The Libris® 2 fall-detection pendants are not only giving seniors and lone workers an added feeling of safety and independence, they’re also backed by powerful technology, making it the most advanced MPERS in the industry. Jenny Sheep, a Senior Software Engineer for Numera® medical alert systems with fall protection, details the integrated technology features behind the Libris 2 fall monitoring system pendant. Jenny focuses on the importance of designing for accuracy and how she and her team have achieved just that in the Libris 2 pendant. Her data points make compelling sales messages helping dealers to easily highlight the advantages of state-of-the-art fall detection. This medical device worn around the neck has a built-in sensor and help button, serving as the perfect tool for anyone living alone.
- What advancements make the Libris 2 devices the best fall detection MPERS device on the market? We have developed fall detection technology based on actual human falls, which is a significant strength that lets us constantly improve the Libris 2 pendant. The Libris 2 wearable device also features pinpoint GPS location technology as well as three different integrated sensors compared other devices that have more limited fall detection capabilities. Not only do these sensors in the fall detection device help determine a fall’s impact to the wearer, but they capture an immense amount of data. We then use this information to perform cloud-based analysis and apply it to the latest artificial intelligence and machine learning techniques that allow us to better identify a wide range of fall categories. There are an infinite number of different fall scenarios that a person can experience so the data we gather is vital to advancing the accuracy of our fall algorithms.
- Why is accurate fall detection monitoring so important? The level of fall detection accuracy means the Libris 2 pendant fall detector can provide as little false positives as possible, but more critical is that accuracy eliminates false negatives so that 100 percent of falls are identified. The Libris 2 fall-detection pendant has a 90 percent accuracy rate and recognizes more than 3,000 different fall algorithms. The bottom line is that precise information on a fall enables monitoring services and emergency personnel to respond faster and with the right equipment to handle the situation giving the wearer an increased sense of security.
- What do Numera product engineers learn from real human falls vs. computer simulations? Real human falls are very different from computer simulations as there are multiple scenarios and circumstances surrounding an individual fall that cannot be accounted for in a simulation. We learn a great deal from these varying scenarios and use this information to create a medical alert system that is efficient and reliable. How did the person fall and for what reason? Did physical surroundings, temperature, underlying health conditions or another situation contribute to the fall? And, we have found that different people can fall differently under the same scenario. We are continually using volunteers to record complete scenarios to refine our wearable device – from its initiation to the final fall and model it. This direct type of field and lab analysis allows us to constantly enhance the algorithms in the Libris 2 devices to precisely detect the type and severity of a fall. Our innovative fall detection system uses next-level technology to ensure the safety of your loved one during an emergency situation.
Want to see more on who benefits from Libris 2 medical alert system? Check out our latest post from Product Line Manager Ko Matsuo to learn more about these fall detection device systems.