Smart Stretchable Electronics for Advanced Human–Machine Interface

Kim, Kyun Kyu; Suh, Young-Sang; Ko, Seung Hwan

doi:10.1002/aisy.202000157

Cited by 38 publications

(28 citation statements)

References 107 publications

(310 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…noninvasive on-skin electrodes are developed for continuous data collections of electrophysiological signals such as electroencephalogram (EEG)/electrocorticography (ECoG) of the central nerve system, action potentials of the peripheral nerve system, electrocardiogram (ECG), electromyogram (EMG), and electrooculogram (EOG). [9,[99][100][101] From the point-of-view of materials, advances of flexible/stretchable, conformal, self-adhesive, and air-permeable electrodes to tackle the biodevice interfacing issues have been witnessed in the past five years. These material improvements could further facilitate high-quality data collection from stable and reliable signals.…”

Section: Model Type Applicationsmentioning

confidence: 99%

“…

Advances in new materials and soft and stretchable circuits have given rise to the interests in wearable sensing electronic systems (WSESs) for a broad range of applications, including health monitoring, disease diagnosis, personalized healthcare, on-demand treatment, assistive device, human-machine interface (HMI), and virtual and augmented reality. [1][2][3][4][5][6][7][8][9][10][11] Generally, a WSES consists of several heterogenous components: the sensor unit, power unit, wireless communication unit, data collection/storage/ transmission unit, and data processing unit. [12][13][14][15][16] Each of these components is essential to be intelligent and smart, thus enabling the potential large-scale use of WSES.

…”

mentioning

confidence: 99%

See 1 more Smart Citation

Augmenting Sensor Performance with Machine Learning Towards Smart Wearable Sensing Electronic Systems

Zhang

Suresh

Yang

et al. 2022

Advanced Intelligent Systems

View full text Add to dashboard Cite

Wearable sensing electronic systems (WSES) are becoming a fundamental platform to construct smart and intelligent networks for broad applications. Various physiological data are readily collected by the WSES, including biochemical, biopotential, and biophysical signals from human bodies. However, understanding these sensing data, such as feature extractions, recognitions, and classifications, is largely restrained because of the insufficient capacity when using conventional data processing techniques. Recent advances in sensing performance and system‐level operation quality of the WSES are expedited with the assistance of machine learning (ML) algorithms. Here, the state‐of‐the‐art of the ML‐assisted WSES is summarized with emphasis on how the accurate perceptions on physiological signals under different algorithms paradigm augment the performance of the WSES for diverse applications. Concretely, ML algorithms that are frequently implemented in the WSES studies are first synopsized. Then broad applications of ML‐assisted WSES with strengthened functions are discussed in the following sections, including intelligent physiological signals monitoring, disease diagnosis, on‐demand treatments, assistive devices, human–machine interface, and multiple sensations‐based virtual and augmented reality. Finally, challenges confronted for the ML‐assisted WSES are addressed.

show abstract

Section: Model Type Applicationsmentioning

confidence: 99%

“…

…”

mentioning

confidence: 99%

Augmenting Sensor Performance with Machine Learning Towards Smart Wearable Sensing Electronic Systems

Zhang

Suresh

Yang

et al. 2022

Advanced Intelligent Systems

View full text Add to dashboard Cite

show abstract

“…The increasing demand for wearable devices and epidermis‐interfaced electronics has led to continuous and extensive research in these fields. [ 28,65,66,126–128 ] Recent studies have focused on implantation in the subdermis, where electrical stimulation or energy harvesting is possible. In the case of bioelectronic applications, pressure sensors have been actively studied because the repetitively moving human body provides a suitable environment for utilizing the piezoelectric effect, which is an energy‐harvesting phenomenon that generates electricity from induced dielectric polarization.…”

Section: Tissue‐scale Bioelectronics For In Vivo Implantationmentioning

confidence: 99%

“…[ 55,60–64 ] In addition, biocompatibility has been achieved by minimizing the elastic modulus mismatch between soft tissue and electrospun polymer nanofiber‐based devices. [ 65 ] Mechanical mismatch means elastic modulus difference between soft tissue and implanted materials. Implanted devices that have high elastic modulus can experience the acute and chronic immune response with fibrotic encapsulation induced by microglial cells and astrocyte cells.…”

Section: Introductionmentioning

confidence: 99%

Recent Advances in 1D Nanomaterial‐Based Bioelectronics for Healthcare Applications

Song

Kim

Lee

et al. 2021

Advanced NanoBiomed Research

Self Cite

View full text Add to dashboard Cite

Figure 1. Schematic illustration of various bioelectronic devices based on 1D nanomaterials including nanowire, nanotube, and nanofiber. a) Nanowire, nanotube, and nanofiber are the representative 1D nanomaterials. b) Cellular scale bioelectronics based on 1D nanomaterials for cell signal recording and stimulation. Nanowire array to monitor signal of cell: Reproduced with permission. [93] Copyright 2017, American Chemical Society. 3D nanowire FET scaffold to record and stimulate cultured cells: Reproduced with permission. [102] Copyright 2016, Springer Nature. c) Tissue scale bioelectronics based on 1D nanomaterials for signal recording and therapeutic functions. Nanofiber-based cuff electrode for neuroprosthetics: Reproduced with permission. [116]

show abstract

“…Strain sensors, as a signal transducer, can convert external mechanical stimuli into electrical signals. In particular, the stretchable strain sensor is a key part of wearable electronics that can be widely used in applications such as human health monitoring [ 1 , 2 , 3 ], artificial muscle [ 4 , 5 ], soft robot skin [ 6 , 7 ], and human–machine interfaces [ 8 , 9 ]. Among the electrical-signal-based strain sensors, resistive-type strain sensors consisting of stretchable elastomer substrate and conductive active materials have been extensively investigated [ 1 , 10 , 11 ], with advantages such as easy-to-setup and high gauge factor (GF).…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable, Stretchable Strain Sensor with the Localized Controlling of Substrate Modulus by Two-Phase Liquid Metal Cells

et al. 2022

View full text Add to dashboard Cite

Strain modulation based on the heterogeneous design of soft substrates is an effective method to improve the sensitivity of stretchable resistive strain sensors. In this study, a novel design for reconfigurable strain modulation in the soft substrate with two-phase liquid cells is proposed. The modulatory strain distribution induced by the reversible phase transition of the liquid metal provides reconfigurable strain sensing capabilities with multiple combinations of operating range and sensitivity. The effectiveness of our strategy is validated by theoretical simulations and experiments on a hybrid carbonous film-based resistive strain sensor. The strain sensor can be gradually switched between a highly sensitive one and a wide-range one by selectively controlling the phases of liquid metal in the cell array with a external heating source. The relative change of sensitivity and operating range reaches a maximum of 59% and 44%, respectively. This reversible heterogeneous design shows great potential to facilitate the fabrication of strain sensors and might play a promising role in the future applications of stretchable strain sensors.

show abstract

Smart Stretchable Electronics for Advanced Human–Machine Interface

Cited by 38 publications

References 107 publications

Augmenting Sensor Performance with Machine Learning Towards Smart Wearable Sensing Electronic Systems

Augmenting Sensor Performance with Machine Learning Towards Smart Wearable Sensing Electronic Systems

Recent Advances in 1D Nanomaterial‐Based Bioelectronics for Healthcare Applications

Reconfigurable, Stretchable Strain Sensor with the Localized Controlling of Substrate Modulus by Two-Phase Liquid Metal Cells

Contact Info

Product

Resources

About