Tagged wearables
4 pieces
- · 7 min read
Cadence Lock: When Your Heart-Rate Monitor Starts Counting Your Steps
Optical heart-rate algorithms separate the cardiac signal from motion by picking the dominant periodic component. When step frequency converges on heart rate, which happens routinely in field sports, the algorithm can lock onto cadence and report steps per minute as beats per minute. It is confident, stable and wrong, and nothing on the display indicates it. The validation protocol has to contain the condition where the two frequencies meet.
- · 10 min read
The Shape Of A Heartbeat Is A Firmware Decision
A convincing mechanical heartbeat is asymmetric and punctuated: a fast contraction over roughly one third of the cycle, a brief hold, a slower release, then a real pause taking roughly two thirds. A motor turning at constant speed produces a smooth sinusoid that reads as a machine running. The shape cannot come from the mechanism, so it has to come from the controller, and that makes the perceptual requirement a firmware problem. There is no machine learning anywhere in this system.
- · 7 min read
The Physical Ceiling: What No Model Can Recover From Your Sensor
Whatever your sensor and that first little circuit throw away is gone. You cannot get it back later with software. A photo that comes out blurry does not become sharp with editing, and the fancy tools that appear to sharpen it are inventing plausible detail rather than recovering real detail, which is exactly the distinction that matters when the output drives a decision about a person.
- · 18 min read
Sensor Placement Is an Algorithm Decision
On a wearable device, where the sensor physically sits is not a comfort decision, it is the decision that determines whether you need an AI model at all, and whether you ship in 6 months or 18. It is usually made in month 2 by someone who does not work on signals, and by month 9 it has quietly become a year-long AI project nobody planned.