Ship #1 Pending review

@allisonly_huang on Kinesia · about 1 hour ago

Kinesia is a gamified Parkinson’s disease tracker built for both patients and clinicians that makes symptom management and daily life easier for those living with Parkinson’s.

Studies show that popular tracking methods for Parkinson’s like home diaries are highly susceptible to a patient’s subjectivity, creating inaccuracies in data that disrupt medication efficacy, skew clinical decisions, and negatively impact patients’ well being. Even with modern tracking technologies, broader surveys show only 34% of patients actively tracked their symptoms over the year.

Instead of asking patients to describe their own symptoms, Kinesia allows their movements to speak for them. Patients play short gardening themed games that measure akinesia-like, bradykinesia-like, and dyskinesia-like symptoms. Patients tend to their garden through taking doses on time and completing mobile games, and are encouraged through daily streaks.

Each game is based on established clinical trials, adapted to work reliably at home. The plant watering game uses the finger tapping test, a reliable measure of bradykinesia. We also added a decrement that measures when taps slow and shrink over time. Firefly catching adapts a reaction time test, and we split each response into movement initiation and time to reach the target, telling a clinician whether a patient struggles to initiate a movement or execute it fully. In constellation tracing, the patient swipes along a constellation instead of typing or spiral tracing, which are too noisy or difficult on a small screen. Together, these choices allow the data that reaches the clinician to reflect the patient’s movement.

While some clinicians note that apps generate data without clear relevance or meaning, Kinesia visualizes data based on frequent use in clinical settings. Each task’s graphs show when the test was taken, test performance in relation to dosage, a primary statistic that reflects performance, and detailed statistics to elucidate patients’ movement symptoms. For example, tapping graphs not only display overall speed on the primary graph, but also rhythm, decrement, accuracy, and drift on the detailed graph, which can explain the cause of a symptom.

The cost of unreliable tracking in Parkinson’s is often hidden—a decision that wasn’t made, or information that was lost to memory. But with an incurable disease that demands lifetime management, each choice shapes a patient’s daily life. It decides whether or not they can play sports with a loved one, speak uninterrupted, and move with freedom. With Kinesia, patients and their caretakers can have better and easier care.

Want to see the app demo? Here’s the youtube link: https://www.youtube.com/watch?v=NmDAg-RShnE&t=9s

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Try project → See source code →

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@allisonly_huang on Kinesia · 4 months ago

1h 8m 3s logged

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.

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@allisonly_huang on Kinesia · 4 months ago

2h 47m 51s logged

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.

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@allisonly_huang on Kinesia · 4 months ago

2h 52m logged

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 🏃‍♂️

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@allisonly_huang on Kinesia · 4 months ago

1h 11m 57s logged

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.