Finished data collection in CoreData + started on UI

Setting up CoreData was 70% researching how it works and 30% actual coding, only to produce a very simple table that I feel could have been accomplished in two hours. But we move on.

Set up health data fetching from apple watch to be normalized to midnight in order to allow the symptom tests taken throughout the day to be all linked to the same date.

Some key UI design choices:

• swiping to access different sections of the app instead of small menus
• calming/warm colors
• large text

I have not done pixel art before and creating an entire plants and farming asset would take too long so I think I’ll go with modifying existing pixel art assets.

Apple CoreData Organization for Movement Tests

Finished organizing and setting up the entities and attributes using apple’s CoreData for the app.

Each entity stores data that needs to be analyzed by the clinician for each test/log type, including AkinesiaResult, BradykinesiaResult, DexterityResult, MedicationLog, and so on.

Each test will have specific parameters calculated by the touchscreen inputs based on what’s important to be measured. For example, the dexterity test requires completing a swipe sequence on the screen and measuring the distance between the user’s input and the predefined path. Attributes of the DexterityResult entity would be rmsError (root mean square error), avgSwipeSpeed, swipeDist, cvSwipeSpeed (correlation of variation of the swipe speed) etc.

Probably spent way too much time researching exactly which parameters should be added but you can never be too meticulous.

Core functions of the app complete: bradykinesia, dexterity, tremors, and more

Looked into apple’s HealthKit and movement disorder API for tracking tremors so that’s what I’ll be using. As long as everything stays local, the law will not be after me.

Each of the mobile symptom tests go like this:

• Bradykinesia: finger tapping test that measures the time between each tap, how much the taps drift across the screen, and how those variables change with time.
• Akinesia: the time it takes for a motion to start
• Dexterity: swiping test for measuring amplitude, speed, etc.

Next will be coding the actual UI 🏃‍♂️

Parkinson’s tracker apps aren’t built for Parkinson’s patients.

Parkinson’s (PD) is a movement disorder, meaning patients have:

• tremors in their hands
• rigid and slow movements

in addition to dementia and cognitive impairment.

So it’s important that patients track their sleep, medication adherence, symptoms, etc. so clinicians know how to adjust their treatment to fully support rehabilitation.

but current apps: sterile and condensed UI with small buttons, complex menus and nav, low incentive…are not ideal. That’s why up to 75% of patients don’t use their tracking app more than 10 times after first downloading.

my app solution:

a gamified PD tracker that prioritizes:

• accessible UI/UX
• calming + aesthetic graphics
• incentive

so far we’ve got:

• swiping instead of menus
• cat garden/farm concept
• slightly punitive streak system

currently working on getting in contact with a clinician for opinions + getting started on xcode.