Interactive charts let you view your health data over time and dive in for a deeper look. For example, you can review your exercise activity for a day, week, or month or see your heart rate during a specific workout.
New advanced trend analysis lets you see how health metrics like blood glucose, heart rate, and respiratory rate change over time. And you can get notifications when new trends are detected. With an Apple Watch, you can track metrics from your sleep like blood oxygen levels, heart rate, time asleep, and now sleeping respiratory rate.
The Health app can incorporate data from tens of thousands of third-party apps that are designed to promote healthier habits — everything from nutrition to meditation to fitness.
The Health app can give you app recommendations for health categories that interest you. Everything is built to keep your data secure and protect your privacy. The sensors in your Apple Watch and iPhone capture data that reveals mobility metrics like walking asymmetry to give you a better overall view of your health. In the Health app, you can view your low-range cardio fitness level, walking speed, how fast you climb and descend stairs, and an estimate of your six-minute walk test, giving you easy access to these important health metrics.
Walking Steadiness is a metric that assesses your balance, strength, and gait. Traditional methods of assessing balance, stability, and risk of falling include a questionnaire and a visit to a specialty clinic. Now you can get an assessment of your walking steadiness as OK, low, or very low just by carrying your iPhone.
And you can get recommendations for exercises that help improve your walking steadiness. Cycle Tracking lets you log your period, record symptoms like cramps, and track cycle factors like lactation.
It can also help predict when your next period or fertility window will begin. The Health app creates simple graphical charts so you can quickly review cycle length and variation. It also now uses heart rate data from Apple Watch to improve its predictions. Your body is a complex system. The Health app helps make understanding it a bit simpler. With it you can organize and access a vast array of health records including allergies, labs, and immunizations — and sort through it all with ease.
View a timeline of your health history that includes lab results, immunizations, and medications, even if the data is from different health institutions. To help you understand and manage your lab results, you can receive highlights, get context for results, and pin labs that matter most to you.
Highlights show how your lab results have changed and if they are within expected ranges. SensorLog will record the actual numbers from the various sensors, like accelerometer, gps, pedometer, altitude, gyroscope, motion, audio and more.
If you are new to Python and not sure how to get started, I suggest downloading and installed the Anaconda distribution.
This is the most friendly setup for getting started with using Python for data science, and it comes prepackaged with the most useful extensions. If you are a programmer in another language, then you should be able to find some open source code to get started in that language on Github. So, our first task is to convert it into something more useable, like CSV.
Alternatively we could process it directly into a data frame or alternative storage model, which we will look at in a later section. First, download or clone the code from github. Third, start Anaconda and launch Jupyter Notebooks with Python 3.
Alternatively, from the command line, you can launch it with the following command:. This process may take several minutes to run depending on the size of your Apple Health directory. After the completing the process, you should have several new files. Each file should include a CSV export of that health metric.
This data should be both well-structured and quite verbose, meaning it contains everything originally stored in Apple. You can easily use any of these files to start your data analysis in your favorite data analysis tool like Tableau or even explore it in a Spreadsheet application. Here is a sample of my weight data:. Two important things to note about this data. We will correct these issues and a few other aspects in the next sections. Another method for extracting and parsing your Apple Health data is to convert it to Feather.
Feather is a relatively recent data storage method, and it is method I recommend if you are a more serious data scientist.
Feather allows data portability with both R and Python and it has some performance optimizations too. You can find good starter code here: github. Additionally none of the data has been aggregated into anything useful like hourly or daily stats. This file will walk us through a step by step method of fixing the timezones, assigning more time-based references, and enable us to aggregate it into more useful stats. In order to fix these timezone errors, we will use the python timezone package and leverage a couple of simple functions to convert from UTC to our own timezone.
We then set a few relevant date references:. These will allow us to aggregate and calculate key statistics about steps. First, we group steps by the date and sum their value. There is one problem though. This includes both step data from both the watch and phone. Tap your profile picture in the upper-right corner.
Tap Health Details, then tap Edit. Add your information, like height, weight, and age. Tap Done. You can also set up your Medical ID or register to be an organ donor from your profile. Choose your favorite categories to track Open the Health app and tap the Summary tab. Tap Edit in the upper-right corner. To add or remove a category from your favorites, tap it.
Categories with a blue star appear in your favorites. When you're finished, tap Done. Add information about your health Open the Health app and tap the Browse tab. Tap a category, like Activity. Tap a subcategory, like Steps. These details are already backed up and stored safely in iCloud.
However, there may be situations when you need to view this data on a big screen or send it to your doctor. Let us look at steps to do so. Step 3. Step 4. Now you may Save this data to Files app or email it to yourself or your doctor.
It will be exported as ZIP file. Note: If you do not see Save to Files or any other App of your choice, tap on Edit Actions from bottom left and using the green plus icon add the app to this share pane.
Though there are some third party apps which allow you to export your health data, we have found QS Access a bit better than others. Better still, it converts all the information into a readable CSV file-unlike Health. Step 2. Now, select the columns that you want to export and tap on Create Table at the bottom right corner.
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