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Aggas JR, Abasi S, Ton C, Salehi S, Liu R, Brandacher G, Grayson WL, Guiseppi-Elie A. Real-Time Monitoring Using Multiplexed Multi-Electrode Bioelectrical Impedance Spectroscopy for the Stratification of Vascularized Composite Allografts: A Perspective on Predictive Analytics. Bioengineering (Basel) 2023; 10:bioengineering10040434. [PMID: 37106621 PMCID: PMC10135882 DOI: 10.3390/bioengineering10040434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 03/20/2023] [Accepted: 03/24/2023] [Indexed: 04/29/2023] Open
Abstract
Vascularized composite allotransplantation addresses injuries to complex anatomical structures such as the face, hand, and abdominal wall. Prolonged static cold storage of vascularized composite allografts (VCA) incurs damage and imposes transportation limits to their viability and availability. Tissue ischemia, the major clinical indication, is strongly correlated with negative transplantation outcomes. Machine perfusion and normothermia can extend preservation times. This perspective introduces multiplexed multi-electrode bioimpedance spectroscopy (MMBIS), an established bioanalytical method to quantify the interaction of the electrical current with tissue components, capable of measuring tissue edema, as a quantitative, noninvasive, real-time, continuous monitoring technique to provide crucially needed assessment of graft preservation efficacy and viability. MMBIS must be developed, and appropriate models explored to address the highly complex multi-tissue structures and time-temperature changes of VCA. Combined with artificial intelligence (AI), MMBIS can serve to stratify allografts for improvement in transplantation outcomes.
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Affiliation(s)
- John R Aggas
- Bioelectronics, Biosensors and Biochips (C3B®), Department of Biomedical Engineering, Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA
- Test Development, Roche Diagnostics, 9115 Hague Road, Indianapolis, IN 46256, USA
| | - Sara Abasi
- Bioelectronics, Biosensors and Biochips (C3B®), Department of Biomedical Engineering, Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA
- Media and Metabolism, Wildtype, Inc., 2325 3rd St., San Francisco, CA 94107, USA
| | - Carolyn Ton
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21231, USA
- Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, MD 21231, USA
| | - Sara Salehi
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21231, USA
- Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, MD 21231, USA
| | - Renee Liu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21231, USA
- Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, MD 21231, USA
| | - Gerald Brandacher
- Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, MD 21231, USA
- Department of Plastic & Reconstructive Surgery, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Warren L Grayson
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21231, USA
- Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, MD 21231, USA
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Institute for Nanobiotechnology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Anthony Guiseppi-Elie
- Bioelectronics, Biosensors and Biochips (C3B®), Department of Biomedical Engineering, Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA
- Department of Cardiovascular Sciences, Houston Methodist Institute for Academic Medicine and Houston Methodist Research Institute, 6670 Bertner Ave., Houston, TX 77030, USA
- ABTECH Scientific, Inc., Biotechnology Research Park, 800 East Leigh Street, Richmond, VA 23219, USA
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Zhou Z, Wang X, Yang Y, Zeng J, Liu H. Mathematical Model of Fingertip Skin Under Constant-Current Electrotactile Stimulation. IEEE TRANSACTIONS ON HAPTICS 2022; PP:3-12. [PMID: 37015514 DOI: 10.1109/toh.2022.3227084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Due to low energy consumption and fast response, electrotactile feedback has shown great potential in human-machine interaction. However, regulating electrotactile perception remains challenging because of the high variability of electrode-skin impedance. Electrode-skin modelling is a common solution, but current researches are still facing many problems such as non-linearity. This paper focuses on voltage response modelling based on data-driven analysis. Two experiments targeting fingertips have been conducted. Significant correlations between pulse amplitude ( PA), pulse width ( PW) and peak voltage ( Vpeak) ( 0.99) have been found. A mathematical model of fingertip skin is then derived, which enables a precision fitting of the voltage response (RMSE=0.9 %). Finally, two calibration methods are proposed for peak voltage prediction. The accuracy (RMSE=2.5 %) is also verified under different electrode-skin conditions. The results of this paper are expected to provide novel theoretical support for precise regulation of fingertip electrotactile perception.
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Zhou Z, Yang Y, Liu J, Zeng J, Wang X, Liu H. Electrotactile Perception Properties and Its Applications: A Review. IEEE TRANSACTIONS ON HAPTICS 2022; 15:464-478. [PMID: 35476571 DOI: 10.1109/toh.2022.3170723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
With the increased demands of human-machine interaction, haptic feedback is becoming increasingly critical. However, the high cost, large size and low efficiency of current haptic systems severely hinder further development. As a portable and efficient technology, cutaneous electrotactile stimulation has shown promising potential for these issues. This paper presents a review on and insight into cutaneous electrotactile perception and its applications. Research results on perceptual properties and evaluation methods have been summarized and discussed to understand the effects of electrotactile stimulation on humans. Electrotactile applications are presented in categories to understand the methods and progress in various fields such as prostheses control, sensory substitution, sensory restoration and sensorimotor restoration. State of the art has demonstrated the superiority of electrotactile feedback, its efficiency and its flexibility. However, the complex factors and the limitations of evaluation methods made it challenging for precise electrotactile control. Groundbreaking innovation in electrotactile theory is expected to overcome challenges such as precise perception control, information capacity increasing, comprehension burden reducing and implementation costs.
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Jiang B, Kim J, Park H. Palatal Electrotactile Display Outperforms Visual Display in Tongue Motor learning. IEEE Trans Neural Syst Rehabil Eng 2022; 30:529-539. [PMID: 35245197 DOI: 10.1109/tnsre.2022.3156398] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Incomplete tongue motor control is a common yet challenging issue among individuals with neurotraumas and neurological disorders. In development of the training protocols, multiple sensory modalities including visual, auditory, and tactile feedback have been employed. However, the effectiveness of each sensory modality in tongue motor learning is still in question. The object of this study was to test the effectiveness of visual and electrotactile assistance on tongue motor learning, respectively. Eight healthy subjects performed the tongue pointing task, in which they were visually instructed to touch the target on the palate by their tongue tip as accurately as possible. Each subject wore a custom-made dental retainer with 12 electrodes distributed over the palatal area. For visual training, 3×4 LED array on the computer screen, corresponding to the electrode layout, was turned on with different colors according to the tongue contact. For electrotactile training, electrical stimulation was applied to the tongue with frequencies depending on the distance between the tongue contact and the target, along with a small protrusion on the retainer as an indicator of the target. One baseline session, one training session, and three post-training sessions were conducted over four-day duration. Experimental result showed that the error was decreased after both visual and electrotactile trainings, from 3.56±0.11 (Mean±STE) to 1.27±0.16, and from 3.97±0.11 to 0.53±0.19, respectively. The result also showed that electrotactile training leads to stronger retention than visual training, as the improvement was retained as 62.68±1.81% after electrotactile training and 36.59±2.24% after visual training, at 3-day post training.
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