A layer-by-layer overview of the EMPATHIQ system architecture. This page describes what each layer does and why it matters. The complete algorithm pseudocode, DEH data schema, RDRS computation parameters, and patent claim language are available in the full Technical Briefing Package — provided to qualified partners under NDA.
The complete algorithm specification, data schema, implementation parameters, and patent claim language for this component are included in the EMPATHIQ Technical Briefing Package — available to qualified partners under a signed non-disclosure agreement.
Request Technical Briefing →A layer-by-layer overview of the EMPATHIQ system architecture. This page describes what each layer does and why it matters. The complete algorithm pseudocode, DEH data schema, RDRS computation parameters, and patent claim language are available in the full Technical Briefing Package — provided to qualified partners under NDA.
The complete algorithm specification, data schema, implementation parameters, and patent claim language for this component are included in the EMPATHIQ Technical Briefing Package — available to qualified partners under a signed non-disclosure agreement.
Request Technical Briefing →The system degrades gracefully — no single modality is required. Masked self-attention in the Transformer handles absent modalities. A confidence field in the ESV output reflects the number and quality of active modalities, enabling downstream components to weight estimates appropriately.
The PEB is constructed exclusively from each user's own longitudinal ESV data — not population norms. This is a key differentiator from all prior art. An anxious person's "calm" looks different from a calm person's "calm." Prior art systems apply population thresholds to everyone.
The complete algorithm specification, data schema, implementation parameters, and patent claim language for this component are included in the EMPATHIQ Technical Briefing Package — available to qualified partners under a signed non-disclosure agreement.
Request Technical Briefing →The DEH is the longitudinal personalised dataset maintained by the system, linking each decision event to the emotional state preceding it and the outcome that followed. It is the training foundation for the RDRS model.
The complete algorithm specification, data schema, implementation parameters, and patent claim language for this component are included in the EMPATHIQ Technical Briefing Package — available to qualified partners under a signed non-disclosure agreement.
Request Technical Briefing →🔒 All DEH records stored on-device only · Encrypted at rest · User-deletable with immediate effect
The complete algorithm specification, data schema, implementation parameters, and patent claim language for this component are included in the EMPATHIQ Technical Briefing Package — available to qualified partners under a signed non-disclosure agreement.
Request Technical Briefing →The complete algorithm specification, data schema, implementation parameters, and patent claim language for this component are included in the EMPATHIQ Technical Briefing Package — available to qualified partners under a signed non-disclosure agreement.
Request Technical Briefing →A layer-by-layer overview of the EMPATHIQ system architecture. This page describes what each layer does and why it matters. The complete algorithm pseudocode, DEH data schema, RDRS computation parameters, and patent claim language are available in the full Technical Briefing Package — provided to qualified partners under NDA.
The complete algorithm specification, data schema, implementation parameters, and patent claim language for this component are included in the EMPATHIQ Technical Briefing Package — available to qualified partners under a signed non-disclosure agreement.
Request Technical Briefing →The system degrades gracefully — no single modality is required. Masked self-attention in the Transformer handles absent modalities. A confidence field in the ESV output reflects the number and quality of active modalities, enabling downstream components to weight estimates appropriately.
The PEB is constructed exclusively from each user's own longitudinal ESV data — not population norms. This is a key differentiator from all prior art. An anxious person's "calm" looks different from a calm person's "calm." Prior art systems apply population thresholds to everyone.
The complete algorithm specification, data schema, implementation parameters, and patent claim language for this component are included in the EMPATHIQ Technical Briefing Package — available to qualified partners under a signed non-disclosure agreement.
Request Technical Briefing →The DEH is the longitudinal personalised dataset maintained by the system, linking each decision event to the emotional state preceding it and the outcome that followed. It is the training foundation for the RDRS model.
The complete algorithm specification, data schema, implementation parameters, and patent claim language for this component are included in the EMPATHIQ Technical Briefing Package — available to qualified partners under a signed non-disclosure agreement.
Request Technical Briefing →🔒 All DEH records stored on-device only · Encrypted at rest · User-deletable with immediate effect
The complete algorithm specification, data schema, implementation parameters, and patent claim language for this component are included in the EMPATHIQ Technical Briefing Package — available to qualified partners under a signed non-disclosure agreement.
Request Technical Briefing →Smartphone (iOS 16+ / Android 12+, 6GB RAM, NPU/Neural Engine) paired with consumer wrist-worn wearable providing minimum HRV, BVP, and EDA. Compatible with Samsung Galaxy Watch 4+, Fitbit Sense 2+, Empatica EmbracePlus, and equivalents. BLE connection. AES-256 on-device storage. Estimated 5–12% additional battery drain per day.
No wearable required. HRV approximated via camera-based rPPG. Arousal proxied via keyboard IKI variance and error rate. Voice, accelerometer, gyro, and context signals identical to first embodiment. ESV has acknowledged lower physiological precision in Arousal dimension. DEH, PEB, RDRS, and intervention layers operate identically. Significantly broader accessible user population.