Consent architecture, data governance, and audit-ready infrastructure for health tech companies that collect biosignal data: sleep, cycle, heart, glucose, mood, and neural signals.
State, federal, and international frameworks increasingly require specific, affirmative, and revocable consent for each use of sensitive health data.
Washington's My Health My Data Act and Nevada's consumer health data law require separate consent to collect and share health data, and signed authorization to sell it. Washington's law includes a private right of action.
Colorado, California, Connecticut, and Montana classify neural data as sensitive personal information. Most state privacy laws already treat health and mental health data as sensitive, requiring opt-in consent.
The FTC's Health Breach Notification Rule covers health apps and connected devices outside HIPAA. BIPA litigation shows the class-action exposure attached to biometric identifiers.
Health data is a special category under GDPR. Controller and processor duties carry direct regulatory exposure and downstream liabilities across every partner that touches the data.
HIPAA covers providers, health plans, and their business associates. Consumer wearables, smart rings, and health, fitness, and femtech apps usually fall outside it, which places them under the stricter per-use consent rules above.
Each sector collects a different signal. All of them need consent captured, tracked, and enforced for every use of the data.
Cycle, fertility, pregnancy, and menopause tracking.
Exposure: among the most scrutinized health dataRings, headbands, and apps measuring sleep stages, HRV, and breathing.
Exposure: sharing with research and AI partnersHeart rate, HRV, recovery, and activity trackers.
Exposure: opt-in and data sale restrictionsConsumer glucose monitoring and metabolic health apps.
Exposure: sits between wellness and medical rulesMood tracking, meditation, and stress monitoring.
Exposure: classed as sensitive under most state lawsEEG headbands, neurofeedback, and brain-computer interfaces.
Exposure: explicit neural data laws in CO, CA, CT, MTThe deeper a signal goes, the more it can reveal about a person. Neural data sits at the far end: it can support inferences about cognition and emotional state, carries persistent "brainprints," and is now named directly in state law.
FISE's consent and governance model was designed for that standard first. A layer built to govern brain data brings the same rigor to sleep, cycle, heart, and metabolic data.
If our governance holds for neural data, it holds for yours.
Illustrative framework. Every tier is treated as sensitive health data under at least some current laws, and all tiers can be combined to reveal more than any single signal alone.
FOR BCI MANUFACTURERS
Data governance, liability, and consent for brain-computer interface manufacturers.
Written by M.E. Nara Lau (CEO Founder, FISE Technologies), this guide examines the most demanding category of sensitive human data: statutory shifts, biometric re-identification risk, the HIPAA gap for consumer devices, technical standards, and controller and processor liability. Its principles of purpose-specific consent, downstream partner governance, and auditable proof of data use apply to every continuously generated biosignal.
FISE combines IT and compliance in one platform, so your product team keeps building while proof of policy replaces marketing claims.
Per-use, per-purpose authorization tied to each user: collection, sharing, research, AI training.
Cloud-hosted, key-separated, jurisdiction-aware. Encryption at rest and in transit.
Consent and revocation passed to downstream research, AI, OEM, and partner integrations.
Immutable log of who accessed what, when, and under which consent scope.
| Data Use | What Regulators Expect | How FISE Handles It |
|---|---|---|
| Collection | Consent before health data is collected | Captured in-app, per user and purpose |
| Partner sharing | Separate consent from collection | Consent and revocation passed downstream |
| Research | Purpose-specific, informed consent | Scopes recorded per study and per user |
| AI training | Consent for secondary use, revocable | Permissions tracked per dataset |
| Sale of data | Signed authorization in some states | Authorization records with audit trail |
Requirements vary by state. FISE maps them to your products during the gap assessment.
Every organization evaluates technical autonomy differently. Compare the trade-offs for your biosignal data pipeline.
Develop custom consent state machines, cryptographic audit logging, and regulatory mapping internally within your engineering team.
An interoperable, auditable consent and identity layer aligned with applicable standards and regulations, integrated with your existing data pipeline through standard APIs.
Published data-format and interoperability standards do not specify integration with portable identity or consent technologies such as W3C DIDs or Verifiable Credentials.
FISE Solution: An off-the-shelf governance layer linking biosignal data structures to portable identity and auditable consent.
Compliance and data-flow audit. Gaps mapped by state and data use.
Consent schema tailored to your product, signals, and stack.
Rollout, audit setup, and staff training.
Regulatory monitoring, quarterly reports, and incident response.