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Tech for older adults – how far have we come (Part 2)

Back in the day – 2009.  Seems like, uh, 17 years ago.  Long before the arrival of AI.  Long before smartphone ownership by seniors took offOne year before the introduction of FaceTime. Back in the day of a new wearable chest strap or belt clip from Halo monitoring that could detect a fall. Back in the introduction day of Healthsense eNeighbor for environment monitoring.  The question that blog post raised was whether it was more important to monitor the person (with a wearable) or the place (in the environment).

Wearables – a long way from I’ve Fallen and Can’t Get Up?  Back in 2009, a lawsuit blocked medical alert companies from all using the same catch phrase, leaving it to LifeAlert’s website.  But even they broadened their messaging – and are not rated (or even recommended) as the top in the Medical Alert category by Forbes Health. And in fact, the smart watch is now an option in that category.

Remote monitoring – a good idea that took a while to take hold.  Remote monitoring of the place was complex and it was not clear that either of the prospective customers (a family monitoring a senior relative or an institution monitoring residents) were ready to buy. And so in 2016, GreatCall acquired Healthsense – and then in 2018, Best Buy acquired GreatCall – and augmented its very large current line of products for the elderly. Today, senior living organizations have an ever-frailer as they cope with an older population moving in – half of assisted living residents are age 85 or older.

Down the hall and around the corner – falls need to be prevented as well as detected.  One might wonder what took them so long, given the horrendous publicity about failures. As announced yesterday, senior living operators need smarter fall detection technology to reduce ER visits and ‘blind spots’ as they call them. Aside from the infamous examples of undetected falls in senior living that resulted in ‘long lie’ times and even death. Today’s combinations of wearables and room-based sensors have the potential to prevent serious outcomes from falls – especially if gait and behavior pattern changes are noted before the serious fall takes place.

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