Skip to main content
SpringerLink
Log in

Human Activity Sensing

Corpus and Applications

  • Book
  • © 2019

Overview

Editors:
  1. Nobuo Kawaguchi

    1. Institute of Innovation for Future Society, Nagoya University, Nagoya, Japan

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Nobuhiko Nishio

    1. Department of Computer Science, Ritsumeikan University, Kyoto, Japan

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Daniel Roggen

    1. University of Sussex, Brighton, UK

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  4. Sozo Inoue

    1. Kyushu Institute of Technology, Kitakyushu, Japan

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  5. Susanna Pirttikangas

    1. Center for Ubiquitous Computing, University of Oulu, Oulu, Finland

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  6. Kristof Van Laerhoven

    1. Ubiquitous Computing, University of Siegen, Siegen, Germany

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • The first collection of best practices and methodologies for activity recognition, by some of the most experienced activity recognition experts
  • A community-based approach to assemble study results and data set collections from common human activities
  • Latest trends and challenge definitions in the area of context and activity recognition

Part of the book series: Springer Series in Adaptive Environments (SPSADENV)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (15 chapters)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  2. Modalities and Applications

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Optimizing of the Number and Placements of Wearable IMUs for Automatic Rehabilitation Recording

      • Kohei Komukai, Ren Ohmura
      Pages 3-15

    3. Identifying Sensors via Statistical Analysis of Body-Worn Inertial Sensor Data

      • Philipp M. Scholl, Kristof Van Laerhoven
      Pages 17-28

    4. Compensation Scheme for PDR Using Component-Wise Error Models

      • Junto Nozaki, Kei Hiroi, Katsuhiko Kaji, Nobuo Kawaguchi
      Pages 29-46

    5. Towards the Design and Evaluation of Robust Audio-Sensing Systems

      • Akhil Mathur, Anton Isopoussu, Fahim Kawsar, Robert Smith, Nadia Berthouze, Nicholas D. Lane
      Pages 47-57

    6. A Wi-Fi Positioning Method Considering Radio Attenuation of Human Body

      • Shohei Harada, Kazuya Murao, Masahiro Mochizuki, Nobuhiko Nishio
      Pages 59-68

  3. Data Collection and Corpus Construction

    1. Front Matter

      Pages 69-69
      Download chapter PDF

    2. Drinking Gesture Recognition from Poorly Annotated Data: A Case Study

      • Mathias Ciliberto, Lin Wang, Daniel Roggen, Ruediger Zillmer
      Pages 71-89

    3. Understanding How Non-experts Collect and Annotate Activity Data

      • Naomi Johnson, Michael Jones, Kevin Seppi, Lawrence Thatcher
      Pages 91-110

    4. A Multi-media Exchange Format for Time-Series Dataset Curation

      • Philipp M. Scholl, Benjamin Völker, Bernd Becker, Kristof Van Laerhoven
      Pages 111-119

    5. OpenHAR: A Matlab Toolbox for Easy Access to Publicly Open Human Activity Data Sets—Introduction and Experimental Results

      • Pekka Siirtola, Heli Koskimäki, Juha Röning
      Pages 121-133

    6. MEASURed: Evaluating Sensor-Based Activity Recognition Scenarios by Simulating Accelerometer Measures from Motion Capture

      • Paula Lago, Shingo Takeda, Tsuyoshi Okita, Sozo Inoue
      Pages 135-149

  4. SHL: An Activity Recognition Challenge

    1. Front Matter

      Pages 151-152
      Download chapter PDF

    2. Benchmark Performance for the Sussex-Huawei Locomotion and Transportation Recognition Challenge 2018

      • Lin Wang, Hristijan Gjoreski, Mathias Ciliberto, Sami Mekki, Stefan Valentin, Daniel Roggen
      Pages 153-170

    3. Bayesian Optimization of Neural Architectures for Human Activity Recognition

      • Aomar Osmani, Massinissa Hamidi
      Pages 171-195

    4. Into the Wild—Avoiding Pitfalls in the Evaluation of Travel Activity Classifiers

      • Peter Widhalm, Maximilian Leodolter, Norbert Brändle
      Pages 197-211

    5. Effects of Activity Recognition Window Size and Time Stabilization in the SHL Recognition Challenge

      • Michael Sloma, Makan Arastuie, Kevin S. Xu
      Pages 213-231

    6. Winning the Sussex-Huawei Locomotion-Transportation Recognition Challenge

      • Vito Janko, Martin Gjoreski, Gašper Slapničar, Miha Mlakar, Nina Reščič, Jani Bizjak et al.
      Pages 233-250
Back to top

Keywords

About this book

Activity recognition has emerged as a challenging and high-impact research field, as over the past years smaller and more powerful sensors have been introduced in wide-spread consumer devices. Validation of techniques and algorithms requires large-scale human activity corpuses and improved methods to recognize activities and the contexts in which they occur. 

This book deals with the challenges of designing valid and reproducible experiments, running large-scale dataset collection campaigns, designing activity and context recognition methods that are robust and adaptive, and evaluating activity recognition systems in the real world with real users.


Editors and Affiliations

  • Institute of Innovation for Future Society, Nagoya University, Nagoya, Japan

    Nobuo Kawaguchi

  • Department of Computer Science, Ritsumeikan University, Kyoto, Japan

    Nobuhiko Nishio

  • University of Sussex, Brighton, UK

    Daniel Roggen

  • Kyushu Institute of Technology, Kitakyushu, Japan

    Sozo Inoue

  • Center for Ubiquitous Computing, University of Oulu, Oulu, Finland

    Susanna Pirttikangas

  • Ubiquitous Computing, University of Siegen, Siegen, Germany

    Kristof Van Laerhoven

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation