Ubiquitous systems are becoming an integral part of our everyday lives. Functionality and user experience often depends on accurate, sensor-based activity recognition and interaction. Systems aiming to provide the user with assistance or to monitor their behavior and condition rely heavily on sensors and the activities and interactions that they can recognize. Providing adequate activity recognition and interaction requires consideration for particular elements: sensors that are capable of capturing relevant behavior, methods that reason about sensor readings in the context of these behaviors, and appropriate methods for assisting and interacting with the user. All of these aspects are essential and can influence the quality and suitability of the provided service.
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Smarter Smart Homes with Social and Emotional Intelligence
Pervasive intelligent assistive technologies promise to alleviate some of the increasing burden of care for persons with age-related cognitive disabilities, such as Alzheimer's disease. However, despite tremendous progress, many attempts to develop and ...
The SPHERE Experience
The talk will describe the experience for researchers and the public alike in co-producing and deploying at scale a bespoke wearable, video and environmental sensor system for activity monitoring at home. It will consider the health requirements that ...
Experiences from a Wearable-Mobile Acquisition System for Ambulatory Assessment of Diet and Activity
- Kristof Van Laerhoven,
- Mario Wenzel,
- Anouk Geelen,
- Christopher Hübel,
- Maike Wolters,
- Antje Hebestreit,
- Lene Frost Andersen,
- Pieter van't Veer,
- Thomas Kubiak
Public health trends are currently monitored and diagnosed based on large studies that often rely on pen-and-paper data methods that tend to require a large collection campaign. With the pervasiveness of smart-phones and -watches throughout the general ...
Smartwatch based Respiratory Rate and Breathing Pattern Recognition in an End-consumer Environment
Smartwatches as wearables became part of social life and practically and technically offer the possibility to collect medical body parameters next to usual fitness data. In this paper, we present an evaluation of the respiratory rate detection of the &...
Low-level Event Detection System for Minimally-Invasive Surgery Training
We present an event detection system in a laparoscopic surgery domain, as part of a more ambitious supervision by observation project. The system, which only requires the incorporation of two cameras in a laparoscopic training box, integrates several ...
Where are my colleagues?: Tracking and Counting Multiple Persons using Lifted Marginal Filtering
Tracking multiple targets with anonymous sensors (e.g. presence sensors) leads to a combinatorial explosion in the number of possible siuations (hypotheses) that need to be tracked, due to the uncertainty of the association of identities to observed ...
Knowledge Extraction from Task Narratives
One of the major difficulties in activity recognition stems from the lack of a model of the world where activities and events are to be recognised. When the domain is fixed and repetitive we can manually include this information using some kind of ...
Co-Creating Emotionally Aligned Smart Homes Using Social Psychological Modeling
Smart homes have long been proposed as a viable mechanism to promote independent living for older adults in the home environment. Despite tremendous progress on the technology front, there has been limited uptake by end-users. A critical barrier to the ...
Exercise Monitoring On Consumer Smart Phones Using Ultrasonic Sensing
Quantified self has been a trend over the last several years. An increasing number of people use devices, such as smartwatches or smartphones to log activities of daily life, including step count or vital information. However, most of these devices have ...
Bottom-up Investigation: Human Activity Recognition Based on Feet Movement and Posture Information
Human Activity Recognition (HAR) research on feet posture and movement information has seen an intense growth during the last five years, drawing attention of fields such as healthcare systems and context inference. In this work, we tested our 6-...
Real-time Embedded Recognition of Sign Language Alphabet Fingerspelling in an IMU-Based Glove
- Chaithanya Kumar Mummadi,
- Frederic Philips Peter Leo,
- Keshav Deep Verma,
- Shivaji Kasireddy,
- Philipp Marcel Scholl,
- Kristof Van Laerhoven
Data gloves have numerous applications, including enabling novel human-computer interaction and automated recognition of large sets of gestures, such as those used for sign language. For most of these applications, it is important to build mobile and ...
Preliminary Evaluation of a Framework for Overhead Skeleton Tracking in Factory Environments using Kinect
This paper presents a preliminary evaluation of a framework that allows an overhead RGBD camera to segment and track workers skeleton in an unstructured factory environment. The default Kinect skeleton tracking algorithm was developed using front-view ...
Detecting Process Transitions from Wearable Sensors: An Unsupervised Labeling Approach
Authoring protocols for manual tasks such as following recipes, manufacturing processes, or laboratory experiments requires a significant effort. This paper presents a system that estimates individual procedure transitions from the user's physical ...
Deep Neural Network based Human Activity Recognition for the Order Picking Process
- Rene Grzeszick,
- Jan Marius Lenk,
- Fernando Moya Rueda,
- Gernot A. Fink,
- Sascha Feldhorst,
- Michael ten Hompel
Although the fourth industrial revolution is already in pro-gress and advances have been made in automating factories, completely automated facilities are still far in the future. Human work is still an important factor in many factories and warehouses, ...