call-acoustic-breath-biomarker-tracker · v1.0.0 · 2026-09-18 · sha256 10a4e70c703ac3f9
call-acoustic-breath-biomarker-tracker v1.0.0A
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--- name: call-acoustic-breath-biomarker-tracker description: Offline nonclinical phone-workflow demonstration over supplied speech/pause durations. Returns illustrative pause-ratio labels, not medical findings or an actual emergency handoff. version: 1.0.0 --- # Acoustic Breath Biomarker Tracker This experimental helper calculates a pause ratio from synthetic, pre-segmented durations. It does not capture audio, run VAD, detect a medical condition, assess patient safety, or execute a handoff. Its `DYSPNEA_DETECTED`, `NORMAL`, and action enums are illustrative legacy labels, not clinical conclusions. Do not use this prototype for patient triage or emergency decisions. ## Scientific Foundation | Paper / Framework | Source | Relevance | |---|---|---| | Detection of Mild Dyspnea from Pairs of Speech Recordings | IEEE ICASSP (2020) | Provides the acoustic feature extraction models for identifying respiratory variations and abnormal pause mechanics. | | Biomarkers in respiratory diseases | Breathe editorial (2019) | General background, not validation of pause-ratio clinical inference. | | COVID-19-related voice disorders: a scoping review | PubMed (2026) | Background on voice disorders, not validation of this helper. | | Software as a Medical Device (SaMD) | FDA (2023) | Regulatory framework for AI algorithms evaluating biological states. | ## How it works 1. Supply synthetic `AudioSegment` durations to the helper. 2. Audio capture and VAD are not included; any future host would provide its own inputs. 3. The `process_call_stream` function evaluates the extracted segments. 4. A pause ratio at or above the illustrative threshold selects the legacy `DYSPNEA_DETECTED` enum; it does not establish dyspnea. 5. `ESCALATE_TO_HUMAN` is returned as a demo label only. No workflow is halted and no nurse transfer or emergency handoff occurs. ## Decision Matrix | Pause Ratio | Classification | Recommended Action | |---|---|---| | `>= 0.40` | `DYSPNEA_DETECTED` | `ESCALATE_TO_HUMAN` | | `< 0.40` | `NORMAL` | `PROCEED_NORMALLY` | | `Ratio < 0 (no data)` | `INSUFFICIENT_DATA`| `INDETERMINATE` | ## Configuration Reference | Parameter | Default | Range | Description | |---|---|---|---| | `pause_threshold_ratio` | `0.40` | `0.30 - 0.60` | Ratio of pause time over total time to trigger dyspnea flag. | | `segment_duration_ms` | `500` | `250 - 2000` | Window size for acoustic feature extraction. | ## Expected Outcomes & Metrics The figures below are unvalidated design aspirations, not clinical sensitivity, specificity, or handoff guarantees. | Metric | Target | Notes | |---|---|---| | Escalation Latency | < 1 second | Critical for emergency health response. | | False Positive Rate (FPR) | < 5% | Legitimate pauses shouldn't trigger an emergency. | | False Negative Rate (FNR) | < 2% | Must not miss severe respiratory distress. | ## Limitations & Known Constraints - **Codec Degradation**: Low-bitrate connections may obscure acoustic pauses or falsely introduce silence gaps (packet loss). - **Background Noise**: Heavy environmental noise might be misclassified as speech by VAD, lowering the calculated pause ratio. - **Not a Clinical Tool**: This is not a diagnostic or patient-triage mechanism. Low scores do not establish that a person is safe. ## Possible Future Research Contexts These contexts require separate clinical evaluation and human-governed systems; they are not supported patient-care uses of this prototype. - Post-discharge monitoring for COPD or heart failure patients. - Daily check-in phone calls for patients with severe asthma. - Triage in automated telehealth intake systems. ## Integration No dialogue-model or telephony integration is included. For a future host, this numeric demonstration must not delay human review or override an explicit report of distress.