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iWOAR '17: Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction
ACM2017 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
iWOAR '17: 4th international Workshop on Sensor-based Activity Recognition and Interaction Rostock Germany September 21 - 22, 2017
ISBN:
978-1-4503-5223-9
Published:
21 September 2017
In-Cooperation:
Rostock
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Abstract

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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SESSION: Keynotes
invited-talk
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 ...

invited-talk
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 ...

SESSION: Information and Communication Technology in Healthcare and Medical Applications
research-article
Experiences from a Wearable-Mobile Acquisition System for Ambulatory Assessment of Diet and Activity
Article No.: 3, Pages 1–8https://doi.org/10.1145/3134230.3134239

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 ...

research-article
Smartwatch based Respiratory Rate and Breathing Pattern Recognition in an End-consumer Environment
Article No.: 4, Pages 1–5https://doi.org/10.1145/3134230.3134235

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 &...

research-article
Low-level Event Detection System for Minimally-Invasive Surgery Training
Article No.: 5, Pages 1–6https://doi.org/10.1145/3134230.3134241

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 ...

SESSION: Towards future Activity Recognition Algorithms
research-article
Where are my colleagues?: Tracking and Counting Multiple Persons using Lifted Marginal Filtering
Article No.: 6, Pages 1–6https://doi.org/10.1145/3134230.3134237

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 ...

research-article
Knowledge Extraction from Task Narratives
Article No.: 7, Pages 1–6https://doi.org/10.1145/3134230.3134234

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 ...

research-article
Co-Creating Emotionally Aligned Smart Homes Using Social Psychological Modeling
Article No.: 8, Pages 1–6https://doi.org/10.1145/3134230.3134242

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 ...

SESSION: Wearable Technologies and Activity Recognition Approaches
research-article
Exercise Monitoring On Consumer Smart Phones Using Ultrasonic Sensing
Article No.: 9, Pages 1–6https://doi.org/10.1145/3134230.3134238

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 ...

research-article
Bottom-up Investigation: Human Activity Recognition Based on Feet Movement and Posture Information
Article No.: 10, Pages 1–6https://doi.org/10.1145/3134230.3134240

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-...

research-article
Real-time Embedded Recognition of Sign Language Alphabet Fingerspelling in an IMU-Based Glove
Article No.: 11, Pages 1–6https://doi.org/10.1145/3134230.3134236

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 ...

SESSION: Manufacturing and Industrial Applications of Sensors and Intelligent Algorithms
research-article
Preliminary Evaluation of a Framework for Overhead Skeleton Tracking in Factory Environments using Kinect
Article No.: 12, Pages 1–6https://doi.org/10.1145/3134230.3134232

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 ...

research-article
Detecting Process Transitions from Wearable Sensors: An Unsupervised Labeling Approach
Article No.: 13, Pages 1–6https://doi.org/10.1145/3134230.3134233

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 ...

research-article
Deep Neural Network based Human Activity Recognition for the Order Picking Process
Article No.: 14, Pages 1–6https://doi.org/10.1145/3134230.3134231

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, ...

Contributors
  • University of Greifswald
  • University of Rostock
  • University of Rostock
  • University of Rostock

Recommendations

Acceptance Rates

iWOAR '17 Paper Acceptance Rate 12 of 19 submissions, 63%;
Overall Acceptance Rate 46 of 73 submissions, 63%
YearSubmittedAcceptedRate
iWOAR '19111091%
iWOAR '18281554%
iWOAR '17191263%
iWOAR '1615960%
Overall734663%