"Frequencies" are just one piece of the puzzle

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1. v4 2026-09-12 07:54 posts: inline source cards, and every post cut to the point Joshua Anderton with Claude Opus 5 +209 −491 words

   status: published

   inline_sources: true

   tier: C

   ---

   This is a process post. It is about building a list, why the list turned out to be the useful artefact, and what checking it against non-living waves did to it.

   Process note. Building a list of what a biological signal is known to carry, then pointing the same reader at waves with nothing alive in them.

   The startingStarting observation is unremarkable once stated: **an ECG is not only a record of a heart contracting.** The published literature has read identityIdentity, sex, age and health have all been read out of the same traceone. If that isholds truefor ofa onesingle signal, the obvious question is what *every* biological signal carries, and whether the same structural features carry it each time.

   Answering that properly starts with a boring inventory.

   ## The signals catalogued so far

   Six, named by thesource tissue they come from rather than the application they serve. These are representativeRepresentative textbook ranges, not hard bounds.

   | signal | source | band | amplitude | what its shape is like |

   |---|---|---|---|---|

   | **ECG** | myocardium | ~0.05–100 Hz | 1–10 mV | strongly periodic, one sharp recurring event, very consistent beat shape |

   | **EEG** | cortex | ~0.5–100 Hz | 2 µV – 0.1 mV | broadband, oscillatory, band-structured, weakly event-locked |

   | **EMG** | skeletal muscle | ~2–500 Hz | 50 µV – 5 mV | burst-structured, high-frequency, amplitude tracks effort |

   | **EOG** | corneo-retinal dipole | ~DC–10 Hz | 10 µV – 5 mV | slow steps and ramps — saccades, blinks —; essentially DC |

   | **EDA** | sweat glands | ~DC–2 Hz | µS-scale | a slow level with responses on top; not oscillatory at all |

   | **EGG** | stomach smooth muscle | ~0.03–0.15 Hz | 10–500 µV | a very-low-frequency near-sinusoidal pacemaker rhythm |

   Writing**The thatuseful tablepart was the first useful thing, and not for the reason I expectedunexpected.** Laid out together, the six areseparate separated byon properties that have nothing to do with physiology: how periodic they are, how sharp theirthe events are, where theirthe spectral weight sits, how much DC they carry. **You can tell them apart without knowing whatthe tissue you are looking at.** That is either an interesting fact about biological signals or an artefact of how they are all recorded, and I genuinely do not know which yet.

   ## The axes, and where each one comes from

   That is either an interesting fact about biological signals or an artefact of how they are all recorded. Which one is not known here.

   ## The information axes

   The second list is the map: whatWhat kind of information is a biological wave known to carry?. Each row below is an entry point to a literature, not a claim of mine.

   **Identity.** Attributing a trace to a specific person is a mature field for ECG {% include cite.html key="fratini2015" %}, and there iswith a parallel line of work on individuating signatures in EEG {% include cite.html key="chan2018" %}.

   {% include source.html key="fratini2015" %} {% include source.html key="chan2018" %}

   **Sex and age.** Both have been read from short clinical recordings.

   {% include source.html key="attia2019" %}

   **Sex and age.** Both have been read from short clinical recordings {% include cite.html key="attia2019" %}, and theThe *discrepancy* between an age estimated from the signal and thea person's actual age has itself been studied as a marker {% include cite.html key="lima2021" %}.

   {% include source.html key="lima2021" %}

   **Autonomic and affective state.** Heart-rate variability is the standard non-invasive window onto autonomic balance, and; electrodermal activity indexes a sympathetic pathway directly.

   **Intention.** Muscle activity decodes motor intent; cortical activity carries potentials that precedepreceding movement rather than followfollowing it.

   **Health.** The axis with the most literature behind it, and the only one this bench has measured anything on directly.

   I want to be careful here, because this is exactly the point where a survey turns into an overclaim: **I have not read any of those papers at full text.** They are cited as the entry point to their topic. What I can say is that these axes exist and are established; what I cannot say from this page is what any individual study found.

   None of those papers was read at full text. They are cited as entry points; what they exist to study is stated, not what any of them found.

   ## The part I did not expectreframing

   Building the list changed what I thought the project waslooked like.

   It had been treated as signal processing — extracting a feature from a trace. Laid out together the axes look like a **taxonomy** problem instead.

   I had been treating this as *signal processing* — a question about extracting a feature from a trace. Laying the axes out next to each other makes it look like a **taxonomy problem** instead. Identity, sex and age are properties that barely change. State and intention change minute to minute. Health drifts. Those are not the same kind of quantity, and lumpingcalling them together asall "information in the signal" hides the most important distinction between them.

   That reframing is the actual output of the exercise, and it came from making a table, not from running anything.

   ## Pointing it at wavesWaves with nothing alive in them

   Here is the part that keeps the whole thing honest, and it is the reason I would defend this method to anyone building something similar.

   If you build aA reader that finds rich structure in biological signals, you havehas to askbe asked whether it finds rich structure in *everything*. So the same reader gets pointed at waves with no organism anywhere in them:

   - **Tide gauges** — two stations, 61 days. A blind read recovered the principal lunar semidiurnal period and correctly separated the moon's contribution from the weather's.

   - **Solar flux against cosmic-ray flux** — 14.6 years. It recoveredRecovered the known anticorrelation, but only when given the full cycle. That makes it a result about *how much data you need*.

   *how much data you need*, not about the sun.

   - **Seismic, infrasound, ocean sound and the, geomagnetic field** — it recovered the secondary microseism and the daily solar-quiet variation, blind.

   The standing rule on that log is the sentence I would put on the wall:

   > A high structure score on a signal with no organism in it is a caution about the > instrument, not a finding about nature.

   **Reading tides well is partly bad news.** It means theThe structure thebeing reader is findingfound might be a property of the reader rather than of life. Every oneTwo of those runs wasdid a test ofembarrass the instrument that could have embarrassed it, and two of them did — one exposed silent bugs at low sample rates, another showed a standard statistical null to be invalid on deterministic signals.

   ## Sound, light, and water

   The obvious next question is whether the same characteristics carry information in non-biological waves, and here I want to be honest about the state of it: **this is mapped, not tested.**

   Mapped, not tested.

   The structural properties in question — how loud, how bright, how periodic, how consistent the repeating unit is, whether a slow rhythm modulates a fast one — all have natural readings in sound and in light. Loudness and timbre in acoustics; brightness and colour in optics; amplitude and morphology in a bioelectric trace. Water gave the cleanest test so far precisely because a tide is sowell wellenough characterised that the reader had nowhere to hide.

   But aA correspondence you can *write down* is not a correspondenceone you have *shown*. Applying these characteristics across modalities is, until it is tested the same way the cardiac work was, **a hypothesis carried by analogy.** I would rather say that plainly than let a tidy table imply otherwise.

   ## What would make this wrong

   If the structural characteristics that separate biological signals turn out to separate

   If the structural characteristics separating biological signals turn out to separate *any* filtered time series equally well, then the shared-grammar idea is an artefact of everyone using similar analysis pipelines, and this survey is describingdescribes the pipeline rather than describing life. That is a reallive possibility, it is the reasonwhy the non-biological waves get read at all, and nothing on this pagehere rules it out.

   Commit fb7ef7b on GitHub →

2. v3 2026-09-03 16:02 site: envelope icon on the contact link, retitle the wave post Joshua Anderton with Claude Opus 5 +9 −13 words

   ---

   title: "What a wave can tell you about the thing that made it"

   title: '"Frequencies" are just one piece of the puzzle'

   description: >-

   Commit 79b6678 on GitHub →

3. v2 2026-09-03 15:17 site: images on every post, bigger thumbnails, CTA moves into the sidebar Joshua Anderton with Claude Opus 5 +39 −0 words

   - lima2021

   image: /assets/posts/sea-wave.jpg

   image_alt: >-

   A breaking ocean wave photographed close to the water surface.

   image_credit: Editor abcdef

   image_license: CC0

   image_license_url: https://creativecommons.org/publicdomain/zero/1.0/

   image_source_url: https://commons.wikimedia.org/wiki/File:Sea_wave_saipan.JPG

   summary: >-

   Commit cb0df37 on GitHub →

4. v1 2026-09-01 12:19 posts: the magnetometer walkthrough, and the wave-information survey Joshua Anderton with Claude Opus 5 first version

   v1: the original version, as first committed. Read it on GitHub →

   Commit 3f615ec on GitHub →