A portable triboelectric spirometer for wireless pulmonary function monitoring

Xu, Qiu; Fang, Yunsheng; Jing, Qingshen; Hu, Ning; Lin, Ke; Pan, Yifan; Xu, Lin; Gao, Haiqi; Yuan, Mengwei; Chu, Liang; Ma, Yanwen; Xie, Yannan; Chen, Jun; Wang, Lianhui

doi:10.1016/j.bios.2021.113329

Cited by 107 publications

(64 citation statements)

References 54 publications

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“…[7][8][9][10][11][12][13][14][15][16] TENG can convert mechanical motion into electrical signals, allowing it to function as a self-powered sensor. [17][18][19][20] However, the data generated by TENGs present challenges for analysis, including large volume, high noise and poor continuity. Attempts to process TENG data using traditional analysis methods have met with long operation cycles and low efficiency.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Sound Monitoring and Identification System Combining Triboelectric Nanogenerator‐Based Self‐Powered Sensor with Deep Learning Technique

Yao

Wang

et al. 2022

Adv Funct Materials

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Urban sound management is required in a variety of fields such as transportation, security, water conservancy and construction, among others. Given the diverse array of available noise sensors and the widespread opportunity to connect these sensors via mobile broadband Internet access, many researchers are eager to apply sound-sensor networks for urban sound management. Existing sensing networks typically consist of expensive information-sensing devices, the cost and maintenance of which limit their large-scale, ubiquitous deployment, thus narrowing their functional measurement range. Herein, an innovative, low-cost, sound-driven triboelectric nanogenerator (SDTENG)-based self-powered sensor is proposed, from which the SDTENG is primarily comprised of fluorinated ethylene propylene membranes, conductive fabrics, acrylic shells, and Kapton spacers. The SDTENG-based sensor has been integrated with a deep learning technique in the present study to construct an intelligent sound monitoring and identification system, which is capable of recognizing a suite of common road and traffic sounds with high classification accuracies of 99% in most cases. The novel SDTENG-based self-powered sensor combined with deep learning technique demonstrates a tremendous application potential in urban sound management, which will show the excellent application prospects in the field of ubiquitous sensor networks.

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Section: Introductionmentioning

confidence: 99%

Intelligent Sound Monitoring and Identification System Combining Triboelectric Nanogenerator‐Based Self‐Powered Sensor with Deep Learning Technique

Yao

Wang

et al. 2022

Adv Funct Materials

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“…While research is still in its early stages, promising results have been reported. TENG-based wound healing systems hold a collection of compelling features including portable size, [46,137,138] flexibility, [139,140] low cost, making them a promising, emerging biotechnology to advance the field of wound healing. Research efforts need to continue to address several bottlenecks in the field of TENG-based wound healing.…”

Section: Conclusion and Perspectivementioning

confidence: 99%

Triboelectric Nanogenerators for Self‐Powered Wound Healing

Xiao

Nashalian

Libanori

et al. 2021

Adv Healthcare Materials

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Wound healing, one of the most complex processes in the human body, involves the spatial and temporal synchronization of a variety of cell types with distinct roles. Slow or nonhealing skin wounds have potentially life-threatening consequences, ranging from infection to scar, clot, and hemorrhage. Recently, the advent of triboelectric nanogenerators (TENGs) has brought about a plethora of self-powered wound healing opportunities, owing to their pertinent features, including wide range choices of constitutive biocompatible materials, simple fabrication, portable size, high output power, and low cost. Herein, a comprehensive review of TENGs as an emerging biotechnology for wound healing applications is presented and covered from three unique aspects: electrical stimulation, antibacterial activity, and drug delivery. To provide a broader context of TENGs applicable to wound healing applications, state-of-the-art designs are presented and discussed in each section. Although some challenges remain, TENGs are proving to be a promising platform for human-centric therapeutics in the era of Internet of Things. Consequently, TENGs for wound healing are expected to provide a new solution in wound management and play an essential role in the future of point-of-care interventions.

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“…More recently, a third technological wave is coming where patients can take the lab with them through wearable bio-marker monitoring [1][2][3]. Wearable technology can be an innovative solution to current medical problems with the ability to continuously monitor both physiological and biochemical markers and physical activities and behaviors [4][5][6][7][8]. Vital signs such as heart rate, body temperature, and blood pressure are measured [9,10].…”

Section: Introductionmentioning

confidence: 99%

Wearable Biosensors for Non-Invasive Sweat Diagnostics

2021

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Recent advances in microfluidics, microelectronics, and electrochemical sensing methods have steered the way for the development of novel and potential wearable biosensors for healthcare monitoring. Wearable bioelectronics has received tremendous attention worldwide due to its great a potential for predictive medical modeling and allowing for personalized point-of-care-testing (POCT). They possess many appealing characteristics, for example, lightweight, flexibility, good stretchability, conformability, and low cost. These characteristics make wearable bioelectronics a promising platform for personalized devices. In this paper, we review recent progress in flexible and wearable sensors for non-invasive biomonitoring using sweat as the bio-fluid. Real-time and molecular-level monitoring of personal health states can be achieved with sweat-based or perspiration-based wearable biosensors. The suitability of sweat and its potential in healthcare monitoring, sweat extraction, and the challenges encountered in sweat-based analysis are summarized. The paper also discusses challenges that still hinder the full-fledged development of sweat-based wearables and presents the areas of future research.

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A portable triboelectric spirometer for wireless pulmonary function monitoring

Cited by 107 publications

References 54 publications

Intelligent Sound Monitoring and Identification System Combining Triboelectric Nanogenerator‐Based Self‐Powered Sensor with Deep Learning Technique

Intelligent Sound Monitoring and Identification System Combining Triboelectric Nanogenerator‐Based Self‐Powered Sensor with Deep Learning Technique

Triboelectric Nanogenerators for Self‐Powered Wound Healing

Wearable Biosensors for Non-Invasive Sweat Diagnostics

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