Wearing-off phenomenon 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.

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).

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.

Challenge Goal and Task

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 2022 Garmin Health Awards winners.

Published papers about the dataset

  • 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. >
  • 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. doi:10.3390/app11167354
  • 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. doi:10.1016/j.procs.2021.12.0644


This Challenge will be held as part of the ABC Conference 2023
  • Challenge opens: May 4, 2023
  • Test Data release and Tutorial: June 15, 2023 June 22, 2023 (Extended!)
  • Registration close: June 15, 2023 June 26, 2023 (Extended!)
  • Submission of results: June 29, 2023 July 27, 2023 (Extended!)
  • Submission of paper: July 6, 2023 July 27, 2023 (Extended!)
  • Review sent to participants: July 20, 2023 August 3, 2023 (Extended!)
  • Resubmission of conditionally accepted challenge papers: August 18, 2023
  • Camera-ready Final Submission: July 27, 2023 August 21, 2023 (Extended!)
  • Workshop: September 7 - 9, 2023

Challenge Registration

To participate, please complete the Registration Form HERE.

Result Submission

Please submit your results via the submission form. Access the Submission Form HERE.