- Forced inclusion
- Yes
- Material coverage
- No completed material-review receipt
- Publication status
- Date not verified
- Matrix status
- Retained in the evidence set; outside the closest-document view
Patentability assessment
The report displays 3 closest retrieved documents. 3 verified documents support the categorical legal conclusions; 0 remain visible only as excluded or context records.
Search provenance: 121 retrieved -> 98 after dedup -> 25 ranked -> 3 closest.
Patentopia Demonstration · sample@patentopia.example · 3 April 2026
Prepared by Christopher Holmgaard · Report ID mock-sample-001
Demonstration record: the claim, documents, evidence excerpts, review identities and decisions on this page are synthetic and show the completed workflow only.
Assessment overview
The record separates novelty, inventive step and claim drafting. Status is shown from traceable evidence and approval receipts; numerical model estimates are not presented as patentability probabilities.
5 of 5 counted features have a recorded relationship across 3 reviewed documents.
The evidence-qualified Art. 56 analysis is available below.
4 drafting directions retained for traceability; the recorded support, professional review and user decisions produced the clean claim shown below.
Search record
The record below distinguishes database scale, retrieved material, the displayed closest-document set and conclusion-bearing reviewed evidence. Exclusions are reported explicitly; user-supplied prior art is retained in the review record.
- 1Database-reported matchesCount unavailable
- 2Retrieved records121
- 3Unique documents after deduplication23 excluded: Duplicate record or patent-family representation98
- 4Ranked candidates73 excluded: Outside the ranked candidate window25
- 5Closest retrieved-document set22 excluded: Outside the approved closest-document set3
- 6Conclusion-bearing reviewed evidence0 excluded: Displayed as excluded or context-only records3
Recorded provenance: 121 retrieved -> 98 after dedup -> 25 ranked -> 3 closest.
- Displayed material sources
- EPO Open Patent Services, Crossref, USPTO, User-supplied prior art
- Displayed material languages
- EN
- Critical date
- 2026-03-01 · User-provided critical date
- Search executed
- 3 April 2026, 10:06 UTC
- Displayed / conclusion-bearing
- 3 / 3
- Unresolved displayed records
- 0
- Every displayed closest document has a conclusion-bearing review receipt.
- Art. 54(3) prior rights are not assessed unless expressly recorded.
- No-disclosure findings are limited to the reviewed material and do not establish absence from unreviewed passages, family members or the wider prior-art universe.
- The listed source languages describe the displayed record and do not prove complete multilingual source coverage.
Current candidate starting point, subject to verification
This document has the strongest verified relationship to the approved feature model and is the current starting point for the separate novelty and inventive-step analyses.
2-A · Real-time Gait Analysis Using Wearable Pressure Sensors
Approved feature model
The claim is represented as patent-relevant technical relationships, not grammatical fragments. Search and legal conclusions use the approved conversion recorded below.
Approved source claim
The complete claim text used for feature traceability and search approval.
A smart adaptive insole system comprising (a) a flexible substrate configured to be inserted into footwear; (b) an array of pressure sensors embedded within the substrate for detecting plantar pressure distribution in real-time; (c) a wireless communication module that transmits pressure data to a mobile device; and (d) a machine learning algorithm running on the mobile device that analyzes gait patterns and generates injury prevention recommendations based on historical pressure data and biomechanical models.
From claim: “an array of pressure sensors embedded within the substrate for detecting plantar pressure distribution in real-time”
Provisional cross-jurisdiction feature estimates. These values are not office-specific legal conclusions and require patent-professional review.
From claim: “a machine learning algorithm running on the mobile device that analyzes gait patterns”
Provisional cross-jurisdiction feature estimates. These values are not office-specific legal conclusions and require patent-professional review.
From claim: “generates injury prevention recommendations based on historical pressure data and biomechanical models”
Provisional cross-jurisdiction feature estimates. These values are not office-specific legal conclusions and require patent-professional review.
From claim: “a wireless communication module that transmits pressure data to a mobile device”
Provisional cross-jurisdiction feature estimates. These values are not office-specific legal conclusions and require patent-professional review.
From claim: “a flexible substrate configured to be inserted into footwear”
Provisional cross-jurisdiction feature estimates. These values are not office-specific legal conclusions and require patent-professional review.
Retrieval validation
| Diagnostic | Expected | Observed | Status |
|---|---|---|---|
| Feature A: A flexible substrate configured to be inserted into footwear | Targeted retrieval and completed material review; positive mappings and explicit non-identifications are reported separately | 3 positive mapped references; remaining reviewed cells explicitly record no identified disclosure | Passed |
| Feature B: An array of pressure sensors embedded within the substrate for detecting plantar pressure distribution in real-time | Targeted retrieval and completed material review; positive mappings and explicit non-identifications are reported separately | 2 positive mapped references; remaining reviewed cells explicitly record no identified disclosure | Passed |
| Feature C: A wireless communication module that transmits pressure data to a mobile device | Targeted retrieval and completed material review; positive mappings and explicit non-identifications are reported separately | 2 positive mapped references; remaining reviewed cells explicitly record no identified disclosure | Passed |
| Feature D: A machine learning algorithm running on the mobile device that analyzes gait patterns | Targeted retrieval and completed material review; positive mappings and explicit non-identifications are reported separately | 1 positive mapped reference; remaining reviewed cells explicitly record no identified disclosure | Passed |
| Feature E: Generates injury prevention recommendations based on historical pressure data and biomechanical models | Targeted retrieval and completed material review; positive mappings and explicit non-identifications are reported separately | 1 positive mapped reference; remaining reviewed cells explicitly record no identified disclosure | Passed |
Disclosure matrix and novelty
Partial feature overlap: 5 of 5 counted claim features appear in 3 documents; no single document discloses all of them. Per-document overlap: 1-P (features A, B and C), 2-A (features A, B, D and E) and 3-A (features A and C). The reviewed scope does not identify a single-document novelty-destroying disclosure under EPC Art. 54; overlap of separate features across different documents is assessed separately under EPC Art. 56.
The strategic matrix uses only patent-relevant technical relationships. Select a cell to inspect the publication, locator, reviewed material, language and verification record. A blank cell is not evidence of absence.
Every recorded claim limitation remains visible. The disclosure summary counts only strategic features; traceability-only wording stays in the matrix without affecting that count.
- AA flexible substrate configured to be inserted into footwearCounted in strategic view
- BAn array of pressure sensors embedded within the substrate for detecting plantar pressure distribution in real-timeCounted in strategic view
- CA wireless communication module that transmits pressure data to a mobile deviceCounted in strategic view
- DA machine learning algorithm running on the mobile device that analyzes gait patternsCounted in strategic view
- EGenerates injury prevention recommendations based on historical pressure data and biomechanical modelsCounted in strategic view
Legal claim-limitation traceability · 5 total limitations
| Prior-art document | Disclosure | A | B | C | D | E |
|---|---|---|---|---|---|---|
| Smart Insole for Plantar Pressure MonitoringEP3284412 | Partly mapped (3 of 5) | |||||
| Real-time Gait Analysis Using Wearable Pressure Sensors2-A | Partly mapped (4 of 5) | |||||
| Wireless Foot Pressure Measurement System for Clinical Use3-A | Partly mapped (2 of 5) |
- FFull
- The evidence record maps the complete feature.
- PPartial
- The evidence record maps only part of the feature.
- IImplicit
- The relationship is recorded as implicit rather than express.
- UUnclear
- The material does not support a settled mapping.
- NINot identified
- No relationship was identified in the reviewed material.
- NANot analysed
- No completed review covers this document-feature pair.
- RImported
- A legacy relationship exists and requires verification.
- NRNo record
- No structured evidence object is recorded.
Select any cell to inspect the evidence record. “Not identified” is limited to the material reviewed; “no record” is not evidence of absence.
Real-time Gait Analysis Using Wearable Pressure SensorsHigh
This document discloses 4 claim features, rated high on the named scale.
“The insole substrate was fabricated from flexible thermoplastic polyurethane.”
“Sixteen FSR sensors were placed at key plantar regions for continuous pressure distribution measurement at 100 Hz.”
“A convolutional neural network was deployed on the smartphone for real-time gait phase classification.”
“Longitudinal pressure features were compared with a generic biomechanical risk model to produce injury-risk guidance.”
Smart Insole for Plantar Pressure MonitoringSubstantial
This document discloses 3 claim features, rated substantial on the named scale.
“A flexible polymeric substrate shaped to conform to the interior of a shoe.”
“An array of piezoresistive pressure sensors distributed across anatomical pressure points for real-time plantar pressure mapping.”
“A Bluetooth Low Energy transceiver module for wireless transmission of sensor data to a paired smartphone application.”
Wireless Foot Pressure Measurement System for Clinical UseLimited
This document discloses 2 claim features, rated limited on the named scale.
“A flexible substrate designed for in-shoe placement.”
“A BLE 5.0 module transmitted pressure data packets to a mobile device at 50 Hz.”
Inventive-step analysis
Inventive step: 1 of 2 assessed features (D) has a located, verified pre-critical obviousness route via 2-A eligible for EPC Art. 56. For the remaining 1 feature, the reviewed routes did not establish that obvious-development conclusion.
Inventive step is organised by document-combination route, not by labelling isolated features obvious or non-obvious.
- Starting point
- 1-P
- Secondary reference
- 2-A
- Shared features
- Feature D
- Distinguishing relationship
- Mobile machine-learning analysis of gait patterns
- Technical effect
- Patient-specific gait analysis across multiple sessions supports more targeted injury-prevention guidance than raw visualization or generic classification.
- Objective technical problem
- How to process collected plantar pressure data to provide actionable injury prevention guidance, rather than raw data visualization or simple gait classification.
- Reason to combine
- 2-A expressly deploys a gait classifier on a smartphone, giving a direct implementation route for this limitation at its present breadth when starting from the separately identified 1-P platform.
- Reason not to combine
- No countervailing rationale was entered; professional review is required.
- Starting point
- 1-P
- Secondary reference
- 2-A
- Shared features
- Feature E
- Distinguishing relationship
- Historical pressure analysis combined with a personalized biomechanical model to generate injury-prevention guidance
- Technical effect
- Patient-specific gait analysis across multiple sessions supports more targeted injury-prevention guidance than raw visualization or generic classification.
- Objective technical problem
- How to process collected plantar pressure data to provide actionable injury prevention guidance, rather than raw data visualization or simple gait classification.
- Reason to combine
- No supported reason to combine was established on the reviewed route.
- Reason not to combine
- 2-A uses a generic risk model, but the reviewed record does not establish a reason to adapt the model continuously to an individual across multiple sessions.
Additional patentability criteria
Industrial applicability and excluded subject matter are assessed independently from novelty and inventive step. A missing result is shown explicitly and is never inferred as favourable.
No persisted Art. 57 result is available. Patent-professional review is required before treating this criterion as satisfied.
No persisted Arts. 52/53 result is available. No favourable eligibility conclusion is inferred from the missing record.
Adversarial review
Substantive claim risks
The following points challenge the technical contribution and claim breadth rather than explaining system limitations.
- A broader or better-targeted search may identify the claimed technical relationship in an earlier publication.
- The distinguishing relationship may be an arbitrary selection or an expected implementation choice.
- The stated technical effect may not be supported across the full breadth of the approved claim.
- A functional limitation may state only a desired result without the technical means that achieve it.
Evidence limitations
- A focused search for adaptive, user-specific biomechanical models could still identify a stronger combination route. The conclusion is limited to the reviewed material and verified dates listed below.
- Feature A is disclosed by "Smart Insole for Plantar Pressure Monitoring" (Art. 54).
- Feature B is disclosed by "Smart Insole for Plantar Pressure Monitoring" (Art. 54).
- Feature C is disclosed by "Smart Insole for Plantar Pressure Monitoring" (Art. 54).
- Feature D is disclosed by "Real-time Gait Analysis Using Wearable Pressure Sensors" (Art. 54).
- Feature E is disclosed by "Real-time Gait Analysis Using Wearable Pressure Sensors" (Art. 54).
- [exposure] Feature A is mapped in all three reviewed closest-art documents and does not add a distinguishing relationship on this record.
- [exposure] Feature D overlaps with the CNN-based gait classifier in 2-A. The claim should be narrowed to distinguish the specific ML approach.
- Verified patent "Smart Insole for Plantar Pressure Monitoring" overlaps feature A: Claim 1; paragraph 22-P
- Verified patent "Smart Insole for Plantar Pressure Monitoring" overlaps feature B: Claim 3; paragraph 25-P
- Verified patent "Smart Insole for Plantar Pressure Monitoring" overlaps feature C: Claim 5; paragraph 28-P
- A challenger would combine the smart-insole platform in 1-P with the smartphone classifier in 2-A and argue that longitudinal risk guidance is an expected analytics objective. The strongest response depends on the verified user-specific adaptation and multi-session relationship.
- Document 2-A shows that machine learning can be applied to gait data. The reviewed record does not establish a reason to adapt its generic model continuously to an individual across multiple sessions.
- The reviewed route treats these as distinguishing relationships requiring professional review: Injury prevention recommendations (not just classification); Historical pressure data analysis over time; Integration of biomechanical models with ML analysis (EPC Art. 56).
Claim amendment workflow
Amendment directions follow from the analysis above. Each direction records the cited document, minimum wording change, support basis, scope effect and novelty or inventive-step effect.
Minimum change
The smallest recorded change that addresses an identified risk.
- a recurrent neural network running on the mobile device that analyzes temporal gait patterns across multiple sessions using a personalized biomechanical model adapted to the individual user's foot morphology
- an array of at least twelve capacitive pressure sensors arranged in anatomically-mapped zones within the substrate for detecting plantar pressure distribution at a sampling rate of at least 100 Hz
Safe expansion
Recorded dependent-claim or breadth directions, subject to explicit support and professional review.
- wherein the biomechanical model is continuously updated based on accumulated user data to refine injury risk predictions over time
Patent-language improvement
Recorded clarity and claim-structure reformulations that do not invent new technical matter.
- a wireless communication module configured to transmit pressure data to a mobile device
- Amend Feature D · Approved for clean claimRationale: Narrowing Feature D to specify the temporal/multi-session aspect and personalized biomechanical model creates distance from 2-A (which uses a generic CNN on single-session data). This is the most impactful amendment because it strengthens the technically distinguishing relationship in the disclosure. Distinguishes from 1-P, 2-A.Minimum verified amendment:
a machine learning algorithm running on the mobile device that analyzes gait patterns→ a recurrent neural network running on the mobile device that analyzes temporal gait patterns across multiple sessions using a personalized biomechanical model adapted to the individual user's foot morphology Basis (paragraph [0042]): “a recurrent neural network running on the mobile device that analyzes temporal gait patterns across multiple sessions using a personalized biomechanical model adapted to the individual user's foot morphology”.Scope effect: Narrows the model architecture, observation period and biomechanical-model relationship.Novelty / inventive-step effect: Specifying multi-session temporal analysis and a personalized biomechanical model distances the claim from 2-A on inventive step; 2-A discloses only single-session CNN gait classification.Disclosure-matrix trace: Feature D × 1-P: not identified; Feature D × 2-A: partial at Section 3.1; page 7Distance verification: Verified by Demo patent professional · 2026-04-03T10:13:00Z. - Amend Feature B · Approved for clean claimRationale: Specifying sensor count, type (capacitive vs piezoresistive in 1-P), anatomical mapping, and sampling rate creates technical distance from both 1-P and 2-A while narrowing to the actual implementation. Distinguishes from 1-P, 2-A.Minimum verified amendment:
an array of pressure sensors embedded within the substrate for detecting plantar pressure distribution in real-time→ an array of at least twelve capacitive pressure sensors arranged in anatomically-mapped zones within the substrate for detecting plantar pressure distribution at a sampling rate of at least 100 Hz Basis (paragraph [0035]): “an array of at least twelve capacitive pressure sensors arranged in anatomically-mapped zones within the substrate for detecting plantar pressure distribution at a sampling rate of at least 100 Hz”.Scope effect: Narrows sensor type, minimum count, placement relationship and sampling rate.Novelty / inventive-step effect: Capacitive sensors in anatomically-mapped zones at ≥100 Hz distance the claim from 1-P on novelty; 1-P discloses generic piezoresistive sensors without a specified sampling rate.Disclosure-matrix trace: Feature B × 1-P: full at Claim 3; paragraph [0024]; Feature B × 2-A: full at Section 2.2; page 4Distance verification: Verified by Demo patent professional · 2026-04-03T10:13:30Z. - Add new feature · RejectedRationale: Adding an adaptive/learning element would narrow Feature E toward a relationship that is not mapped in the retained passages from 1-P, 2-A or 3-A. Professional review is still required before relying on that distance. Distinguishes from 1-P, 2-A, 3-A.Minimum verified amendment: wherein the biomechanical model is continuously updated based on accumulated user data to refine injury risk predictions over time Basis (paragraph [0048]): “the biomechanical model is continuously updated based on accumulated user data to refine injury risk predictions over time”.Scope effect: Narrows the recommendation function to a continuously updated personalised model.Novelty / inventive-step effect: The retained passages from 1-P, 2-A and 3-A do not map continuous, user-specific refinement of injury-risk predictions. This is an evidence-limited distance record, not a broader inventive-step conclusion.Disclosure-matrix trace: Feature E × 1-P: not identified; Feature E × 2-A: partial at Section 4.2; page 10; Feature E × 3-A: not identifiedDistance verification: Verified by Demo patent professional · 2026-04-03T10:13:45Z.
- Amend Feature C · RejectedRationale: Uses conventional functional claim syntax while preserving the same module, data and destination relationship.Minimum verified amendment:
a wireless communication module that transmits pressure data to a mobile device→ a wireless communication module configured to transmit pressure data to a mobile device Basis (claim 1): “a wireless communication module that transmits pressure data to a mobile device”.Scope effect: No scope change is intended.Novelty / inventive-step effect: This is a non-substantive drafting reformulation, not a prior-art distinction.Disclosure-matrix trace: Not applicable; this is a support-verified drafting-form change and asserts no prior-art distance.Distance verification: Not applicable; substantive technical tokens and intended scope are unchanged.
A smart adaptive insole system comprising (a) a flexible substrate configured to be inserted into footwear; (b) an array of at least twelve capacitive pressure sensors arranged in anatomically-mapped zones within the substrate for detecting plantar pressure distribution at a sampling rate of at least 100 Hz; (c) a wireless communication module that transmits pressure data to a mobile device; (d) a recurrent neural network running on the mobile device that analyzes temporal gait patterns across multiple sessions using a personalized biomechanical model adapted to the individual user's foot morphology; and (e) generates injury prevention recommendations based on historical pressure data and biomechanical models, wherein the biomechanical model is continuously updated based on accumulated user data to refine injury risk predictions over time.
A smart adaptive insole system comprising (a) a flexible substrate configured to be inserted into footwear; (b) an array of at least twelve capacitive pressure sensors arranged in anatomically-mapped zones within the substrate for detecting plantar pressure distribution at a sampling rate of at least 100 Hz; (c) a wireless communication module that transmits pressure data to a mobile device; and (d) a recurrent neural network running on the mobile device that analyzes temporal gait patterns across multiple sessions using a personalized biomechanical model adapted to the individual user's foot morphology and generates injury prevention recommendations based on historical pressure data and biomechanical models.
- Source claim3 April 2026, 10:00 UTC
- Strategy generated3 April 2026, 10:12 UTC
- Review record2 amendment decisions recorded · 3 April 2026, 10:15 UTC
Optional assessment terminology
Patentopia · patentability assessment · 3 April 2026
Evidence, source and approval status are drawn from the stored assessment record.