## 2 Materials and Methods
### Data Collection
#### 2.1.5 Data Collection Method  
The two PD patients received the data collection tools needed for our experiment. The data collection lasted for 30 days, with an additional one-day setup for the PD patients.  
Each participant created their own Garmin Connect account to start the Garmin vivos-mart4 fitness tracker's data collection process. Next, the participants signed into our web application server using their Garmin Connect account. At this point, they had control  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Data Type** & **Description** \\ \hline WoQ-9 & Symptoms onset and drug intake time \\ \hline Basic Information & Age and gender \\ \hline Hoehn and Yahr Scale (H&Y) & Participant’s PD stage \\ Japan Ministry of & Health, Labor, and Welfare’s \\ classification of & \\ living dysfunction (JCLD) & \\ \hline PDQ-8 & Participant’s QoL measurement specific to PD \\  & 0–100\%, with 100\% showing worst QoL \\ \hline \hline \end{tabular}
\end{table}
Table 2: FonLog Data.  
\begin{table}
\begin{tabular}{l l l} \hline \hline  & **Participant 1** & **Participant 2** \\ \hline Age & 43 & 38 \\ \hline Gender & Female & Female \\ \hline H\&Y & 2: Bilateral or midline involvement \\  & without impairment of balance & 3: Bilateral disease: \\  & & mild to moderate disability \\  & & with impaired postural reflexes; \\  & & physically independent \\ \hline JCLD & 1: Little assistance is needed & 2: Partial assistance is required \\  & in daily life and outpatient visits & for daily life and outpatient visits \\ \hline PDQ-8 & 37.5\% & 65.63\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: Participants’ demographics.  
over what information they would share with our web application server while reading the privacy policy. After all the steps, the Garmin Health API automatically transmitted available data to our AWS Web Application Server.  
Throughout the 30-day data collection period, the participants were encouraged to always wear the Garmin vivosmart4, even during sleep. However, there were still cases when they forgot to wear it, such as after taking a shower or when doing household chores. In the worst case, they could not wear it due to some PD symptoms. These conditions were accepted to capture data that were as close as possible to the real-world scenario.  
Using FonLog, the participants answered questions regarding (1) basic information, (2) the Hoehn and Yahr Scale, and (3) the PDQ-8 once. Then, they reported any of the following nine symptoms: tremors, slowing down of movement, change in mood or depression, rigidity of muscles, sharp pain or prolonged dull pain, impairment of complex movements of the hand and fingers, difficulty integrating thoughts or slowing down of thought, anxiety or panic attacks, and muscle spasms [1]. However, this study simplified the wearing-off label to either wearing-off (1) or not (0). Any recorded symptoms were considered to represent a wearing-off label.  
The participants recorded the onset of any symptoms as accurately as possible. From the home screen presented in Figure 1(a), the participants could click on the activity on the left side; i.e., activity enclosed in the red box. The home screen showed every recording on the right side. However, if a recording was difficult for the participants due to their symptoms, they could retroactively record data with their best estimation of the time. They could correct and review the onset of the symptoms, as shown in the top part of Figure 1(b).