Research on denoising algorithm of thoracic impedance signal for respiratory monitoring during running exercise

Ge, Hao; Qin, Hui; Xue, Shengjun; Liu, Enkang; Zhang, Mingzhu; Bai, Zixuan; Ma, Yunlong

doi:10.1016/j.bspc.2021.102941

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…Since the 21st century, Internet technology and computer hardware technology have developed rapidly and become popular [1]. e data stock of the Internet has increased exponentially, but there are only a handful of data containing valuable information [2]. erefore, mining valuable information from massive data has changed into the most essential factor or the content in society at present [3].…”

Section: Introductionmentioning

confidence: 99%

Discussion on Redundant Processing Algorithm of Association Rules Based on Hypergraph in Data Mining

Zhu

2022

Journal of Robotics

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With the rapid advancement of big data, it is becoming a great problem for people to nd objective information in the database.e relevance data processing rule for digging the information can be the way. Relevance data processing rule for digging the information is mainly studied in three aspects: data dimension, data abstraction level, and processing variable type. In the aspect of rules, the research mainly focuses on three aspects: active relationships, passive rules, and uncommon relationship rules. Association rules of digging the data can be the most well-employed investigation goal and aim for the data digging. Along with the advancement of the information scale, the time rate of traditional relationship rules exploration of counting ways is too low. How to increase the time rate for the way of counting is the main research content of relevance data processing rules for digging the information. Current relevance data processing rules for digging the information have two limitations: (1) metrics such as support, con dence, and lift rely too much on expert knowledge or complex adjustment processes in value selection; (2) it is often di cult to explain rare association rules. Based on the existing research, this paper proposes a Markov logic network framework model of association rules to address the above shortcomings. e theory of a hypergraph and system is proposed, and the method of a hypergraph in 3D matrix modeling is studied. Aiming at the new characteristics of big data analysis, a new super edge de nition method is introduced according to the de nition of the system, which greatly enhances the ability to solve problems. In the cluster analysis and calculation of hypergraph, this paper will use the hypergraph segmentation operator hMETIS to carry out the cluster analysis method in order to achieve higher accuracy in cluster analysis and calculation. As for the test of cycle ones, which is in line with the relevance of the hypergraph with clear directions, the thesis will o er a brand-new way to make an analysis and turn the rule of relevance into the hypergraph with clear directions with a new de nition of the near linking matrix, and it will change the dealing way from the test of the cycle and more ones into the linking f bricks and circles, which is a new way to explore. is paper uses two datasets of di erent sizes to conduct rule prediction accuracy experiments on the Markov logic network framework model algorithm of association rules and the traditional association rule algorithm. e results show that compared with the traditional association rule algorithm, the rules obtained by the Markov logic network framework model of association rules have a higher prediction accuracy.

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Section: Introductionmentioning

confidence: 99%

Discussion on Redundant Processing Algorithm of Association Rules Based on Hypergraph in Data Mining

Zhu

2022

Journal of Robotics

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“…However, the raw IP measurement encountered drastic baseline drifts, which was a stochastic process both inter-individual and intra-individual, and exhibited relatively low frequency band but extreme complexity and uncertainty. It attributed to a long-term factor of electrical-chemical reaction at the electrode-skin interface and an independent short-term factor of end-tidal residual volume variation due to uneven breathing (Ge et al 2021). Their distortion on baseline were intertwined, to which traditional methods used in detrending static IP, such as polynomial fitting and spectral filtering, failed to present sufficient adaptability.…”

Section: Denoising Strategymentioning

confidence: 99%

“…However, there were still signal change caused by motion and cardiac activities observed as small pulses of higher frequencies superimposed on the respiratory IP. To extricate the respiratory component, the IP signals were then conditioned with a wpsTID denoising algorithm previously proposed by our group, as detailed in (Ge et al 2021).…”

Section: Denoising Strategymentioning

confidence: 99%

“…Lastly, IP is easy to be noise-corrupted with its intrinsic sensitivity to tissue perfusion, muscle tension, cardiomotility and possibly other upper-body physiological activities except overall posture change, proposing a challenge to separate its ventilation component from baseline drifts and motion artifacts during CPET. To this end, a brief denoising strategy with variational mode decomposition (VMD) removing the baseline drift while wpsTID (Ge et al 2021) eliminating the cardiac and motion component was applied on the IP measurements to preserve the respiratory features for the establishment of volume and VE evaluation.…”

Section: Introductionmentioning

confidence: 99%

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Experimental validation of an advanced impedance pneumography for monitoring ventilation volume during programmed cycling exercise

Zhou,

Liu,

Bai

et al. 2024

Physiol. Meas.

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Objective:Impedance pneumography (IP) has provided static assessments of subjects’ breathing patterns in previous studies. Evaluating the feasibility and limitation of ambulatory IP based respiratory monitoring needs further investigation on clinically relevant exercise designs. The aim of this study was to evaluate the capacity of an advanced IP in ambulatory respiratory monitoring, and its predictive value in independent ventilatory capacity quantification during cardiopulmonary exercise testing (CPET).Approach:35 volunteers were examined with the same calibration methodology and CPET exercise protocol comprising phases of rest, unloaded, incremental load, maximum load, recovery and further-recovery. In 3 or 4 deep breaths of calibration stage, thoracic impedance and criterion spirometric volume were simultaneously recorded to produce phase-specific prior calibration coefficients (CCs). The IP measurement during exercise protocol was converted by prior CCs to volume estimation curve and thus calculate minute ventilation (VE) independent from the spirometry approach.Main results:Across all measurements, the relative error of IP-derived VE (VER) and flowrate-derived VE (VEf) was less than 13.8%. In Bland-Altman plots, the aggregate VE estimation bias was statistically insignificant for all 3 phases with pedaling exercise and the discrepancy between VER and VEf fell within the 95% limits of agreement (95% LoA) for 34 or all subjects in each of all CPET phases.Significance: This work reinforces the independent use of IP as an accurate and robust alternative to flowmeter for applications in cycle ergometry CPET, which could significantly encourage the clinical use of IP and improve the convenience and comfort of CPET.

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Instant Disinfecting Face Masks Utilizing Electroporation Powered by Respiration‐Driven Triboelectric Nanogenerators

Sim,

Ee,

Lim

et al. 2024

Adv Funct Materials

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Wearing face masks is an effective non‐pharmaceutical strategy to inhibit the transmission of airborne diseases. Nonetheless, most commercial face masks lack disinfecting capabilities, posing risks of secondary transmission, while those with antimicrobial coatings are incapable of instant pathogen inactivation. Herein, a proof‐of‐concept instant disinfecting face mask is demonstrated consisting of a Cu(OH)2‐nanowire electroporation filter powered by a respiration‐driven triboelectric nanogenerator (R‐TENG). The R‐TENG comprises electrospun polyvinyl alcohol (PVA) and polyvinylidene fluoride (PVDF) membranes. A dome‐shaped PVA membrane is specifically designed to maximize the effective contact area. Coupling the novel dome‐shape design with maximized β‐phase crystallites of PVDF, the enhanced R‐TENG generates an open‐circuit voltage of 120 V under the normal breathing rate of an adult, resulting in an amplified electric field of 19 MV m−1 at the nanowire tips of the electroporation filter. Under this high localized electric field, effective inactivation of bacteria (>99.9%) is achieved via a synergy of electroporation and physical penetration. Conversely, when the R‐TENG is disconnected, only partial inactivation (90%–99%) via physical penetration is realized. For the first time, it shows that R‐TENG powered electroporation is a viable solution to achieve instant, effective disinfection, paving the way for next‐generation face masks.

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Research on denoising algorithm of thoracic impedance signal for respiratory monitoring during running exercise

Cited by 4 publications

References 11 publications

Discussion on Redundant Processing Algorithm of Association Rules Based on Hypergraph in Data Mining

Discussion on Redundant Processing Algorithm of Association Rules Based on Hypergraph in Data Mining

Experimental validation of an advanced impedance pneumography for monitoring ventilation volume during programmed cycling exercise

Instant Disinfecting Face Masks Utilizing Electroporation Powered by Respiration‐Driven Triboelectric Nanogenerators

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