Development of Smart Textile Systems for Electrophysiological Monitoring
Bibliographic record
Abstract
Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Assessments of cardiac electrical signals, such as variations in cardiac rhythm or abnormalities in wave form, allow for diagnoses of cardiac disease states. Conventionally, the cardiac electrical signals are acquired using gel electrodes, part of electrocardiogram (ECG) assessment. Gel electrodes have limitations for long-term use due to durability issues and possible skin irritations. This presents a need for an alternative to gel electrodes that addresses the limitations for long-term ECG measurements such as a holter system, while providing comparable clinical applicability and accuracy.Throughout human history, textiles have been a ubiquitous technology. Their pervasive nature makes them a promising medium as a replacement for gel electrodes. This can be achieved through the introduction of materials that can capture electrical signals from the body. These materials can be introduced through techniques of lamination on textiles or as a fiber/yarn in the textile production process. In this thesis a variety of materials from the literature were selected and deployed using textile lamination and knitting, to create textile-based electrodes for electrophysiological signal acquisition. The textile-based electrodes were electrically characterized and compared to gel electrodes. The textile electrodes were further classified for their performance in the acquisition of electrophysiological signals, such as electrocardiogram (ECG) and electromyogram (EMG). In the subsequent phase of this thesis textile form factors were designed and developed, that incorporated the textile-based electrodes best suited for ECG and EMG acquisition. The form factors were selected for use cases in, a) ECG: continuous monitoring through an underwear form factor for CVD, and b) EMG: continuous monitoring through a sleeve form factor for prosthetic control. Successful demonstrations are presented of the developed textile form factors, and the custom algorithms needed for the analysis of acquired electrophysiological signals from the textile-based electrodes. In conclusion, a framework for the design, development, testing and validation of textile based electrophysiological systems is presented. These guidelines and best practices should pave the way for future developments in this field.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".