5th International Workshop on Human Activity Sensing Corpus and Application: Towards Open-Ended Context Awareness


September 11th (Monday)

Each paper : 25min talk including discussion


(Nobuo Kawaguchi)


Session 1:
(Chair: Nobuo Kawaguchi)

When Generalized Eating Detection Machine Learning Models Fail in the Field

Shibo Zhang (Northwestern University), Rawan Alharbi, Matthew Nicholson, Nabil Alshurafa

Generic Online Animal Activity Recognition on Collar Tags

Jacob W. Kamminga (University of Twente Enschede), Helena C. Bisby, Duc V. Le, Nirvana Meratnia, Paul J.M. Havinga

SPINDLES: A Smartphone Platform for Intelligent Detection and Notification of Leg Shaking

Stephen Xia (Columbia University), Yan Lu, Peter Wei, Xiaofan Jiang

Hybrid Approach for Reliable Floor Recognition Method

Taiga Nishiyama, Masahiro Mochizuki, Kazuya Murao, Nobuhiko Nishio (Ritsumeikan University)


Lunch Break


Session 2:
(Chair: Susanna Pirttikangas)

Smartphone Detection of Collapsed Buildings During Earthquakes

Aku Visuri (University of Oulu), Zeyun Zhu, Denzil Ferreira, Shin'ichi Konomi, Vassilis Kostakos

Compensation Scheme for PDR using Sparse Location and Error Model

Junto Nozaki (Nagoya University), Kei Hiroi, Katsuhiko Kaji (Aichi Institute of Technology), Nobuo Kawaguchi (Nagoya University)

Detecting Aged Deterioration of a Radio Base Station Map for Wi-Fi Positioning

Makiko Kawanaka , Kohei Yamamoto, Kota Tsubouchi, Kazuya Murao, Masahiro Mochizuki, Nobuhiko Nishio(Ritsumeikan University)


Coffee Break


Session 3:
(Chair: Nobuhiko Nishio )

A Location Estimation Method using Mobile BLE Tags with Tandem Scanners

Kenta Urano (Nagoya University), Katsuhiko Kaji (Aichi Institute of Technology), Kei Hiroi (Nagoya University), Nobuo Kawaguchi

MyoGym - Introducing an Open Gym Data Set for Activity Recognition Collected Using Myo Armband

Heli Koskimaki (University of Oulu), Pekka Siirtola, Juha Roning

Designing a Context-Aware Assistive Infrastructure for Elderly Care

Simon Klakegg (University of Oulu), Niels van Berkel, Aku Visuri, Hanna-Leena Huttunen, Simo Hosio, Chu Luo, Jorge Goncalves, Denzil Ferreira


Discussion and Closing Remarks

Program Added!

Workshop Program

Important Dates:

Workshop Day:Sep 11th, 2017

Submission: June 9th -> June 21th, 2017 (Deadline Extended!)

Notification of acceptance: June 28th -> July 3rd, 2017

Camera ready: July 12th, 2017 -> July 17th(Mon), 2017

Welcome to HASCA2017

Welcome to HASCA2017 Web site!

HASCA2017 is a fifth workshop for Human Activity Sensing Corpus and Application: Towards Open-Ended Context Awareness. The workshop will be held in conjunction with UbiComp2017.


Technological advances enable the inclusion of miniature sensors (e.g. accelerometers, gyroscopes) on a variety of wearable/portable information devices. Most current devices only utilize these sensors for simple orientation and gesture recognition. However in the future the recognition of more complex and subtle human behaviours from these sensors will enable next-generation human-oriented computing in scenarios of high societal value (e.g. dementia care). This will require large scale human activity corpuses and much improved methods to recognize activities and the context in which they occur. This workshop deals with the challenges of designing reproducible experimental setups, running large scale dataset collection campaigns, designing activity and context recognition methods that are robust and adaptive, and evaluating systems in the real world.

As a special topic this year, we wish to reflect on the challenges and possible approaches to recognize situations, events or activities outside of a statically pre-defined pool - which is the current state of the art - and instead adopt an open-ended view on activity and context awareness. Following the huge success of previous years, we are further planning to share these experiences of current research on human activity corpus and their applications among the researchers and the practitioners and to have a deep discussion on the future of activity sensing, in particular towards open-ended contextual intelligence.

We solicit the following topics (but not limited to).

Data collection / Corpus construction

Experiences or reports from the data collection and/or corpus construction projects. Also includes the papers which describing the formats, styles or methodologies for data collection. Cloud-sourcing data collection or participatory sensing also could be included in this topic.

Effectiveness of Data / Data Centric Research

There is a field of research based on the collected corpus, which is called “Data Centric Research”. Also, we solicit of the experience of using large-scale human activity sensing corpus. Using large-scale corpus with machine learning technology, there will be a large space for improving the performance of recognition results.

Tools and Algorithms for Activity Recognition

If we have appropriate and suitable tools for management of sensor data, activity recognition researchers could be more focused on their research theme. However, development of tools or algorithms for sharing among the research community is not much appreciated. In this workshop, we solicit development reports of tools and algorithms for forwarding the community.

Real World Application and Experiences

Activity recognition “in the Lab” usually works well. However, it is not true in the real world. In this workshop, we also solicit the experiences from real world applications. There is a huge gap/valley between “Lab Environment” and “Real World Environment”. Large scale human activity sensing corpus will help to overcome this gap/valley.

Sensing Devices and Systems

Data collection is not only performed by the “off the shelf” sensors. There is a requirement to develop some special devices to obtain some sort of information. There is also a research area about the development or evaluate the system or technologies for data collection.

In light of this year's special emphasis on open-ended contextual awareness, we wish cover these topics as well:

Mobile experience sampling, experience sampling strategies:

Advances in experience sampling approaches, for instance intelligently querying the user or using novel devices (e.g. smartwatches) are likely to play an important role to provide user-contributed annotations of their own activities.

Unsupervised pattern discovery

Discovering meaningful repeating patterns in sensor data can be fundamental in informing other elements of a system generating an activity corpus, such as inquiring user or triggering annotation crowd sourcing.

Dataset acquisition and annotation through crowdsourcing,

A wide abundance of sensor data is potentially in reach with users instrumented with their mobile phones and other wearables. Capitalising on crowd-sourcing to create larger datasets in a cost effective manner may be critical to open-ended activity recognition. Online datasets could also be used to bootstrap recognition models.

Transfer learning, semi-supervised learning, lifelong learning

The ability to translate recognition models across modalities or to use minimal supervision would allow to reuse datasets across domains and reduce the costs of acquiring annotations.