Daily Life Activity Recognition with a Head Mounted IMU on Older Adults: Which Features to Extract?

As the population aged 65 and above increases, falls among these older adults emerge as a significant public health concern, leading to disabil- ities and economic burdens. Preventative strategies and personalized fall risk assessments are essential for mitigating fall risks. Human Activity Recognition in early fall risk detection by monitoring...

(Near) Real-time Data Analysis for Smart Sensor Shorts in Football

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...

Football activity recognition: Improving and testing football activity recognition based on signal data using deep learning.

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...

An Interactive & Hands-free Instruction-based Cooking Experience

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...

Joint human motion recognition and breathing frequency estimation for indoor healthcare applications

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...

Point Transformer-Based Human Activity Recognition using high-dimensional Radar Point Clouds

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....

Light Based Activity Recognition Using Realistic Data

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...

Gaze-Based Activity Recognition with a LSTM

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...

Cognitive activity recognition by analyzing eye movement with convolutional neural networks

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...

Multiple Target Tracking and Human Activity Recognition based on The IR-UWB Radar Sensor Networks

Performing joint tracking and classification is the ultimate goal for many radar-based applications. For example, in indoor monitoring scenario, it is important to know the target's position as well as the related activities performed by that target. However, the literature often treats the joint problem independently due to its complexity. As a...

Football activity recognition: A deep learning approach to football activity recognition based on Inertial Measurement Units signals

been given to Human Activity Recognition (HAR) based on signals obtained by IMUs placed on different body parts. This thesis studies the usage of Deep Learning-based models to recognize different football activities in an accurate, robust, and fast manner. Several deep architectures were trained with data captured with IMU sensors placed on...

Human Activity Recognition using a Deep Learning Algorithm for Patient Monitoring

Physical activity and mobility are important indicators of the recovery process of patients in the general ward of the hospital. Currently, monitoring mobility of hospitalized patients relies largely on direct observation from the caregivers. Accelerometers have the potential to quantify physical activity of patients objectively and without...