Evidence map›Paper›PMID 42437284›Full record

ReviewJournal of orthopaedic translation2026

From episodic imaging to real-time sensor monitoring: translational advances in assessing fracture healing dynamics.

Fawwaz Al-Smadi, Ze Lin, Na Li, Jiewen Liao, Sajeda Al-Smadi, Xiayidan Abudourusuli, Xudong Xie, Chenyan Yu, Yiming Li, Mengfei Liu and 2 more

Abstract readReview
In one paragraph

Review in Journal of orthopaedic translation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Fawwaz Al-SmadiDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Ze LinDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Na LiSchool of Integrated Circuits and Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, People's Republic of China.
Jiewen LiaoDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Sajeda Al-SmadiPediatric Health Nursing, Department of Allied Medical Sciences, Zarqa University College, Al-Balqa Applied University, P.O. Box: 313, Zarqa, 13110, Jordan.
Xiayidan AbudourusuliDepartment of Public Administration, College of Public Health, Xinjiang Medical University, Urumqi, Xinjiang, 830011, People's Republic of China.
Xudong XieDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Chenyan YuDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Yiming LiDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Mengfei LiuDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Bobin MiDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Guohui LiuDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fracture healing culminates in restoration of mechanical competence, yet clinical monitoring remains largely dependent on episodic imaging and subjective assessment, which provide delayed structural information and limited insight into the evolving stability of the fracture construct, contributing to uncertainty in clinical decision-making and delayed recognition of impaired healing. Advances in bioelectronics, implantable sensors, and wearable systems are enabling longitudinal assessment of fracture recovery by capturing quantitative signals related to mechanical load transfer, local tissue state, and functional activity in real-world settings. In this review, we synthesize recent developments in sensor-based fracture monitoring and propose a conceptual framework that integrates three complementary dimensions of healing assessment: mechanical competence, biological progression, and functional recovery. Among these, load-path sensing of implant-bone load transfer provides the most direct proxy for fracture stiffness and currently represents the most translationally mature approach, supported by emerging preclinical and early clinical studies. In contrast, biological sensing strategies, including impedance- and dielectric-based approaches, aim to detect earlier changes in callus composition but remain at lower levels of translational readiness, while wearable monitoring technologies offer scalable insights into rehabilitation trajectories but provide indirect measures of fracture stability. Collectively, these approaches support a transition from episodic structural imaging toward continuous, data-driven characterization of healing dynamics. Achieving clinical implementation will require workflow-integrated sensing systems, interpretable analytical frameworks linking sensor outputs to clinically actionable endpoints, and multicentre validation establishing standardized thresholds across fracture types and treatment strategies. The translational potential of this article: Current literature on fracture healing monitoring is largely technology-centric, with limited integration of sensing outputs into clinically actionable frameworks. This review addresses that gap by providing a unified, decision-oriented synthesis that links mechanical, biological, and functional sensing paradigms to the core clinical endpoint of fracture healing, restoration of mechanical competence, and to key management decisions such as weight-bearing progression, follow-up intensity, and early detection of delayed union. By contextualizing existing technologies within a translational maturity (TRL) framework and evaluating evidence from benchtop, preclinical, and early human studies, this work identifies which sensing strategies are closest to clinical implementation and what barriers remain, including the need for standardized protocols, validated decision thresholds, workflow integration, and scalable data interpretation. The translational value of this review lies in defining how continuous, quantitative monitoring can complement or partially replace episodic imaging, enabling earlier, more objective, and individualized fracture care, while providing a roadmap for the development, validation, and clinical adoption of sensor-enabled, data-driven orthopaedic management systems.

Indexed as

Electrical impedance sensingFracture healing monitoringImplant-integrated sensorsLoad transfer mechanicsSmart orthopaedic devicesWearable sensing

Identifiers

PMID42437284
PMCPMC13355026

What OpenQuestion 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 OpenQuestion graph.