Improving Mobility Using AI: MobileMe
We take many of our daily privileges for granted.
Food on our tables, roof over our heads, water to drink, family to spend time with, and so on.
But what if your own body failed you?
What if those two legs of yours refused to hold you up? To take you from place A to B? What if they were your barriers opposed to anything external? They refused to let you go to the bathroom, take a shower, go for a walk, all without support. Your own body trapping your own self.
Mobility is a privilege.
A privilege that 1 in 5 seniors (and that’s only in the US & Canada) do not get to enjoy. And you will begin to lose yours too… in time.
Breaking The Problem Down
Mobility is the ability to move.
Immobility and degrading ease of mobility results in increased risk of falling.
Who does this affect?
Older people have the highest risk of death or serious injury arising from a fall and the risk increases with age.
This risk level may be in part due to physical, sensory, and cognitive changes associated with ageing, in combination with environments that are not adapted for an aging population.
- Falls are the second leading cause of accidental or unintentional injury deaths worldwide.
- Each year an estimated 646 000 individuals die from falls globally of which over 80% are in low- and middle-income countries.
- Adults older than 65 years of age suffer the greatest number of fatal falls.
- 37.3 million falls that are severe enough to require medical attention occur each year.
According to the U.S. Centers for Disease Control and Prevention: One in four Americans aged 65+ falls each year. Every 11 seconds, an older adult is treated in the emergency room for a fall. Eevery 19 minutes, an older adult dies from a fall.
Here are some more numbers to prove that falling is a serious problem…
- Falls are the leading cause of fatal injury and the most common cause of nonfatal trauma-related hospital admissions among older adults
- Falls result in more than 2.8 million injuries treated in emergency departments annually, including over 800,000 hospitalizations and more than 27,000 deaths
- In 2015, the total cost of fall injuries was $50 billion. Medicare and Medicaid shouldered 75% of these costs
- The financial toll for older adult falls is expected to increase as the population ages and is expected to reach $67.7 billion by 2020
- Over 800,000 patients a year are hospitalized because of a fall injury, most often because of a head injury or hip fracture
- Each year at least 300,000 older people are hospitalized for hip fractures. More than 95% of hip fractures are caused by falling.
- Falls are the most common cause of traumatic brain injuries (TBI)
Physical Impacts of Falling on Seniors
- Falls can cause hip and thigh injuries: the most common reason for hip fracture hospital admissions (9 in 10 cases).
- Other injuries: head injuries, wrist fractures, and other injuries.
- Hip fractures also impose a heavy long-term burden as older people become less independent, more reliant on family members and carers.
Psychological Impacts of Falling on Seniors
- Older people become fearful of falling again and lose confidence in walking. They may start to do less physical activity. However, over time this reduced movement makes it more likely that you’ll have another fall because of poorer balance, weaker muscles, and stiffer joints.
- Other fall-related psychological concerns (FRPCs), such as falls-efficacy & balance confidence are highly prevalent.
Proof — Here’s Mrs. Dixit
Hear from a senior who’s fractured herself numerous times as a consequence of falling.
Thank you so much Mrs.Dixit for taking the time to tell us your story💓
Isn’t Falling The Outcome?
Yes. Falling is an outcome — not the problem. It’s less about the act of falling but rather about the consequence of the fall.
Let’s work backward to understand what causes people to fall 👇🏽
The resultant health/lifestyle changes caused by aging lead to decreased ease of mobility, such as…
- Decline in physical fitness: Reduced muscle strength, decreased bone mass, loss of balance and coordination, and reduced flexibility.
- Impaired Vision: age-related eye diseases make it difficult to detect fall hazards, such as steps, puddles, and thresholds. While these environmental factors can be limited in elderly areas, they are inevitable and pose definite
- ⬆ Chances of having surgical procedures: Hip replacements and other surgeries can leave an elderly person weak, in pain and discomfort, and less mobile. This can be temporary while a patient heals or a new and lasting problem.
- ⬆ Susceptibility to environmental hazards: The majority of falls in the elderly population occur in or around seniors’ homes. Environmental factors such as poor lighting, clutter, areas of disrepair, loose carpets, slick floors, and lack of safety equipment can jeopardize a senior’s safety in their home.
- ⬆ Reliance on medications: Side-effects, such as drowsiness, dizziness, and low blood pressure, can all contribute to an accident. Sedatives, antidepressants, anti-psychotics, opioids, and some cardiovascular drugs are the most common culprits. The impact that first-generation antihistamines pose on the poses on the central nervous system indicates symptoms such as “anxiety, confusion, sedation, blurred vision, reduced mental alertness, urinary retention, and constipation.” According to the Merck Manual, just over 40 percent of seniors take at least five drugs per week.
- ⬆ Susceptibility to developing chronic diseases: Health conditions such as Parkinson’s disease, Alzheimer’s disease, and arthritis cause weakness in the extremities, poor grip strength, balance disorders, and cognitive impairment.
Peripheral neuropathy, or nerve damage, can cause numbness in the feet, making it very difficult for a senior to sense environmental hazards and get around safely.
Given the numerous factors that increase one’s fall risk, let’s look at how professionals today are handling this problem.
Dealing With Falls — Reactive>Proactive
In the medical scene, the approach towards mitigating falls are reactive. We try to suppress the physical harm caused by a fall after it occurs.
But what if we prevented falls from happening in the first place?
Or rather, what if we could provide personalized treatment plans to help seniors reduce the impact a fall has on their physical health if they were to encounter one?
Testing an elder’s mobility today
The standard methods for gait analysis rely heavily on human observation, which uses subjective qualitative data, like visual cues to detect ease of mobility. This one-size fits-all approach, prone to inaccurate data collection due to human error resulting in ineffective diagnosis decision making.
Existing Approaches To Quantify Fall Risk
- Weakness: relied on German & Dutch population as the majority, hence the homogenous testing would make the solution difficult to implement on a widespread scale.
- Weakness: small sample size of n=61 was based on data acquired from a hospital in Amsterdam only.
Our AI Solution: Improves Existing Proactive Mobility Assessments
Real-time, proactive fall risk analysis by modeling gait data collected using a microprocessor device.
For the initiation stage, patients will wear the MobileMe hip microprocessor device, equipped with an accelerometer and gyroscope for collecting movement data. The data is a real-time graph with XYZ axis values and acceleration over time based on movement tracked.
Gait data (acceleration, walking patterns, and spatial) is run through an LSTM Recurrent Neural Network to identify specific gait concerns, like propulsive gait, steppage gait etc.
The NN is fed pre-labelled training data containing a graph of movement and acceleration over time corresponding with a specific gait problem. This data is collected from the IMU (inertial measurement unit) onboard the microprocessor device.
New graphs will be run through the NN & the prediction of the gait problem(s) by the network will be compared to the true condition, minimizing the loss value.
After having connected the Bluetooth module with the app (in order to share and display data) using a standard Bluetooth protocol, we collect data for every millisecond on the Serial Plotter. The real-time IMU data will be collected as the patient performs the POMA test steps & sent to the backend NN.
Afterwards, the graphed data is run through the trained NN and returns an output of gait problems and the confidence rate of the classification.
To do this, we plot a Receiver Operating Characteristic curve, which compares the rate of false positives and true positives. If we have an area under the curve > 50%, we have a higher confidence interval and should send the data to the doctor. Of course, data will also be sent under the interval — this would show situations when fall risk is low and will provide more quantitative patterns indicating why that might be the case.
The device automatically sends out a movement graph with a gait problem of a specific confidence rate. This will help doctors create a personalized treatment plan to improve the patient’s strength & ease of mobility.
This is a predictive model — since correlation != causation, newer technologies like causal neural networks can definitely locate the cause of identified gait problem. As it becomes more widespread, a shift to modeling increases the confidence interval & we will be able to trace the fall risk to specific factors, making the treatment more personalized.
Alongside that, the training data for the populations will vary, & we need to collect the same per region (alongside other demographic factors). Right now we are starting out small. As we gain more data, we can expand MobileMe to more areas across the world.
In developing and underdeveloped areas where medical infrastructure is improving at a slower rate + accessibility to medical attention is minimal, we are connecting with locals, in areas with the greatest elderly fall (e.g. Southeast Asia).
Our vision is to improve senior mobility allowing them to live a comfortable and longer life.
Co-created this project with Orna Mukhopadhyay, Hung Huynh, Neha Shukla, Sarah Naghmi,, Mir Ali Zain.