5TH ABC CHALLENGE: Forecasting Parkinson's Disease Patients' Wearing-Off Phenomenon Datasets

Abstract

Parkinson's disease (PD) is a neurodegenerative disorder caused by the loss of dopamine-producing brain cells. It primarily affects the patient's motor abilities but also impacts 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).

PD patients who experience the wearing-off phenomenon have their symptoms reappear before their next Levodopa (L-dopa) treatment intake. L-dopa treatment is a one of the treatments for PD patients by producing dopamine in the brain, which alleviates the symptoms. Over time, the medicine's effective time shortens, causing discomfort among PD patients. Thus, patients and clinicians need to monitor and record the patient's symptoms for adequate treatment, since there is no cure for Parkinson's disease.

Patients and clinicians can continuously monitor patients' health with the improvement of wearable devices such as smartphones, fitness trackers, and smartwatches. We use these technologies to monitor patients' health, record wearing-off periods, and document the impact of L-dopa intake on their symptoms in order to forecast the wearing-off periods in PD patients.

Instructions:

There are three datasets for this challenge.

Garmin dataset contains PD patients' heart rate, number of steps, stress level, and sleep pattern.
Wearing-off periods dataset was based on the Wearing-Off Questionnaire (WoQ-9). PD patients self-report the absence or presence of wearing-off symptoms.
Drug intake dataset was also based on the WoQ-9. PD patients self-report the time of drug intake, and the effect of the drug to their symptoms.