Neural Signal Compression for Wireless Brain-Computer Interfaces

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Solution Overview

Problem

Current brain-computer interfaces face challenges in efficiently transmitting high-bandwidth electrophysiologic data wirelessly due to the limitations of existing wireless communication protocols, leading to data throttling or wired connections that tether patients and compromise data fidelity.

Innovation Solution

Implementing spatiotemporal data compression algorithms, such as H.264, H.265, and AV1, to compress electrophysiologic data from non-penetrating electrode arrays, leveraging the spatial and temporal correlations in neural signal data to achieve substantial lossless compression.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If high-bandwidth electrophysiologic data is transmitted wirelessly using current protocols, then data transmission capability is improved, but data loss increases due to insufficient bandwidth

Engineering Contradiction:

Improvedata transmission capabilityVSAvoiddata loss

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The patent applies preliminary action by performing data compression before transmission. The spatiotemporal compression algorithm processes electrophysiologic data in advance, reducing its size while preserving essential information, so that the compressed data can be transmitted within the bandwidth constraints of wireless protocols without significant data loss.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent changes the parameters of the data by applying spatiotemporal compression algorithms that transform the original high-bandwidth electrophysiologic data into a compressed representation. This parameter transformation reduces the data size while maintaining the critical neural signal characteristics needed for accurate decoding.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If data transmission rate is increased to match data generation rate, then data fidelity is improved, but wireless protocol limitations cause data loss

Engineering Contradiction:

Improvedata fidelityVSAvoiddata loss

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The system performs preliminary compression of the electrophysiologic data using spatiotemporal algorithms before transmission. This preliminary processing reduces the data rate to match wireless protocol capabilities while preserving the fidelity of the neural signals through intelligent compression that maintains essential signal characteristics.

Inventive Principle:

Principle #10Preliminary action

3Measurement precision

If existing lossless compression algorithms are used, then data fidelity is maintained, but compression ratio is insufficient for wireless transmission

Engineering Contradiction:

Improvedata fidelityVSAvoidcompression ratio

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent applies parameter changes by using spatiotemporal compression algorithms that transform the data representation to achieve much higher compression ratios. These algorithms exploit the temporal and spatial correlations in electrophysiologic data to achieve compression ratios of 10:1 or higher while maintaining data fidelity suitable for neural decoding applications.

Inventive Principle:

Principle #35Parameter changes

4Productivity

If existing lossy compression algorithms are used, then compression ratio is improved, but data fidelity deteriorates to an undesirable degree

Engineering Contradiction:

Improvecompression ratioVSAvoiddata fidelity

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent changes the compression approach by using spatiotemporal algorithms that achieve high compression ratios while preserving data fidelity. Unlike traditional lossy compression, these algorithms maintain the essential neural signal characteristics needed for accurate decoding, achieving a balance where compression ratios of 10:1 or higher do not significantly degrade measurement precision.

Inventive Principle:

Principle #35Parameter changes

5Productivity

If data throttling is applied to match transmission bandwidth, then wireless transmission becomes feasible, but data fidelity is substantially impacted

Engineering Contradiction:

Improvetransmission feasibilityVSAvoiddata fidelity

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

Instead of simple data throttling, the patent applies spatiotemporal compression that intelligently reduces data parameters while preserving fidelity. This approach transforms the data to achieve the necessary reduction for wireless transmission without the substantial fidelity loss that would result from naive throttling methods.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12592721B2Data compression for neural systems

Publication Date: 2026.03.31 PRECISION NEUROSCIENCE CORP

AI summary

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.