Flexible and Wearable Ultrasound Device for Medical Applications: A Review on Materials, Structural Designs, and Current Challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Flexible and miniaturized devices inspired by the advances in electronic materials, fabrication technologies, and wireless communication have emerged as the next‐generation smart devices for medicine and healthcare. One of the most promising applications is the flexible devices and systems for medical ultrasound imaging such as ultrasound transducers. Herein, the recent progress in flexible and wearable devices for medical ultrasound imaging is broadly reviewed, focusing on technologies and potential applications in diagnosis and medical care. First, the progressive prospect of wearable devices is briefed, followed by an introduction of the state‐of‐art advances in material development and fabrication technologies. Second, the emerging technologies of flexible, thin‐film ultrasound transducers is focused in comparison to conventional rigid ultrasound devices. Third, this review highlights recent biomedical applications of the flexible ultrasound transducer. Last but not the least, current challenges and future developments are also discussed from the perspectives of medical ultrasound imaging. The flexible ultrasound transducers with capabilities of mass‐fabrication, versatile integration, and on‐skin conformability can add unprecedented abilities such as medical imaging and diagnosis to the flexible, skin‐wearable devices that are promising to improve the quality of personalized care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it