Short answer: IMUs aren’t a dead end — but IMU-only position is. And most teams that ship learn this the painful way.

IMUs win because they’re honest about what they’re good at: capturing change. Acceleration, rotation, rhythm, timing. That maps incredibly well to how wearables actually get used. The moment you ask them for absolute position over long periods, you’re basically asking integration error to politely not accumulate. It never does.

From stuff I’ve seen ship, the pattern usually looks like this:

IMU-only works surprisingly well when:

• You care about relative motion or short-window behavior (steps, reps, gestures, gait cycles).

• You can constantly re-anchor the signal (known poses, periodic events, user-specific baselines).

• The output is pattern-level, not geometry (“this looks like walking” vs “your ankle is here”).

That’s why watches, rings, earbuds, and even some VR controllers get away with IMU-heavy stacks. They don’t promise absolute truth — they promise consistency.

IMUs start hurting when:

• You need position to persist across hours.

• The sensor can rotate or slide on the body.

• You can’t assume a repeatable pose to reset drift.

At that point, “software magic” turns into drift management theater: clever filters, periodic resets, aggressive assumptions. It works until the user does something human, like sweat or sit weirdly.

This is where IMUs need help.
Not necessarily fancy help — just anchoring signals. Strain sensors, pressure/contact sensing, capacitive proximity, occasional optical cues. Even low-resolution, noisy secondary signals can collapse uncertainty if they answer one simple question: “Did the sensor move relative to the body?” You don’t need millimeter accuracy; you need constraint.

The teams with scars usually end up here: IMU as the backbone, everything else as guardrails. Position becomes an inferred state that’s constantly corrected, not a number you trust.

So yeah — IMUs aren’t going away. But anyone still pitching “IMU-only absolute position on the body” without qualifiers either hasn’t shipped yet… or hasn’t worn their own device for a full day.

This really resonates.

One thing I’m curious about though — when people say “IMU-only is fine with good algorithms,” do you think that’s just optimism, or does it actually hold in some real products?

It holds conditionally.

IMU-only is fine as long as you’re honest about the conditions.

Short time windows, repeatable motions, and outputs that are descriptive, not absolute.

The moment marketing or PMs start implying persistent position or geometry, you’re in trouble.

The algorithm didn’t get worse — the promise did.

That makes sense. Where do you usually see teams realize they’re in trouble? Is there a specific failure mode that triggers the “oh no” moment?

Yeah — multi-hour wear. Everything looks great in a 15-minute demo.

Then someone wears it all day, takes it off, puts it back slightly rotated, and suddenly yesterday’s model doesn’t apply.

That’s usually when teams realize drift isn’t just math, it’s behavior.

And that’s when secondary sensors suddenly look very attractive.

Thank you so much, sensorinsight.

I’ll ask you again if I have any questions.

Jumping in here — when you say “IMUs need help,” how minimal can that help be?

Are we talking full optical systems, or can something dumb and cheap actually move the needle?

Honestly, dumb and cheap wins more often. Even a binary-ish signal like pressure contact or strap tension can be huge.

You’re not trying to measure position with it — you’re trying to answer “did the sensor shift?” That single bit of information can stabilize everything else.

Interesting. So would you say future wearables are more about sensor fusion than better sensors?

100%. Better sensors help incrementally, but fusion changes the game.

IMU for motion, something else for anchoring, and software that assumes everything can lie a little.

The teams that ship stop chasing perfect sensors and start designing systems that recover gracefully when humans do human things.