Evidence map›Paper›PMID 42345675›Full record

ArticleBiomimetics (Basel, Switzerland)2026

Strategic Management of Design and Conceptualization Factors for Wearable Postural Rehabilitation Devices: A Causal Interdependency Analysis.

Anghel Constantin, Cristian Radu Badea, Roxana-Mariana Nechita, Corina-Ionela Dumitrescu, Bogdan Marian Verdete, Florentina Badea, Sorin Ionuț Badea

Abstract read
In one paragraph

Article in Biomimetics (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

7 authors.

Anghel ConstantinDepartment of Mechatronics and Smart Measurement, National Institute of Research and Development in Mechatronics and Measurement Technique, 021631 Bucharest, Romania.
Cristian Radu BadeaDepartment of Mechatronics and Smart Measurement, National Institute of Research and Development in Mechatronics and Measurement Technique, 021631 Bucharest, Romania.
Roxana-Mariana NechitaDepartment of Entrepreneurship and Management, Faculty of Entrepreneurship, Business Engineering and Management, National University of Science and Technology POLITEHNICA Bucharest, 060042 Bucharest, Romania.ORCID 0009-0004-7556-5572
Corina-Ionela DumitrescuDepartment of Economics, Faculty of Entrepreneurship Business Engineering and Management, National University of Science and Technology POLITEHNICA Bucharest, 060042 Bucharest, Romania.ORCID 0000-0003-3717-7590
Bogdan Marian VerdeteDepartment of Machine and Production Systems, Faculty of Industrial Engineering and Robotics, National University of Science and Technology POLITEHNICA Bucharest, 060042 Bucharest, Romania.ORCID 0009-0001-1856-9786
Florentina BadeaDepartment of Strategic Marketing, National Institute of Research and Development in Mechatronics and Measurement Technique, 021631 Bucharest, Romania.ORCID 0000-0001-8910-6060
Sorin Ionuț BadeaDepartment of Mechatronics and Smart Measurement, National Institute of Research and Development in Mechatronics and Measurement Technique, 021631 Bucharest, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The implementation of wearable systems in postural rehabilitation offers new perspectives for continuous monitoring, yet their success depends on the interaction between technical parameters and clinical requirements. This study analyzes clinical performance factors to identify strategic levers determining recovery effectiveness. It examines indicators such as postural deviation detection, sensitivity to minor motion changes, suitability for home monitoring, continuous monitoring capability, clinical relevance of extracted parameters, and the capability to assess patient progress over time. Using the DEMATEL methodology, the study highlights influences among these factors in a clinical context. This structural analysis separates primary drivers from rehabilitation outcomes. To refine the analysis, the MICMAC method classifies factors by driving and dependence power, distinguishing determinant, relay, dependent, and autonomous variables. The approach provides an objective basis for managers and designers to prioritize resources toward functionalities with the greatest systemic impact on patient progress. The combined DEMATEL-MICMAC framework enhances decision-making by linking causal relationships with clear hierarchical categorization. The findings may support the integration of wearable technologies into rehabilitation practice by identifying the clinical performance factors with the strongest influence within the system.

Indexed as

DEMATELpostural rehabilitationrehabilitationwearable sensors

Identifiers

PMID42345675
PMCPMC13297155

What Socratic holds

Textmetadata
LicenceCC BY
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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.