EEG Sensor and Acquisition System Development

What does this service cover?

EEG sensor and acquisition system development supports products and research systems that need to capture, record, transfer, and analyze electroencephalography signals. The engineering scope can include electrode interfaces, low-noise analog front ends, ADC and controller integration, embedded firmware, data transport, desktop or mobile acquisition software, and signal-quality tools.

Channel count, sampling rate, input range, noise target, electrode type, isolation, communications, and power architecture must be defined from the intended scenario. This page describes engineering services; it does not state that a prototype has medical-device clearance, diagnostic status, or predetermined performance.

Applicable projects

• Research acquisition: EEG recording, stimulus event markers, device synchronization, and raw-data export.
• BCI prototypes: real-time EEG streams, processing interfaces, and algorithm evaluation tools.
• Sleep and health monitoring: single- or multi-channel EEG, optionally synchronized with EOG, EMG, motion, respiration, or SpO2.
• Device integration: integration of an EEG module with an existing terminal, embedded host, mobile application, or data platform.
• Algorithm data pipelines: traceable inputs for signal processing, event detection, state classification, or sleep staging.

Hardware development scope

Firmware and software scope

• Multi-channel sampling, buffering, packet-loss checks, timestamps, event markers, and fault records;
• electrode-contact or impedance checks where supported by the selected front end and safety design;
• raw waveform display, channel configuration, recording, playback, export, and device logs;
• digital filtering, mains rejection, saturation, disconnection, and basic artifact flags;
• file or API interfaces for MATLAB, Python, desktop software, mobile applications, or customer platforms;
• EDF/EDF+ evaluation when required, subject to the agreed interface specification and test results.

Signal quality and verification

Verification should cover more than whether a waveform is visible. A project may test shorted-input noise, frequency response, channel consistency, saturation recovery, mains interference, electrode-contact changes, long recordings, data integrity, and time synchronization. Algorithm datasets should also retain device versions, acquisition parameters, subject identifiers, event markers, and exclusion reasons.

Acceptance criteria must be defined before development. Terms such as “medical grade,” “diagnostic grade,” or a fixed accuracy should not be used without matching test conditions, sample scope, and regulatory evidence.

Typical deliverables

• Requirements, system architecture, interface definitions, and a technical risk list;
• schematics, PCB, BOM, embedded firmware, and version records where included in the contract;
• acquisition, configuration, playback, or diagnostic software and interface documentation;
• prototypes, debug records, functional tests, and known limitations;
• production-test recommendations, calibration or inspection tools, and an iteration backlog.

How does EEG acquisition relate to sleep staging?

EEG acquisition is one possible data source for sleep staging, but obtaining EEG waveforms does not by itself create a validated staging function. Sleep staging also needs a label protocol, data quality control, artifact handling, training and verification datasets, model deployment, and review workflows. See the EEG sleep staging hardware and software development solution for the complete path. For motion, PPG, SpO2, respiration, or pressure sensing, see sleep monitoring sensor and data acquisition system development.

Can an EEG acquisition system be used directly for medical diagnosis?

Not based on an engineering page or prototype alone. Diagnostic use depends on the intended purpose, risk classification, design controls, verification, clinical evaluation, and applicable clearance or registration. Until those activities are complete, the system should be managed for research, prototyping, or another explicitly agreed non-diagnostic use.

How are channel count and sampling rate selected?

They are selected from the target signal, electrode locations, algorithm inputs, data bandwidth, power, mechanical design, and budget. The project should first define the channels, frequency range, recording duration, synchronization devices, and output format.

Can the system use an existing electrode or EEG front end?

An interface assessment can be performed. Electrode construction, connectors, front-end documentation, schematics or interface specifications, data format, power architecture, samples, and current test records are needed. Compatibility is confirmed by integration testing.

Can Winge develop only the acquisition software or algorithm interface?

Yes, the scope can be modular. When stable hardware already exists, work can focus on drivers, protocols, desktop or mobile software, file formats, SDKs, or algorithm data interfaces.

What information is needed to start?

Provide the use case, target users, signals and channels, sampling requirements, electrode information, mechanical limits, communications, recording duration, data format, algorithm purpose, reference equipment, compliance target, and acceptance method. A small feasibility phase can be used when parameters are incomplete.