Data compression for neural systems

A system for compressing neural signal data using spatiotemporal data compression techniques. The system includes an implantable neural that receives electrophysiologic signal data from the electrode array, maps the electrophysiologic signal data to locations of each of the plurality of the electrodes, and compresses the mapped electrophysiologic signal data based on the locations of the plurality of electrodes utilizing a spatiotemporal data compression algorithm to define compressed electrophysiologic signal data. The implantable neural device can be connectable to a computer system that decompressed the electrophysiologic data for various downstream applications.

The abstract as published by the patent office, from US20240291504A1. It describes the invention; it is not a statement of what is protected.

• Interface and electrodes

  Electrodes and arrays

• Telemetry

  Data compression

• Signal processing

  Signal processing

What the filing appears to be about, read by published rules from its title, abstract and classification codes (A61B5/37, A61B5/7232, H03M7/70). The claims define what a patent protects, and they are not read here.

Interface and electrodes

Everything downstream works with what the contacts pick up. Their number, size and distance from the neurons set the ceiling on the signal. The problem behind it: more contacts, closer to neurons, that still record after years in tissue that reacts to them.

Telemetry

Thousands of channels produce more data than a low-power radio can carry raw, so what is sent, and how, decides what the system can use. The problem behind it: high data rates at low power through tissue, reliably and securely.

Signal processing

A decoder is only as good as the features it is given, and recordings drift and pick up noise from movement, muscle and stimulation. The problem behind it: stable features from signals that change from day to day, computed fast enough to act on.

Why the layer matters to the field, not a judgement of this filing. A patent family shows that protection was sought. It does not show that the technology was built, is used in a product, or works in people. The whole stack

One invention, published 6 times in 4 offices. Each publication opens in Espacenet.

• United StatesUS20240291504A129 Aug 2024US12592721B231 Mar 2026 · grantUS20260221987A130 Jul 2026
• International (PCT)a route to several countries, not a countryWO2024182501A16 Sep 2024
• AustraliaAU2024230815A12 Oct 2025
• European Patent Officea route to several countries, not a countryEP4673051A17 Jan 2026

1. 28 Feb 2023First filingEarliest priority, at United States. The family is counted in this year.
2. 28 Feb 2024ApplicationsFiled at United States, International (PCT), Australia, European Patent Office.
3. 29 Aug 2024First publicationUS20240291504A1, United States.
4. 12 Dec 2024Owner recordedUnited States, on US20240291504A1: assignment; owner named: PRECISION NEUROSCIENCE CORPORATION, NEW YORK.
5. 27 Mar 2026ApplicationFiled at United States.
6. 31 Mar 2026Grant publishedUS12592721B2, United States.

Dates as the offices published them. Office records are in the offices' own words and are a selection: refusals, lapses and withdrawals, and records that name an owner. Each concerns one member of the family, not the family as a whole, and another member in the same office may stand. Whether a patent is in force today is not assessed.

Organisation

Precision Neuroscience · 28 families identified

• Bibliographic data, family members and office records: European Patent Office, Open Patent Services (the DOCDB and INPADOC databases), read 7 Oct 2026.
• The record itself, with its claims and description: US20240291504A1 in Espacenet
• Counted as a BCI patent family: uses the field's wording; classified A61B5/37 (analysis and use of electroencephalograms); filed by PRECISION NEUROSCIENCE CORPORATION, an organisation already in the graph; describes neural hardware or methods without naming the field; cites a family already accepted. How families are found and judged