2026: The Future of Machine Learning and the Elderly

The field of machine learning has begun to branch out into territories previously unexpected as the internet of things has continued to penetrate much of what we come into contact with in our day to day lives. The elderly have long depended on systems which combine technology and manual monitoring to ensure that they stay healthy. The applications of machine learning technologies and algorithms have the potential to greatly improve the lives of the elderly and the ways in which they are cared for. Herein, I will attempt to investigate five different examples of how machine learning might help the elderly to continue thriving 10 years from now.

Machine Learning has the potential to greatly change the lives of the elderly in a beneficial way, one of which, is in in home health care. One company which is based in Honk Kong, called HKC International, has developed a system which monitors an elderly person’s movements within their home, noting their patterns to eventually detect if there is an emergency or if the user becomes inactive for a long period of time (1). This current system uses infrared beams to detect a user’s movements and notice if these are outside of typical patterns. I think in the future, this system will evolve utilizing a wide array of sensors, both movement and sound detectors, whose data will be fed to machine learning algorithms which will be able to calculate a resident’s exact condition, eventually allowing for a prediction of problems before they even arise.

This all-encompassing system will need to be able to detect more than just external problems. Another somewhat similar application of machine learning to the aid of the elderly is in a system that was proposed by Pogorelc et al. (2) which utilizes sensors which are worn on one’s body. If abnormal physical conditions arise, a physician or emergency staff will be contacted to come to the aid of the person. This system can utilize classifiers to detect different possible diseases in combination with a user’s medical history. I expect bodily-worn sensors similar to these become a common trend in the care for the elderly, as instead of just relying on weekly physician visits, with this system and machine learning, a patient’s medical condition can be monitored and reacted to constantly.

A common cause of injury for the elderly is falling. Albert et al. (3) has shown a method for utilizing machine learning to successfully detect and classify the falls of the elderly, using only a patient’s mobile phone and an application. This application heavily relies on the phones internal accelerometer to detect how hard of a fall occurred. Data from the accelerometer is fed to machine learning algorithms which predict what kind of fall occurred- whether merely a phone drop or maybe a hard fall backwards. This system can then send an alert to contact necessary aid for the user. I think this system, when mixed with the aforementioned ones, specifically if an accelerometer were to be mounted on the body sensors that will probably become standard in the near future, will end up saving a lot of lives detecting accidents as they happen, not just after.

I see another possible application for machine learning in the lives of the elderly being in breathing respirators. I predict that in the near future breathing respirators may come to incorporate machine learning algorithms so that the respirator can operate at an optimal setting for the patient’s conditions. Smart respirators, such as this, would be able to follow patterns in a patient’s day and physical activity so that the patient can utilize the respirator in the best way possible.

One last use of machine learning which may benefit the lives of the elderly would be in smart lenses. Technology which replaces classic bifocals has already been introduced (4), but I predict that in the next 10 years, a product which combines this with technologies and the computing power found in smart glasses, such as Google Glass, will emerge utilizing machine learning to best focus a pair of lenses on a target. Smart, auto focusing glasses such as these would utilize machine learning to learn the location of one’s eye in respect to what one is looking at, allowing an elderly person to be able to focus on anything without having to move their head in ways typically associated with the bifocal lenses that are used currently. I think this technology, specifically, will continue to grow as these glasses systems begin to utilize heads up displays which will mix technology with the real world.