Say: a handheld push-to-talk microphone for working with AI, integrating heart rate variability and galvanic skin response sensing in the button face for real-time stress measurement.
Author: Pablo Sanzo
Status: Invention disclosure, published for prior-art purposes.
Say is a handheld voice input device for working with artificial intelligence agents on a personal computer, which simultaneously measures the user's physiological stress response during the interaction. A push-to-talk button captures voice only while the user is pressing it; the audio is transcribed locally and classified as dictation or as a command for the host computer. The button face integrates a photoplethysmography sensor for heart rate variability measurement and two electrodes for galvanic skin response measurement — together with acoustic voice analysis and linguistic content analysis, these four signals fuse into a single self-relative stress score. A coaching layer issues contextual notifications, generated locally by a language model, when sustained stress crosses a personalised threshold. Collected data is anonymised on the user's local machine using an open-source semantic-redaction pipeline before any transmission. Users may opt in to contribute anonymised expert interaction data to a marketplace serving AI training labs, compensated via an ongoing royalty share. Say is a health device designed specifically for cognitive work with AI, distinct from computer-peripheral microphones.
Plain language: voice input, push-to-talk microphone, AI cognitive strain, stress measurement wearable, heart rate variability sensor, galvanic skin response sensor, skin conductance, handheld health device, local speech-to-text, local language model, voice assistant, AI agent interaction, cognitive load monitor, burnout prevention, expert data marketplace, paired interaction-biometric dataset, open-source anonymisation.
Technical / patent-style: handheld push-to-talk voice input device, photoplethysmography (PPG) integrated in a tactile input actuator, bioimpedance skin conductance sensing via dual electrodes on a push-to-talk button, vocal biomarker extraction (fundamental frequency F0, jitter, shimmer, harmonics-to-noise ratio), linguistic stress markers from transcribed speech, composite self-relative cognitive-strain score, on-device speech-to-text and intent classification, chromium-silicon-carbon-nitride (CrSiCN) semi-transparent chrome-appearance coating on a sapphire dielectric substrate, inductive charging through dielectric button face, two-exponent superellipsoid handheld device form factor, electrochemical aptamer-free non-invasive stress sensing, three-stage data pipeline with local semantic anonymisation, royalty-share data marketplace for AI training data, paired interaction-biometric dataset, human-computer interface for generative AI.
The following Cooperative Patent Classification codes best describe the subject matter disclosed here.
- A61B 5/02405 — Measuring pulse rate or heart rate derived from the optical signal of a photoplethysmograph
- A61B 5/02416 — Measuring pulse rate or heart rate using photoplethysmograph signals as such
- A61B 5/0531 — Measuring skin impedance (galvanic skin response)
- A61B 5/0533 — Measuring galvanic skin response
- A61B 5/024 — Detecting or measuring pulse rate or heart rate
- A61B 5/165 — Evaluating the state of mind, e.g., depression, anxiety
- A61B 5/486 — Biofeedback
- A61B 5/742 — Details of notification to user
- A61B 5/74 — Details of notification to user or communication with user or patient
- A61B 5/681 — Wristwatch-type devices (for reference; Say is handheld, not worn)
- A61B 5/68 — Sensor arrangements on the body
- G10L 25/63 — Speech or voice analysis techniques for the purpose of emotion recognition
- G10L 25/66 — Speech or voice analysis techniques for the purpose of extracting parameters related to health condition
- G10L 15/22 — Procedures used during speech recognition, e.g., man-machine dialogue
- G10L 15/26 — Speech-to-text systems
- G06F 3/16 — Sound input; sound output; audio user interfaces
- G06F 3/167 — Audio in a user interface
- G16H 10/60 — Patient-specific data
- G16H 50/30 — Individual health risk assessment
- G16H 20/70 — ICT specially adapted for therapies or health-improving plans, e.g., for mental therapies or persuasive computing
- G06N 20/00 — Machine learning
- H04W 4/80 — Short-range radio, e.g., Bluetooth
spec.md— the Say product specification. This is the invention disclosure.README.md— this file: abstract, keywords, and CPC codes for findability.
This disclosure is published publicly to establish prior art under 35 U.S.C. §102(a)(1). Any person is free to inspect, cite, and build on the subject matter disclosed here. The author does not intend to pursue patent protection on the subject matter disclosed in this repository. Commit timestamps on this repository, combined with GitHub's server-side record and the Wayback Machine's archival crawl, constitute the publication date.
Pablo Sanzo — the author will update this repository as the invention is implemented and shipped. Substantive changes to the invention disclosure itself, once first committed, will be recorded as additional files with their own timestamps rather than by modifying the original disclosure.