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2019 Fiscal Year Research-status Report

Where is stressed processed in brain during sleep? -- A Neuroimaging study into stress-related abnormalities in brain activity during sleep

Research Project

Project/Area Number 19K20141
Research InstitutionKyoto University of Advanced Science

Principal Investigator

梁 滋路  京都先端科学大学, ナガモリアクチュエータ研究所, 講師 (10782807)

Project Period (FY) 2019-04-01 – 2021-03-31
KeywordsfNIRS / stress / sleep / brain imaging
Outline of Annual Research Achievements

The main research achievements has been the preparation of experiment equipment and devices and the application of ethics approval. The state-of-the-art in wearable brain imaging technologies and stress research was firstly investigated. A wearable Artinis 24-channel fNIR (functional Near Infra-Red Spectroscopy) and portable cortisol test kits were purchased. A web application for longitudinal data collection on daily life behavior and perceived stress was developed. Ethics approval was obtained from the ethics committee of Kyoto University of Advanced Science. A small-scale pilot study was conducted to test use the devices and the experiment protocol.

Current Status of Research Progress
Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

This study involves conducting longitudinal study using multiple wearable devices, mobile apps and cortisol kits. In the research plan, the first year was mostly devoted to the preparation of experiment equipment and devices and the ethics application. All tools needed for the experiment have been prepared, including a wearable Artinis 24-channel fNIR (functional Near Infra-Red Spectroscopy), a self-made web application for collecting data on daily behavior and perceived stress level, and portable cortisol test kits. Ethics approval has been obtained that allows the smooth running of the study. A small-scale pilot study was also conducted to test use the devices and the experiment protocol. Nevertheless, participants recruitment has been delayed due to the onset of the pandemics.

Strategy for Future Research Activity

In the data collection phase, the main experiment will be conducted on a smaller cohort (less than 10 participants) due to the pandemic situation. Due to safety concerns, the experiment will be conducted at participants' homes. The wearable Artinis 24-channel fNIR (functional Near Infra-Red Spectroscopy) will be used to monitor brain activities during sleep. A mobile app and cortisol test kits will be used to measure subjective and objective stress level. All devices will be thoroughly disinfected before applying on participants.

In the data analysis phase, signal processing and data mining techniques will be applied to identify brain areas in prefrontal cortex that are abnormally activated/suppressed by stress during the period of falling asleep. Gender difference will also be analyzed.

Causes of Carryover

The incurring amount is due to the delay of participants recruitment under the pandemic situation. This amount will be used to cover the cost occurred during the main experiment and participants incentives.

  • Research Products

    (20 results)

All 2020 2019 Other

All Int'l Joint Research (2 results) Journal Article (7 results) (of which Int'l Joint Research: 3 results,  Peer Reviewed: 7 results,  Open Access: 2 results) Presentation (7 results) (of which Int'l Joint Research: 1 results) Remarks (4 results)

  • [Int'l Joint Research] Queensland University of Technology(オーストラリア)

    • Country Name
      AUSTRALIA
    • Counterpart Institution
      Queensland University of Technology
  • [Int'l Joint Research] Trinity College Dublin(アイルランド)

    • Country Name
      IRELAND
    • Counterpart Institution
      Trinity College Dublin
  • [Journal Article] Developing mHealth App for Tracking Academic Stress and Physiological Reactions to Stress2020

    • Author(s)
      Liang Z, Oraphan T, Egholm AL
    • Journal Title

      Proceedings of The IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech)

      Volume: 0 Pages: 147-150

    • DOI

      10.1109/LifeTech48969.2020.1570618580

    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] How Does Fitbit Measure Brainwaves2020

    • Author(s)
      Liang Zilu、Ploderer Bernd
    • Journal Title

      Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

      Volume: 4 Pages: 1~29

    • DOI

      10.1145/3380994

    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Accuracy of Fitbit Wristbands in Measuring Sleep Stage Transitions and the Effect of User-Specific Factors2019

    • Author(s)
      Liang Zilu、Chapa-Martell Mario Alberto
    • Journal Title

      JMIR mHealth and uHealth

      Volume: 7 Pages: e13384~e13384

    • DOI

      10.2196/13384

    • Peer Reviewed / Open Access
  • [Journal Article] Achieving Accurate Ubiquitous Sleep Sensing with Consumer Wearable Activity Wristbands Using Multi-class Imbalanced Classification2019

    • Author(s)
      Liang Zilu、Chapa Martell Mario Alberto
    • Journal Title

      Proceedings of The IEEE International Conference on Pervasive Intelligence and Computing (PICOM)

      Volume: 0 Pages: 768-775

    • DOI

      10.1109/DASC/PiCom/CBDCom/CyberSciTech.2019.00143

    • Peer Reviewed
  • [Journal Article] Combining Resampling and Machine Learning to Improve Sleep-Wake Detection of Fitbit Wristbands2019

    • Author(s)
      Liang Zilu、Chapa-Martell Mario Alberto
    • Journal Title

      Proceedings of The IEEE International Conference on Healthcare Informatics (ICHI)

      Volume: 0 Pages: 1-3

    • DOI

      10.1109/ICHI.2019.8904753

    • Peer Reviewed
  • [Journal Article] Combining Numerical and Visual Approaches in Validating Sleep Data Quality of Consumer Wearable Wristbands2019

    • Author(s)
      Liang Zilu、Martell Mario Alberto Chapa
    • Journal Title

      Proceedings of 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)

      Volume: 0 Pages: 777-782

    • DOI

      10.1109/PERCOMW.2019.8730805

    • Peer Reviewed
  • [Journal Article] A Quantified-Self Framework for Exploring and Enhancing Personal Productivity2019

    • Author(s)
      White Gary、Liang Zilu、Clarke Siobhan
    • Journal Title

      Proceedings of The IEEE International Conference on Content-Based Multimedia Indexing (CBMI)

      Volume: 0 Pages: 1-6

    • DOI

      10.1109/CBMI.2019.8877475

    • Peer Reviewed / Int'l Joint Research
  • [Presentation] A two-stage imbalanced learning method to sleep stage classification using consumer activity trackers2020

    • Author(s)
      Liang Zilu、Chapa Martell Mario Alberto
    • Organizer
      The 13th International Conference on Health Informatics
    • Int'l Joint Research
  • [Presentation] Towards automatic analysis of relationship between perceived stress and physical activity with self-tracking technologies2020

    • Author(s)
      Liang Zilu、Andersen Lys Egholm、Tatha Oraphan
    • Organizer
      IEICE General Conference 2020
  • [Presentation] Leveraging consumer activity trackers for sleep stage prediction2020

    • Author(s)
      Liang Zilu、Chapa Martell Mario Alberto
    • Organizer
      The 82th National Convention of the Information Processing Society of Japan
  • [Presentation] Moving beyond statistical analysis: applying association rule mining to discovering correlations between daily behavioral rhythm and sleep quality2019

    • Author(s)
      Liang Zilu、Chapa Martell Mario Alberto
    • Organizer
      The 26th Annual Meeting of the Japanese Society for Chronobiology
  • [Presentation] Measurement accuracy of consumer sleep tracking wristbands is associated to user-specific factors2019

    • Author(s)
      Liang Zilu、Chapa Martell Mario Alberto
    • Organizer
      The 74th Annual Meeting of the Japanese Society of Physical Fitness and Sports Medicine
  • [Presentation] Mining association rules in quantified self data for better sleep and productivity2019

    • Author(s)
      Liang Zilu、White Grey、Clarke Siobhan、Chapa Martell Mario Alberto
    • Organizer
      IEICE Society Conference
  • [Presentation] Predicting medical-grade sleep/wake classification from Fitbit data using tree-based machine learning2019

    • Author(s)
      Liang Zilu、Chapa Martell Mario Alberto
    • Organizer
      IPSJ SIG Technical Report
  • [Remarks] Personal Website

    • URL

      https://www.zilu-liang.net/research-projects

  • [Remarks] ResearchGate Profile

    • URL

      https://www.researchgate.net/profile/Zilu_Liang

  • [Remarks] Google Scholar Profile

    • URL

      https://scholar.google.co.jp/citations?user=UlMDCkQAAAAJ&hl=ja

  • [Remarks] DBLP Profile

    • URL

      https://dblp.org/pers/l/Liang:Zilu.html

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Published: 2021-01-27  

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