Prosecution Insights
Prosecution Insights
3 pending office actions • 2 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready
Based on the USPTO statutory response window for each pending office action. 2 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §101 + other | 2 (67%) |
| §103 only | 1 (33%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| NGUYEN, HIEN NGOC | 1 | 52.7% | +40.2% |
| JENNESS, NATHAN JAY | 1 | 53.8% | +37.8% |
| LEVERETT, MARY CHANG | 1 | 61.1% | +22.9% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18026890 | METHOD AND DEVICE FOR ANALYZING ABNORMAL PHYSIOLOGICAL STATE | JENNESS, NATHAN JAY | 132d overdue |
| 18026898 | METHOD AND DEVICE FOR ANALYZING BIO-SIGNAL | LEVERETT, MARY CHANG | — |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18026890 | METHOD AND DEVICE FOR ANALYZING ABNORMAL PHYSIOLOGICAL STATE | JENNESS, NATHAN JAY | 132d overdue |
| 18692056 | DEEP LEARNING-BASED ATRIAL FIBRILLATION DETERMINATION SYSTEM USING PPG SIGNAL DETECTION RING | NGUYEN, HIEN NGOC | 33d |
| 18026898 | METHOD AND DEVICE FOR ANALYZING BIO-SIGNAL | LEVERETT, MARY CHANG | — |
| Art Unit | Apps |
|---|---|
| 3797 | 1 |
| 3733 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18692056 | DEEP LEARNING-BASED ATRIAL FIBRILLATION DETERMINATION SYSTEM USING PPG SIGNAL DETECTION RING | NGUYEN, HIEN NGOC | 3797 | §103 | Final Rejection | 33d | Pending | Mar 14, 2024 |
| 18026890 | METHOD AND DEVICE FOR ANALYZING ABNORMAL PHYSIOLOGICAL STATE | JENNESS, NATHAN JAY | 3733 | §101§112 | Non-Final OA | 132d overdue | Pending | Mar 17, 2023 |
| 18026898 | METHOD AND DEVICE FOR ANALYZING BIO-SIGNAL | LEVERETT, MARY CHANG | — | §101§102§103 | Non-Final OA | — | Pending | Mar 17, 2023 |
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