CogCBR: A Complete Case-Based Reasoning Framework for Wearable-Sensor-Based Gait Screening of Neurodegenerative Diseases.

Huayue Liu, Yujia Sun, Lihua Luo, Xingeng Li, Huanghe Zhang

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Huayue LiuThe Center for Robotics, School of Control Science and Engineering, Shandong University, Jinan 250100, China.ORCID 0009-0008-9900-6256

Yujia SunSchool of Qilu Transportation, Shandong University, Jinan 250100, China.

Lihua LuoThe Center for Robotics, School of Control Science and Engineering, Shandong University, Jinan 250100, China.

Xingeng LiThe Center for Robotics, School of Control Science and Engineering, Shandong University, Jinan 250100, China.ORCID 0009-0008-3382-4475

Huanghe ZhangThe Center for Robotics, School of Control Science and Engineering, Shandong University, Jinan 250100, China.ORCID 0000-0003-2770-8335

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable force-sensitive insoles enable quantitative gait analysis as a screening aid for neurodegenerative diseases (NDDs), yet prevailing machine learning pipelines give point predictions with no per-case reliability estimate, no intrinsic explanation, and no way to curate their own knowledge base. Case-Based Reasoning (CBR) mirrors clinical reasoning, but deployed healthcare CBR systems typically implement only partial R

Indexed as

GaitNeurodegenerative DiseasesWearable Electronic DevicesHumansMachine Learningcase-based reasoningcase-base maintenanceclinical decision supportconfidence estimationedge deployabilityforce-sensitive insolesgait analysisknowledge containersneurodegenerative diseaseParkinson’s diseasewearable sensors

Identifiers

PMID42451400

DOI10.3390/s26134158

PMCPMC13363778

What Socratic holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.