lübeck Verified email at uni-luebeck.de Cited by 101 |
SenseHunger: Machine learning approach to hunger detection using wearable sensors
The perception of hunger and satiety is of great importance to maintaining a healthy body
weight and avoiding chronic diseases such as obesity, underweight, or deficiency syndromes …
weight and avoiding chronic diseases such as obesity, underweight, or deficiency syndromes …
Sleep stage classification in children using self-attention and Gaussian noise data augmentation
The analysis of sleep stages for children plays an important role in early diagnosis and
treatment. This paper introduces our sleep stage classification method addressing the following …
treatment. This paper introduces our sleep stage classification method addressing the following …
[Regular Paper] Biomedical Data Acquisition and Processing to Recognize Emotions for Affective Learning
Emotion recognition is a increasingly popular topic because of its potential applications in the
field of affective learning. It allows the development of systems able to adapt themselves to …
field of affective learning. It allows the development of systems able to adapt themselves to …
Sensor-based classification of primary and secondary car driver activities using convolutional neural networks
To drive safely, the driver must be aware of the surroundings, pay attention to the road traffic,
and be ready to adapt to new circumstances. Most studies on driving safety focus on …
and be ready to adapt to new circumstances. Most studies on driving safety focus on …
Predicting executive functioning from walking features in Parkinson's disease using machine learning
Parkinson’s disease is characterized by motor and cognitive deficits. While previous work
suggests a relationship between both, direct empirical evidence is scarce or inconclusive. …
suggests a relationship between both, direct empirical evidence is scarce or inconclusive. …
Non-invasive wearable devices for monitoring vital signs in patients with type 2 diabetes mellitus: a systematic review
A Piet, L Jablonski, JI Daniel Onwuchekwa, S Unkel… - Bioengineering, 2023 - mdpi.com
Type 2 diabetes mellitus (T2D) poses a significant global health challenge and demands
effective self-management strategies, including continuous blood glucose monitoring (CGM) …
effective self-management strategies, including continuous blood glucose monitoring (CGM) …
[HTML][HTML] Optimizing sleep staging on multimodal time series: Leveraging borderline synthetic minority oversampling technique and supervised convolutional …
Sleep is an important research area in nutritional medicine that plays a crucial role in human
physical and mental health restoration. It can influence diet, metabolism, and hormone …
physical and mental health restoration. It can influence diet, metabolism, and hormone …
[HTML][HTML] The detection of alcohol intoxication using electrooculography signals from smart glasses and machine learning techniques
The operation of a motor vehicle under the influence of alcohol poses a significant risk to
the safety of the driver, passengers, and other road users. Electrooculographic (EOG) signal …
the safety of the driver, passengers, and other road users. Electrooculographic (EOG) signal …
ParkProReakt-Evaluation of a proactive approach to health care in Parkinson's disease: a study protocol for a randomised controlled trial
Introduction Parkinson's disease (PD) causes significant impairment due to both motor and
non-motor symptoms, which severely impact patients' health-related quality of life (HRQoL) …
non-motor symptoms, which severely impact patients' health-related quality of life (HRQoL) …
Exploring the Benefits of Time Series Data Augmentation for Wearable Human Activity Recognition.
Wearable Human Activity Recognition (HAR) is an important field of research in smart assistive
technologies. Collecting the data needed to train reliable HAR classifiers is complex and …
technologies. Collecting the data needed to train reliable HAR classifiers is complex and …