Freezing of Gait Turn Narrow Trigger Checker
Observed freezing-of-gait context inventory, not diagnose Parkinsonsdisease or predict a fall. Actual independently established feature columns: independently reported freezing during turning, independently reported freezing in narrow passage, event history independently reviewed. Unknown and overlapping candidates retained, not automatic diagnosis, causation, predicted performance or safety approval.
Description
Freezing-of-gait observations can be recorded in turning or narrow-space contexts.
Freezing-of-gait observations can be recorded in turning or narrow-space contexts.1
An evidence comparison does not diagnose freezing or establish the cause of an episode. Use this tool to compare independently annotated known features with fixed candidate rules.
When to use Freezing of Gait Turn Narrow Trigger Checker
Use this tool to compare independently annotated known features with fixed candidate rules. Establish the measurement protocol, instrument or reference edition, matching units and observation context.
How to use Freezing of Gait Turn Narrow Trigger Checker and understand its results
- Establish the measurement protocol, instrument or reference edition, matching units and observation context.
- Enter independentlyObservedFeatureFlags, featureKnownFlags, using the field meanings and rules below, then run the tool.
- Read result.compatibleClasses, result.witnessedClasses, result.unknownFeatureIndices. Interpret each field using the units, signs and evidence rules below.
- If input validation fails, correct the reported field and run again. Before applying a successful result, check the stated reference scope, units, assumptions and any retained unknown evidence.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| independentlyObservedFeatureFlags | Independently observed feature flags; binary 0/1 in the order documented below | list of number | Required |
| featureKnownFlags | Feature known flags; 1 means known and 0 means unknown; keep the same item order | list of number | Required |
Enter binary observed and known flags in the fixed feature-column order below. A known disagreement with a constrained rule excludes a class; an unknown constrained feature leaves it compatible but not fully witnessed. Ignored features never block witnessing. Return all compatible and witnessed classes and zero-based unknown feature indices. This records supplied observations without establishing a clinical cause or diagnosis.
| Zero-based column | Observed feature |
|---|---|
| 0 | Independently reported freezing during turning |
| 1 | Independently reported freezing in narrow passage |
| 2 | Event history independently reviewed |
| Candidate | Independently reported freezing during turning | Independently reported freezing in narrow passage | Event history independently reviewed |
|---|---|---|---|
| turn-context-observed | Known present (1) | Ignored | Known present (1) |
| narrow-context-observed | Ignored | Known present (1) | Known present (1) |
compatible_c=no known constrained mismatch; witnessed_c=compatible_c and every constrained feature known Apply the field units and exact ordering, boundary and evidence rules above.
| Output field | Meaning | Value type |
|---|---|---|
| result | Structured result containing the calculation or selected reference fields below | object |
| result.compatibleClasses | All candidates consistent with known features; may include candidates with missing evidence | list of string |
| result.witnessedClasses | Candidates with all required feature constraints actually known and satisfied | list of string |
| result.unknownFeatureIndices | Zero-based positions of unknown features | list of values |
{
"input": {
"independentlyObservedFeatureFlags": [
1,
1,
1
],
"featureKnownFlags": [
1,
1,
1
]
},
"output": {
"result": {
"compatibleClasses": [
"turn-context-observed",
"narrow-context-observed"
],
"witnessedClasses": [
"turn-context-observed",
"narrow-context-observed"
],
"unknownFeatureIndices": []
}
}
}Limitations and assumptions
Feature and criterion flags are independent annotations. Unknown evidence remains unknown; matching rules do not establish a diagnosis, cause, prediction or approval.
Every listed input requires an explicit value. Unexpected fields, incorrect value types, nonfinite numbers and sparse numeric arrays fail validation; tool-specific bounds and alignment rules apply as described above. Extremely large inputs or outputs can also be rejected. An input error is distinct from a successful calculation that reports a false comparison or retains unknown evidence.
Alternative or Complementary methods
Use Trendelenburg Sign Abductor Weakness Positive Checker to examine a related aspect: A Trendelenburg-sign observation requires independently established stance and pelvic-movement evidence.
Use Overhead Squat Compensations Feet Flat Knee Valgus Lookup where its separate inputs and scope apply: Overhead-squat observations reflect task, anatomy and movement strategy.
References
Similar or alternative tools
- Trendelenburg Sign Abductor Weakness Positive Checker
A Trendelenburg-sign observation requires independently established stance and pelvic-movement evidence.
- Overhead Squat Compensations Feet Flat Knee Valgus Lookup
Overhead-squat observations reflect task, anatomy and movement strategy.