CONNECTED CARE
The Evolution of Safety Devices
How AI is shaping the future of PERS
By Chia-Lin Simmons
Personal emergency response systems (PERS), also commonly known as medical alert devices, first emerged in the 1970s as a solution for aging adults and at-risk individuals to call for help during emergencies. These early tools were originally designed as simple units featuring a push-button system linked to a landline telephone. Medical alert devices initially offered quick access to emergency assistance for users, marking a significant turning point in promoting independence within a population that historically struggled to balance autonomy with safety.
Although the primary target consumers for these devices were older adults, they can also benefit people with disabilities and those with chronic health conditions. By assisting these at-risk individuals as well, medical alert devices have provided peace of mind for an even wider community of caregivers and family members.
Those first medical alert devices were, however, limited in functionality: they could not speak to more modern communication networks and relied on users being conscious and able to activate them manually. The original devices only offered direct-to-911 connections, which were often too extreme an occurrence for those who didn’t require emergency services or who feared costly ambulance bills. Another challenge was the absence of similar protection outside the home, where people were still vulnerable while running errands or engaging in daily activities. And of course, those versions were designed with the assumption that users would always be alert and able to physically push the button for help.
New Advancements
As the number of aging individuals living alone and more independently continues to rise, so too does the demand for solutions to support a variety of lifestyles and health concerns. This has created a consumer expectation for technology that not only enhances safety but also innovates and adapts to our current, mobile-dominant way of life. Advancements in both hardware and connectivity have led to significant improvements in these mobile PERS, enhancing both the devices and services available to consumers. Cellular networks and the Internet of Things (IoT) have resulted in more reliable and efficient systems that provide protection at home or away.
The introduction of monitoring services further advanced the field, enabling these devices to connect directly to trained operators who could determine the best course of action, whether that was notifying 911 in case of an emergency, or just contacting a friend, family member or caregiver for assistance. Wearable medical alert devices also increased the versatility and reliability of PERS, ensuring help is always within reach. Another significant feature is geographic location boundaries, which inform operators or caregivers via GPS if a device and its user have left a set location. This is especially important for seniors with Alzheimer’s disease or dementia.
The Age of AI
Recently, the integration of artificial intelligence (AI) in PERS has significantly enhanced the traditional capabilities of these devices with, for example, fall detection as a standard new feature. AI-enhanced technology also improved other limitations of conventional medical alert devices by enhancing sensor accuracy, improving response times, reducing false alarms, and facilitating preventative care. The current landscape of fall detection features on PERS devices continues to rely on the use of accelerometers as the primary sensor for calibration and fall detection. It’s a step in the right direction, but the future of PERS should not be limited to accelerometer-based fall detection algorithms, which are currently prevalent in the market for personal emergency response systems (PERS).
The future of PERS and AI is the use of additional sensors on devices or in the home that may include a gyroscope, altimeter/barometers, data that comes from sensors that capture sounds, vibrations, etc. to better identify if there is a real fall versus a “false positive” (someone who sat down too quickly for example). The additional sensor usage requires more sophisticated AI and machine learning (ML) algorithm development. It brings with it greater assurance to the caretakers that real falls are captured (and that they can validate remotely via video, for example) and that the wearer of the PERS is not constantly barraged with a device that is not accurate and continually interrupts their day. Manufacturers and PERS service providers use AI for various applications in PERS tech, including fall detection, geofencing, and personalized emergency alerts. Systems like predictive analytics are also being integrated into devices and services to determine user behavior and detect potential health risks before they become more serious and potentially lead to a fall. By monitoring patterns of activity and mobility, medicine adherence, and other factors, devices and AI-enhanced services can provide a potential probability of falls or medical distress and automatically alert caregivers and emergency services in advance. For example, by looking at changes in patterns of walking and activities, medicine adherence, and other factors, a PERS product and service can compare the pattern of that user to a cohort of users with a similar age, gender, activity background, health care concerns,
A variety of sensors are now built in and able to detect a fall and contact emergency services immediately even if the user cannot speak. AI also improved other limitations of traditional medical alert devices by enhancing sensor accuracy, improving response times, reducing false alarms and facilitating preventative care.
The evolution of PERS and medical alert devices has transformed from basic push-button operations to advanced solutions designed to meet the needs of aging individuals and at-risk populations. Advances in AI, connectivity, wearable technology and mobile integration have expanded their functionality, enabling reliable protection both at home and on the go. As technology continues to evolve, the future of medical alert systems holds endless possibilities, promising even more intuitive, proactive and personalized solutions to redefine safety and independence for generations to come.
Chia-Lin Simmons is the CEO of LogicMark, a provider of personal emergency response systems (PERS), health communications devices, and advanced technology for the growing personal care and safety economy. She is evolving the PERS sector with AI and predictive analytics while building technology that gives families, caregivers, home care professionals, and aging adults better peace of mind when it comes to aging.
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