Healthcare treats falls like lightning strikes. Sudden, unpredictable, and unavoidable.
The industry built an entire infrastructure around reaction, pendants, buttons, and alerts that fire after someone is already on the floor. Steve Waddell has spent years studying what comes before the fall, and he’s learned that falls don’t come out of nowhere.
They announce themselves weeks, sometimes months in advance, through small erosions in daily life that no one is watching.
The glass of water that stays full. The shower that gets skipped. These aren’t random. They’re signals. The body whispers before it screams, and for decades, healthcare hasn’t been listening.
Waddell calls this ADL drift, activities of daily living that slowly fade in function, hiding in plain sight. It’s measurable. It’s predictive. And with 10,000 Americans turning 65 every day, recognizing it is no longer optional.
Start With Behavior, Not Technology
For years, the industry built sensors and asked what they could detect.
The better question is what the body is already revealing.
“When you map the micro-rhythms of daily routines, how someone moves, when they move, what they abandon, you see the truth long before a device would ever trigger,” Waddell explains. “Technology should illuminate human behavior, not the other way around.”
Most health monitoring starts with the technology and works backwards to find applications. This approach produces solutions searching for problems. Waddell’s work in AgeTech and ambient health intelligence inverts that model by starting with the behavioral patterns that precede decline.
A person who stops showering regularly isn’t making a choice. They’re signaling that standing balance has deteriorated to the point where the shower feels unsafe. A person who leaves water glasses untouched throughout the day isn’t hydrated. They’re avoiding bathroom trips because mobility has declined.
These behavioral changes are diagnostic and reveal functional decline weeks or months before traditional medical assessments would catch it. But only if someone is watching, and most of the time, no one is.
Make Sensing Invisible
Older adults shouldn’t have to wear something, charge something, or perform for a camera to stay safe. Independence doesn’t come with homework.
“Ambient sensing, especially radar, allows people to live naturally while the environment quietly captures what matters,” Waddell notes. “That’s the kind of protection people adopt, trust, and eventually forget it’s even there.”
Wearables fail not because of technology limitations but because they require ongoing compliance from the people who need them most. Charging devices, remembering to put them on, and accepting that staying safe requires visible accommodation all reduce adoption and create gaps in monitoring when devices aren’t worn.
Radar-based sensing solves this by embedding monitoring into the environment rather than the person. Sensors detect movement, breathing patterns, and behavioral rhythms without requiring any action from the person being monitored. Daily routines become vital signs.
This matters because the goal isn’t just safety but maintained independence. People don’t want to feel monitored. They want to feel secure while living naturally. Invisible sensing provides security without the psychological burden of constant surveillance.
Turn Patterns Into Actionable Signals
Collecting data is easy; understanding it is the hard part. A caregiver doesn’t need a stream of motion graphs. They need one answer: Is my mother stable or starting to slip?
“That’s what a behavioral biomarker delivers,” Waddell emphasizes. “It converts the chaos of daily life into a single actionable signal.”
Waddell developed what he calls the Healthy Habits Index. It synthesizes behavioral patterns into a single metric that indicates whether someone is maintaining baseline function or experiencing drift that predicts decline.
This is the difference between data and insight. Most monitoring systems generate endless streams of information that caregivers lack the time or expertise to interpret. Did fewer bathroom trips last night mean better sleep or dangerous dehydration? Did reduced kitchen activity mean a light appetite or an emerging inability to prepare food? The data exists, but the meaning remains unclear.
Behavioral biomarkers solve this by establishing individual baselines and flagging deviations that correlate with increased fall risk or functional decline.
Building Before, Not After
When behavior becomes diagnostic, healthcare moves upstream. Detection happens sooner, intervention happens earlier, and families get something the current system rarely provides: time.
“Time to act before a crisis takes something that can’t be recovered,” Waddell explains.
The current model waits for the fall, then responds. The person goes to the emergency room, and many never return to independent living. The fall didn’t just cause injury. It triggered a cascade that ended independence.
Predictive fall prevention changes this timeline. When ADL drift becomes visible weeks before the fall, interventions can happen while the person is still strong enough to benefit. Physical therapy prevents falls instead of responding to them.
From Reaction to Prediction
After years of building the future of aging and longevity, Waddell is actively working towards a world where healthcare doesn’t wait for the fall.
“ADL drift is real. It’s measurable. It’s clinically meaningful,” Waddell concludes. “If we get this right, we won’t just respond to emergencies faster. We will prevent them.”
The body whispers before it screams. The question is whether healthcare will finally start listening.
Connect with Steve Waddell on LinkedIn for insights on AgeTech, predictive fall prevention, and ambient health intelligence.
