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---
layout: splash
author_profile: false
toc: false
header:
# image: /assets/images/header1600.png
image: /assets/images/challenge2023.png
image_description: "2023 Wearing-Off Recognition Challenge"
---
<!-- Submissions are open! <br /> -->
<!-- <a href="/cook2020/submit/">Send your results</a> -->
<!-- <br /> -->
<p> <b>Wearing-off phenomenon</b> is experienced by Parkinson’s disease (PD) patients when their symptoms re-appear before their next medicine intake. Over time, the medicine’s effective time shortens, causing discomfort among PD patients. Thus, PD patients and clinicians must monitor and record the patient symptom changes for adequate treatment.
<p> Parkinson's disease (PD) is a slowly progressive nervous system condition caused by the loss of dopamine-producing brain cells. It primarily affects the patient's motor abilities, but it also has an impact on non-motor functions over time. Patients' symptoms include tremors, muscle stiffness, and difficulty walking and balancing. Then it disrupts the patients' sleep, speech, and mental functions, affecting their quality of life (QoL).
<p> With the improvement of wearable devices, patients can be continuously monitored with the help of cell phones and fitness trackers. We use these technologies to monitor patients' health, record WO periods, and document the impact of treatment on their symptoms in order to predict the wearing-off phenomenon in Parkinson's disease patients.
<h2> Challenge Goal and Task</h2>
The goal of this challenge is to forecast the wearing-off in the next hour given past data.
In a real-world setting, a smartphone app is used to collect fitness tracker data and self-reported symptoms.
This will help the doctors to create specific treatment strategies to manage Parkinson's disease and its associated symptoms properly.
Participants are tasked to create a model that can anticipate the "wearing-off" of anti-PD medication. The original project is one of the <a href="https://www.kyutech.ac.jp/english/en-news/topics/entry-9408.html#prettyPhoto">2022 Garmin Health Awards winners.</a></a>
<p></p>
<ul>
<li><a href="/challenge2023/faq/">Check out the FAQ</a></li>
<li><a href="https://ieee-dataport.org/competitions/5th-abc-challenge-forecasting-parkinsons-disease-patients-wearing-phenomenon-datasets">Download the dataset</a></li>
<li><a href="https://docs.google.com/forms/d/e/1FAIpQLSf7Gt2_fXfDKNt06OrwpkqhlMxXPJep0XDEbSnMtasfAxsbHg/viewform?edit_requested=true&fbzx=-5424371331795866531">Registration is now open</a></li>
</ul>
<p></p>
<p> <b>Published papers about the dataset</b> </p>
<ul>
<li> J. N. Victorino, Y. Shibata, S. Inoue, and T. Shibata, “Forecasting Parkinson’s Disease Patients’ Wearing-Off using Wrist-Worn Fitness Tracker and Smartphone Dataset,” in 4th International Conference on Activity and Behavior Computing (ABC 2022), 2022-10-27 - 2022-10-29, London, United Kingdom.
></li>
<li> J. N. Victorino, Y. Shibata, S. Inoue, and T. Shibata, “Predicting Wearing-Off of Parkinson’s Disease Patients Using a Wrist-Worn Fitness Tracker and a Smartphone: A Case Study,” Applied Sciences, vol. 11, no. 16, p. 7354, 2021. <a href="https://www.mdpi.com/2076-3417/11/16/7354">doi:10.3390/app11167354</a>
</li>
<li> J. N. Victorino, Y. Shibata, S. Inoue, and T. Shibata, “Understanding Wearing-Off Symptoms in Parkinson’s Disease Patients using Wrist-Worn Fitness Tracker and a Smartphone,” Procedia Computer Science, vol. 196, pp. 684-691, 2022. <a href="https://www.sciencedirect.com/science/article/pii/S1877050921022870?via%3Dihub">doi:10.1016/j.procs.2021.12.0644</a>
</li>
</ul>
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</p>
<ul>
<li><a href="/challenge2022/faq/">Check out the FAQ</a></li>
<li><a href="https://ieee-dataport.org/competitions/nurse-care-activity-recognition-challenge-datasets-2022-0">Download the dataset</a></li>
<li><a href="https://forms.gle/GLFrkG5AxxCEuduh8">Registration is now open</a></li>
</ul>
<p>The data we are providing this time is a part of the dataset which was used in our previous work, titled <a href="https://dl.acm.org/doi/abs/10.1145/3351244">“Integrating Activity Recognition and Nursing Care Records: The System, Deployment, and a Verification Study”</a>. The authors of this work proposed a theory that extending of start and end times of the activities can increase the prediction rate. The reason behind the theory is that many of the nurses provided the labels before or after completing an activity. In the paper, they verified and proved this theory. A part of this data set has also been used in last year's <a href="https://abc-research.github.io/nurse2021/">3rd nurse care challenge</a>. The summary paper is titled <a href="http://dx.doi.org/10.1145/3460418.3479391">”Summary of the Third Nurse Care Activity Recognition Challenge - Can We Do from the Field Data?"</a>.
</p>
-->
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<!-- <li><a href="https://ieee-dataport.org/competitions/bento-packaging-activity-recognition-challenge">Download train and test data</a></li> -->
<h2> Schedule </h2>
This Challenge will be held as part of the <a href="https://abc-research.github.io">ABC Conference 2023</a>
<ul>
<li><b>Challenge opens:</b> May 4, 2023</li>
<li><b>Test Data release and Tutorial:</b> <strike style="color:gray">June 15, 2023</strike><span style="color:red"> June 22, 2023 (Extended!)</span></li>
<li><b>Registration close:</b> <strike style="color:gray">June 15, 2023</strike><span style="color:red"> June 26, 2023 (Extended!)</span></li>
<li><b>Submission of results:</b> <strike style="color:gray">June 29, 2023</strike><span style="color:red"> July 27, 2023 (Extended!)</span></li>
<li><b>Submission of paper:</b> <strike style="color:gray">July 6, 2023</strike><span style="color:red"> July 27, 2023 (Extended!)</span></li>
<li><b>Review sent to participants:</b> <strike style="color:gray">July 20, 2023</strike><span style="color:red"> August 3, 2023 (Extended!)</span></li>
<li><b>Resubmission of conditionally accepted challenge papers:</b> August 18, 2023</li>
<li><b>Camera-ready Final Submission:</b> <strike style="color:gray">July 27, 2023</strike><span style="color:red"> August 21, 2023 (Extended!)</span></li>
<li><b>Workshop:</b> September 7 - 9, 2023</li>
</ul>
<h2> Challenge Registration </h2>
To participate, please complete the <a href="https://docs.google.com/forms/d/e/1FAIpQLSf7Gt2_fXfDKNt06OrwpkqhlMxXPJep0XDEbSnMtasfAxsbHg/alreadyresponded?edit_requested=true&fbzx=-5424371331795866531">Registration Form HERE.</a></a>
<h2> Result Submission </h2>
Please submit your results via the submission form. <a href="https://forms.gle/pX1FCBMr9Tb5FE9n9">Access the Submission Form HERE.</a></a>
<p></p>
<p></p>
<p></p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/S6DVRy58ywc" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
<!--
<h2> Tutorial Webinar (Japanese/English) </h2>
As we are going for a more challenging dataset this 2023, we organized tutorial webinars on June 22 both in Japanese and English.
In the webinar, we covered:
<ul>
<li>Explanation of Parkinson’s Disease Patients’ Wearing-Off Phenomenon.</li>
<li>Give a brief introduction to data processing and forecasting.</li>
<li>Demonstrate how to make the forecast submission file.</li>
<li>Content Outline: Explanation of challenge, registration, data structure, tutorial program and submission format</li>
<li><a href="https://kyutech-ac-jp.zoom.us/rec/play/xAFq_gxe5QXCCOn_YS7MshLN-PPQ_5DTYaagui-du1Ijxq0C4Xu2jhyVEq-5MhF79jHq7wHBQhh6r7B5.B5Vh1a9EmPIrtQoh?canPlayFromShare=true&from=share_recording_detail&continueMode=true&componentName=rec-play&originRequestUrl=https%3A%2F%2Fkyutech-ac-jp.zoom.us%2Frec%2Fshare%2Fgvc5FYgeeI2TvgErb-7ydGN3gqBx_OyRdqh5PHE1czcxF0S1r7IRGYHE6oaalZq4.5CjenUO18_9Yy-HW"><b>Link to the Tutorial</b></a></li>
</ul>
Feel free to join by completing <a href="https://forms.gle/fzc5VsaCcA4iZB6FA">this Application Form for the Tutorial.</a>
<p></p>
If you are interested, please join us.
<ul>
<li>Date: June 22, 2023, 2 PM JST (Japanese), 4 PM JST (English)</li>
<li>Place: Online (Zoom link will be shared with registered participants)</li>
<li>Language: Japanese / English, Python </li>
<li>Application Form for the Tutorial: https://forms.gle/fzc5VsaCcA4iZB6FA </li>
<li>Content Outline: Explanation of challenge, registration, data structure, tutorial program and submission format</li>
</ul>
<h2> Tutorial Webinar (Japanese/English) </h2>
In our fourth year, we are again hosting another Nurse Care Activity Recognition Challenge. As we are going for a more challenging task this 2022, we have decided to organize two webinars this June: one in Japanese and another in English. Feel free to join by completing <a href="https://forms.gle/mCETC2fSxWty2TMw9">this Survey Form.</a>
<ul>
<li><a href="https://youtu.be/pzuAXzRtkHg"><b>Link to the Japanese Tutorial</b></a></li>
<li><a href="https://youtu.be/9djBag5QZqY"><b>Link to the English Tutorial</b></a></li>
</ul>
<p></p>
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