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Liu, Qingxin (author)Most injuries in football occur in the lower extremities due to high muscle stress. To prevent such injuries, the Dutch Football Association (KNVB) and the Delft University of Technology developed the Smart Sensor Shorts, an inertial sensor-based tracking system measuring the athlete’s lower body kinematics, to improve physical load estimates...master thesis 2023
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Tebbens, Ricardo (author)There is a raising demand for player statistics in the world of football. With the developments over the last years in wearable sensors, Human Activity Recognition (HAR) based on wearable IMU sensors can be used to tackle this problem. This thesis builds upon an earlier research done for this topic, where an end-to-end pipeline based on deep...master thesis 2023
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Fenwick, Kayla (author)Cooking is an essential part of most people’s day-to-day lives. It is a dynamic activity that involves multitasking, timing of tasks, and flexibility. However, the available instruction methods for cooks who wish to follow recipes are quite rigid and linear. This project aims to create a design solution that provides instructions in a way that...master thesis 2023
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Focante, Edoardo (author)In recent years, neural networks (NNs) have seen a surge in popularity due to their ability to model complex patterns and relationships in data. One of the challenges of using NNs is the requirement for large amounts of labelled data to train the model effectively. In many real-world applications such as radar, labelled data may be scarce due to...master thesis 2023
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Ciszewski, M.G. (author), Söhl, J. (author), Jongbloed, G. (author)The past decade has seen an increased interest in human activity recognition based on sensor data. Most often, the sensor data come unannotated, creating the need for fast labelling methods. For assessing the quality of the labelling, an appropriate performance measure has to be chosen. Our main contribution is a novel post-processing method...journal article 2023
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Ding, Chuanwei (author), Zhang, Li (author), Chen, Haoyu (author), Hong, Hong (author), Zhu, Xiaohua (author), Fioranelli, F. (author)Radar-based solutions have attracted great attention in human activity recognition (HAR) for their advantages in accuracy, robustness, and privacy protection. The conventional approaches transform radar signals into feature maps and then directly process them as visual images. While effective, these image-based methods may not be the best...journal article 2023
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Guo, Zhongyuan (author), Guendel, Ronny (author), Yarovoy, Alexander (author), Fioranelli, F. (author)Radar-based Human Activity Recognition(HAR) is considered by using snapshots of point clouds. Such point cloudsinterpret 2D images generated by an mm-wave FMCW MIMO radar enriched byincluding Doppler and temporal information. We use the similarity between suchradar data representation and the core of the self-attention concept inartificial...conference paper 2023
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Ghorbani, R. (author), Reinders, M.J.T. (author), Tax, D.M.J. (author)With the progress of sensor technology in wearables, the collection and analysis of PPG signals are gaining more interest. Using Machine Learning, the cardiac rhythm corresponding to PPG signals can be used to predict different tasks such as activity recognition, sleep stage detection, or more general health status. However, supervised...conference paper 2023
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Joint human motion recognition and breathing frequency estimation for indoor healthcare applicationsCORTES PERALTA, Max (author)The challenge of dealing with patients suffering from chronic diseases and an aging population requires evolving from traditional hospital-based healthcare systems into a person-centered approach, where patients can be monitored remotely via modern technologies by cost-effective and reliable solutions based on emerging technologies in the...master thesis 2022
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Guo, Zhongyuan (author)Today, with increasingly aging population, healthcare systems in many countries need to improve their effectiveness, and the automatic HAR technology can be beneficial. This can provide early diagnosis of changes in behavioral patterns in the home environment, without hospitalization, and detect critical events such as falls in a timely manner....master thesis 2022
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Vos, Jasper (author)In the field of Visible Light Sensing, light sensors are used to extract information from objects which do not actively communicate any information. Previous research within this field proposed the system called SolAR, and proved the possibility of using a solar cell as both a power source and an activity sensor. A wrist mounted solar cell...bachelor thesis 2022
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Poeth, Ole (author)Cognitive processes have been used in recent years for context sensing and this has shown promising results. Multiple sets of features have shown good performance but no set of features has been determined the best for classifying gaze data. This paper looks at different feature sets and the heterogeneity of gaze signals from subjects and...bachelor thesis 2022
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Chatalbasheva, Violeta (author)Sedentary activity recognition is an important research field due to its various positive implications in people’s life. This study builds upon previous research which is based on low level features extracted from the gaze signals using a fixation filter and uses a dataset of 24 participants performing 8 different sedentary activities. The main...bachelor thesis 2022
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Brockbernd, Bob (author)This research proposes a novel method to classify cognitive behavior based on eye-movement data. Most state-of-the-art approaches use conventional machine learning techniques needing manual feature extraction. This experiment explores the possibility of applying deep learning algorithms to cognitive activity recognition for feature extraction...bachelor thesis 2022
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Vaessen, Kasper (author)Classification of sedentary activities using gaze tracking data can be of great use in fields such as teaching, human-computer interaction and surveilling. Conventional machine learning methods such as k-nearest neighbours, random forest and support vector machine might be used to classify such activities, but this requires knowledge about the...bachelor thesis 2022
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Zhao, Yubin (author)Nowadays, the aging problem is shaking the root of the healthcare system in many countries, an automatic human activity recognition (HAR) is seen as a promising solution to that problem. In particular, radar-based HAR attracts people’s attention thanks to its respect for privacy and functionality in poor lighting conditions. With a lot of...master thesis 2022
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Yang, Ximei (author), Guendel, Ronny (author), Yarovoy, Alexander (author), Fioranelli, F. (author)Human activities classification in assisted living is one of the emerging applications of radar. The conventional analysis considers micro-Doppler signatures as the chosen input for feature extraction or deep learning classification algorithms, or, less frequently, other radar data formats such as the range-time, the range-Doppler, or the...conference paper 2022
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Li, Xinyu (author), He, Yuan (author), Fioranelli, F. (author), Jing, Xiaojun (author)Human activity recognition (HAR) plays a vital role in many applications, such as surveillance, in-home monitoring, and health care. Portable radar sensor has been increasingly used in HAR systems in combination with deep learning (DL). However, it is both difficult and time-consuming to obtain a large-scale radar dataset with reliable labels...journal article 2022
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Guendel, Ronny (author), Fioranelli, F. (author), Yarovoy, Alexander (author)Continuous Human Activity Recognition (HAR) in arbitrary directions is investigated using 5 spatially distributed pulsed Ultra-Wideband (UWB) radars. Such activities performed in arbitrary and unconstrained trajectories render a more natural occurrence of Activities of Daily Living (ADL) to be recognized. An innovative signal level fusion method...conference paper 2022
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Zhu, S. (author), Guendel, Ronny (author), Yarovoy, Alexander (author), Fioranelli, F. (author)Unconstrained human activities recognition with a radar network is considered. A hybrid classifier combining both convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for spatial–temporal pattern extraction is proposed. The 2-D CNNs (2D-CNNs) are first applied to the radar data to perform spatial feature extraction on the...journal article 2022