We have long been interested in the idea of an early warning tool that alerts you if your fall risk starts going up — so you get motivated to do something about that increasing risk (see this article).
Apple has some intriguing tools now available in the iPhone that are very relevant to this idea of fall risk monitoring.
In this post we are going to do two things:
Introduce readers to these tools; and
Encourage those of you who are tech-savvy Apple users, interested in preventing falls in older adults, to try out the tools — and use the comments section to tell other readers what you learn.
For any fall risk experts reading this, please use the comments section to add any ideas or knowledge you have, as our goal is to get a sharing of ideas and knowledge going.
Disclaimer: We have no financial relationship with Apple, and get no financial benefit of any sort from writing this post, other than from those of you who subscribe to Tech-enhanced Life’s Newsletter on Substack.
Introduction to Apple Features Relevant to Fall Risk
Over the last few years Apple has added several intriguing features to its iPhones that are relevant to fall risk. Below is an introduction to them.
Buried in the Health App on your iPhone are a number of measurements that relate to health and potentially to fall risk. They work best if you carry your phone with you when you walk around, and we suspect they work best if you have the phone in your pocket rather than in a purse.
In what follows, we assume that you take your phone with you whenever you walk around or go out for a walk, and also that you keep it in a pocket (near your center of mass) when you are walking.
If you also have an Apple Watch, that adds some additional relevant measurements to the collection you can see in the Health App on your phone, assuming you have set things up correctly.
Mobility Metrics Related to Falling
For iPhones more modern than iPhone 8 and iOS 14, Apple has included a variety of mobility metrics into the health app. These are very relevant to our desire for monitoring fall risk, as well as other aspects of health.
The key metrics are:
Walking Speed
Step length
Double Support Time
Walking Asymmetry.
Then, these metrics are combined into a composite metric called Walking Steadiness. This metric (Walking Steadiness) is very much along the lines of the early warning risk score we wrote about in the past as being something extremely desirable!
Here is an overview of these features (taken from an Apple paper in ref 1).
“Walking is a key indicator of the status of an individual’s injury, disability and short- and long-term health. Walking mobility can represent the ability to age with independence, and it is affected by a variety of health conditions, including muscular degeneration, neurological disease and cardiopulmonary fitness.
A simple way that health professionals measure an individual’s mobility is by observing them walking. Walking requires a suite of complex components that are co-ordinated across multiple physiological systems, and a single failure of any element may indicate progression of a disease or an increased risk of injury.
Measurement of walking performance is often used to assess an individual’s health status, track recovery from injury or surgery and monitor changes that occur with ageing. Some commonly used walking performance measurements are walking speed, step length, double support time and walking asymmetry.
Walking speed, and how it changes over time, is closely related to clinically meaningful health outcomes. Measured walking speed is frequently used to track recovery from acute health events, such as a joint replacement or stroke, and to monitor health changes over time, such as the progression of Parkinson’s disease and ageing.
Step length is a marker of compromised mobility for certain types of neurologic and musculoskeletal conditions, and is predictive of falls and fear of falling. Step length decreases with age, with older adults showing reduced step length compared with younger people. Shortening step length is an important consideration as we age and early exercise interventions may provide a way to maintain independence.
Double support time is the proportion of time that both feet are touching the ground during walking. It increases when a person has an injury or dysfunction, both in terms of absolute time and as a percentage of each gait cycle. An increase in double support time has been related to a rise in an individual’s fear of falling, while lower double support times are correlated with improved walking stability and a lower risk of falling.
Walking asymmetry emerges when a unilateral pathology or injury occurs and an individual relies on the contralateral limb when walking. An increase in walking asymmetry occurs after an injury or due to neurodegeneration from ageing or disease. A decline in bilateral co-ordination between the two legs has been shown to be tied to an increased risk of falling and poor surgical outcomes, and is predictive of later joint injury.”
NOTE: The paper in reference 1 includes a lot of references to specific studies that the authors believe support the claims above. We did not go back and read all the scientific literature, so if you are an expert and don’t agree with the above, feel free to say so in the comments.
In the image below, you can see how these metrics appear in the Health App: in this case for a fairly healthy 67 yr old male.
Caption: Mobility Metrics in Apple Health App.
Walking Steadiness: Derived Summary Metric
To simplify the usage of these measurements, Apple has also created a composite metric called “Walking Steadiness”.
This metric somehow combines all the variables above into a single variable and gives it a score. It also tells you whether your score is “OK”, “Low”, or “Very Low”.
Caption: 6 month trend of walking steadiness score.
Apple explains “Walking Steadiness” as follows:
“Walking Steadiness uses custom algorithms to assess your balance, stability, and coordination through the built-in motion sensors on your iPhone. As you walk with your iPhone, it tracks important mobility metrics, such as walking speed, step length, double support time, and walking asymmetry. These are used to determine your walking steadiness and classification.
Your walking steadiness is classified as OK, Low, or Very Low. You can also choose to receive a notification if your steadiness is Low or Very Low.”
Are These Correlated With Falling?
Here is what Apple says about the relationship between risk of falling and the metrics above.
“Your Steadiness is related to your fall risk. As steadiness goes down, your risk of falling goes up. Walking Steadiness is not an indication of how likely you are to fall in any given moment, but an overall sense of fall risk in the next twelve months.”
How to Use These Tools?
We think the obvious potential is to track Walking Steadiness over time, and if you notice any sort of degradation in that score to:
discuss with your healthcare provider and show them the data; and
consider one of the balance training classes discussed here.
Share How You Use These Tools
You will notice this article includes mainly snapshots of data from a rather healthy, young-ish Longevity Explorer.
We would love to see some similar images from others with less high scores. Feel free to share your opinions in the comments below. If you want to send a screenshot of your data, feel free to send it via email (just reply to this email you are reading).
Please Comment
We really want to get some dialogs going about these tools. Please add any comments, questions etc below.
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References
Measuring Walking Quality Through iPhone Mobility Metrics (PDF: by Apple)
I own an iPhone and was amazed when my phone started giving me "advice". Since I'm having health issues that relate to walking I quickly realized how helpful my walking steadiness notifications are - and as I work to get my walking back to normal, check in frequently to see if my phone "agrees" with my assessment of my progress. My physical therapist thinks it's great also. Like having a friend along
Very useful, I am printing out for future reference when monitoring myself.