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Studying pedestrians´ crossing behavior during automated vehicle interactions: A Wizard of Oz study
As a substitute for communication with a human driver, additional communication cues for AVs have been proposed [1]. To analyze their effect on traffic flow, preceding studies captured pedestrians´ crossing decision in an unnatural manner, e.g., via ...
Fine-Grained Human Activity Recognition - A new paradigm
Nowadays, fine-grained Human Activity Recognition (HAR) has become extremely interesting among researchers due to its applications in fields such as healthcare, security, sports, and smart environments. In this paper, we provide a brief overview of the ...
Discovering Behavioural Predispositions in Data to Improve Human Activity Recognition
The automatic, sensor-based assessment of challenging behavior of persons with dementia is an important task to support the selection of interventions. However, predicting behaviors like apathy and agitation is challenging due to the large inter- and ...
Evaluating neurorehabilitation exercises captured with commodity sensors and machine-learning framework
During the last decades, disease-related disabilities, primarily caused by stroke have increased worldwide. Neurorehabilitation exercise therapy plays a vital role in the recovery of such disabilities. However, due to global demographic changes and the ...
Hand Gesture Recognition in Daily Life as an Additional Tool for Unobtrusive Data Labeling in Medical Studies
For many use cases, such as supervised machine learning, labeled data is needed. However, to collect information for labels in real-life contexts, scientists are confronted with the challenge of gathering labeled data over an extended period. Labeling ...
Activities of Daily Living Detection on Healthcare: A Categorization
The incremental advancement of sensor technology has positively impacted the field of activities of daily living (ADL) recognition and monitoring in Ambient Assisted Living (AAL) environments. People in AAL environments interact by means of electronic ...
ShoeTect: Detecting Body Posture, Ambulation Activity, Gait Abnormalities, and Terrain with Multisensory Smart Footwear
Our feet are not just used to walk upright, feet can also reveal important context information on our physical constitution and context. In this research, we present a proof-of-concept multisensory approach to uncover the hidden information our feet ...
Does my glucose level tell how energetic I feel?
Nowadays, many organisations steadily have to face new challenges due to an increasing competition, new technologies and manpower shortage. While dealing with this growth of challenges and confronting employees with higher demands, organizations have ...
Transformer-Based Recognition of Activities of Daily Living from Wearable Sensor Data
- Gabriela Augustinov,
- Muhammad Adeel Nisar,
- Frédéric Li,
- Amir Tabatabaei,
- Marcin Grzegorzek,
- Keywan Sohrabi,
- Sebastian Fudickar
Smart support systems for the recognition of Activities of Daily Living (ADLs) can help elderly people live independently for longer improving their standard of living. Many machine learning approaches have been proposed lately for Human Activity ...
Nurturing Cognitive Abilities of Older Adults Using NLP Models on Mobile Devices
Studies have shown that cognitive function and stamina are vulnerable to aging. Susceptibility to such age-related decline can be related to many factors, including education, literacy, occupation, and engagement in leisure activities. In this paper, we ...
Online Personalisation of Deep Mobile Activity Recognisers
- Manuel Milling,
- Ilhan Aslan,
- Moritz Berghofer,
- Adria Mallol-Ragolta,
- Utkarsh Kunwar,
- Björn Wolfgang Schuller
Activity recognition is an increasingly important feature in mobile consumer devices that enables the design of context-aware applications and the customisation of user experiences. Recent deep learning-based recognisers demonstrate promising ...
Reducing Deployment Cost for Passive Electric Field Sensors
Electric field sensors are used in a variety of ways to recognize different human actions and behaviors, for example, fall detection or classification of movements. However, very little is known about the number of sensors that are needed to achieve an ...
Camera-based Blink Detection using 3D-Landmarks
Working in front of the computer for long periods of time leads to exhaustion, fatigue and high strain on the eyes. Often the natural eye blink activity is disturbed and the eyes do not form enough tears to stay moist. Computer workstations are usually ...
Dataset and Methods for Recognizing Care Activities
A major challenge in stationary care in hospitals is the limited amount of time for each patient due to a large overhead being created by manual documentation efforts. Studies show that it is common for caregivers to spend more than one hour per day for ...