Journal article
Mechanical Imaging of Soft Tissues With a Highly Compliant Tactile Sensing Array
IEEE transactions on biomedical engineering, v 65(3), pp 687-697
Mar 2018
PMID: 28622664
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Objective: The mechanical imaging of lumps in tissues via surface measurements can permit the noninvasive detection of disease-related differences in body tissues. We present and evaluate sensing techniques for the mechanical imaging of soft tissues, using a highly compliant electronic sensing array. Methods : We developed a mechanical imaging system for capturing tissue properties during automatic- or human-guided palpation. It combines extremely compliant capacitive tactile sensors based on soft polymers and microfluidic electrodes with custom electronic data acquisition hardware, and new algorithms for enhanced tactile imaging by reference to nominal tissue responses. Results: We demonstrate that the system is able to image simulated tumors (lumps), yielding accurate estimates of cross-sectional area independent of embedding depth. In addition, as a proof of concept, we show that similar tactile images can be obtained when the sensor is worn on a palpating finger. Conclusion: Soft capacitive sensors can accurately image lumps in soft tissue provided that care is taken to control and compensate for electrical and mechanical background signals. Significance: The results underline the utility of soft electronic sensors for applications in medical imaging or clinical practices of palpation.
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Details
- Title
- Mechanical Imaging of Soft Tissues With a Highly Compliant Tactile Sensing Array
- Creators
- Bin Li - Department of Electrical and Computer EngineeringDrexel UniversityYe Shi - Department of Electrical and Computer EngineeringDrexel UniversityAdam Fontecchio - Department of Electrical and Computer EngineeringDrexel UniversityYon Visell - California NanoSystems Institute
- Publication Details
- IEEE transactions on biomedical engineering, v 65(3), pp 687-697
- Publisher
- IEEE
- Grant note
- 1623459; 1628831 / National Science Foundation
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000425664500022
- Scopus ID
- 2-s2.0-85021836367
- Other Identifier
- 991019168309804721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Engineering, Biomedical