Evidence map›Paper›PMID 40074807›Full record

ArticleScientific reports2025

Adaptive digital twin integration with multilevel inverter control for energy efficient smart rehabilitation systems.

Sara Mahmoudi Rashid, Amir Rikhtehgar Ghiasi

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Sara Mahmoudi RashidFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran. s.mahmoudirashid@tabrizu.ac.ir.
Amir Rikhtehgar GhiasiFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research proposes an innovative framework integrating adaptive Digital Twin (DT) models with Multi-Level Inverter (MLI) control to improve energy efficiency in advanced rehabilitation systems. By utilizing real-time monitoring and adaptive adjustment of power parameters through DT technology, the method achieves precise and dynamic control of devices such as prosthetics and exoskeletons. The incorporation of MLI ensures smooth and efficient power delivery, reducing harmonic distortion and enhancing overall energy utilization. Key outcomes include a 14.05% increase in energy efficiency, an 8.12% decrease in power ripple, and a 24.03% improvement in system response accuracy, enabling real-time optimization tailored to patient-specific rehabilitation needs. Furthermore, the proposed approach lowers operational costs by 7.01% through optimized energy usage and extended system lifespan. These results highlight the potential of this innovative method to advance rehabilitation systems through the integration of adaptive control and real-time digital modeling.

Indexed as

Adaptive digital twinEnergy efficiencyMultilevel inverterPower ripple reductionSmart rehabilitation systems

Identifiers

PMID40074807
PMCPMC11903879

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.