Intelligent Socks enabled with IoT and AI for early fall detection and prevention.
Our Vision
Our project aims to improve the quality of life for elderly people by creating a solution for one of the most detrimental issues they face: falls.
Falls can rapidly shorten an elderly person’s life, so by detecting the risk early on, our solution will help improve and extend the lives of elderly people.
Our goal was to create a more cost-effective solution, as customers will pay significantly less for the product than they might have to pay for a hospital visit after a fall. The product uses an IoT-enabled sock to predict the quality of a person’s walk and determine their risk level of falling.
1 in 4 Americans over 65 fall each year
800,000 hospitalizations annually from falls
$18,658 Average cost per inpatient visit
9.6% Increased mortality rate
Product
Our product includes a sock that uses a gyrometer and accelerometer to collect data on a person’s foot movement and rotation. The device is easy to use with a variety of advanced features.
Next, the collected data is used to predict the user’s propensity to fall. This is done by utilizing an AI algorithm that compares a user’s data to baseline data in order to determine whether or not the user is at risk of falling.
The final component of the product is a mobile app that offers the user a variety of personalized solutions (using a cane, walker, etc.) based on their results and risk level. Users or their caretakers will be able to easily access the data report and suggestions on their mobile device.
Features
Sleek and Compact Design
High-Accuracy Predictions
Companion Mobile App
Personalized Suggestions
How SafeStride Compares
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SafeStride Socks
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Hospital Alert Socks
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Gait Socks
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Wearable Sensors
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Early Detection Before an Incident
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Companion Software
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Recommends Precautions
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Can Be Used At Home
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Cost Effective & Accessible
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Primary Focus on Elderly Health
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Progress
Next, based on the results from our initial tests, we worked on the next version of our prototype. This version included improvements such as an on/off switch to make the sock more convenient and easy to use daily.
At Beehive Homes of Frisco, an assisted living center, we requested that a few residents try wearing the sock, if they were willing and able to wear it for long periods of time. This allowed us to see how user-friendly the prototype currently was and determine what changes could be made to improve the prototype in the future.
Based on our research, we created an initial prototype that could serve as a way to detect falls early on. The initial prototype of the sock included the gyroscope/accelerometer to collect data, and based on tests and experiments, we made changes in the future versions.
After realizing how quickly an unexpected fall could rapidly shorten or worsen an elderly person’s life, we set out to find a solution that would aid in early fall detection. To begin, we researched the current market and available solutions to the issue before attempting to plan our product.