Automatic detection of poor quality signals as a pre-processing scheme in the analysis of sEMG in swallowing

2022 ◽  
Vol 71 ◽  
pp. 103122
Author(s):  
J. Cuadros-Acosta ◽  
A. Orozco-Duque
Keyword(s):  
Automatic Detection ◽  
Poor Quality ◽  
Processing Scheme ◽  
Quality Signals

Suspecting service overprovisions: how market signals help restore personal control and reduce decision deferrals

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Subimal Chatterjee ◽  
Debi P. Mishra ◽  
Jennifer JooYeon Lee ◽  
Sirajul A. Shibly
Keyword(s):  
Process Model ◽  
Service Providers ◽  
Personal Control ◽  
Poor Quality ◽  
Mediation Process ◽  
Content Type ◽  
Quality Signal ◽  
Market Signals ◽  
Quality Signals ◽  
Practical Implications

Purpose Service providers often recommend unnecessary and expensive services to unsuspecting consumers, such as recommending a new part when a simple fix to the old will do, a phenomenon known as overprovisioning. The purpose of this paper is to examine to what extent consumers tend to defer their decisions should they suspect that sellers are overproviding services to them and they cannot prevent the sellers from doing so (they lack personal control); and how proper market signals can mitigate such suspicions, restore personal control and reduce deferrals. Design/methodology/approach The paper conducts three laboratory experiments. The experiments expose the participants to hypothetical repair scenarios and measure to what extent they suspect that sellers might be overproviding services to them and they feel that they lack the personal control to prevent the sellers from doing so. Thereafter, the experiments expose them to two different market signals, one conveying that the seller is providing quality services (a repair warranty; quality signal) and the other conveying that the seller is taking away any incentives their agents (technicians) may have to overprovide services (the technicians are paid a flat salary; quantity signal). The paper examines how these quality/quantity signals are able to reduce overprovisioning suspicions, restore personal control and reduce decision deferrals. Findings The paper has two main findings. First, the paper shows a mediation process at work i.e. suspecting potential overprovisioning by sellers leads consumers to defer their decisions indirectly because they feel that they lack personal control to prevent the sellers from doing so. Second, the paper shows that the quantity signal (flat salary disclosure), but not the quality signal (warranty), is able to mitigate suspicions of overprovisioning, restore personal control and reduce decision deferrals. Practical implications The paper suggests that although buyers may rely on quality signals to assure them of superior service, these signals do not guarantee that the quantity of service they are receiving is appropriate. Therefore, sellers will have to send a credible quality signal and a credible quantity signal to the consumers if they wish to tackle suspicions about service overprovision and service quality. Originality/value The paper is original in two ways. First, the paper theorizes and tests a mediation process model whereby quality/quantity signals differentially mitigate overprovisioning suspicions, restore personal control and reduce decision deferrals. Second, the paper speaks to the necessity of expanding the traditional signaling literature, designed primarily to detect poor quality hidden in the products/services of lower-quality sellers, to include detecting/solving overprovisioning often hidden in the services provided by higher-quality sellers.

scholarly journals CaRiSMA 1.0: Cardiac Risk Self-Monitoring Assessment

2017 ◽  
Vol 10 (1) ◽  
pp. 179-190 ◽  
Author(s):  
Angela Agostinelli ◽  
Micaela Morettini ◽  
Agnese Sbrollini ◽  
Elvira Maranesi ◽  
Lucia Migliorelli ◽  
...  
Keyword(s):  
Wearable Sensors ◽  
Training Session ◽  
Cardiac Risk ◽  
Poor Quality ◽  
Traffic Light ◽  
Self Monitoring ◽  
Software Application ◽  
Traffic Lights ◽  
Quality Signals ◽  
First Time

Background:Sport-related sudden cardiac death (SRSCD) can only be fought through prevention.Objective:The aim of this study is to propose an innovative software application, CaRiSMA 1.0 (Cardiac Risk Self-Monitoring Assessment), as a potential tool to help contrasting SRSCD and educating to a correct training.Methods:CaRiSMA 1.0 analyzes the electrocardiographic and heart-rate (HR) signals acquired during a training session through wearable sensors and provides intuitive graphical outputs consisting of two traffic lights, one related to cardiac health, based on resting QTc (a parameter quantifying the duration of ventricular contraction and subsequent relaxation), and one related to training, based on exercise HR. Safe and worthwhile training sessions have green traffic lights. A red QTc traffic light indicates the need of a medical consultation, whereas a red HR traffic light indicate the need of a reduction of training intensity. By way of example, CaRiSMA 1.0 was applied to sample data acquired in 10 volunteers (age= 27±11 years; males/females 3/7).Results:Two acquisitions (20.0%) were rejected because too noisy, indicating that wearable sensors may record poor quality signals. The QTc traffic light was red in 1 case, indicating that people practicing sport may not be aware of being at risk. The HR traffic light was red in 0 cases.Conclusion:CaRiSMA 1.0 is a software application that, for the first time in the sport context, uses QTc, the most important index of cardiac risk in clinics. Thus, it has the potential for giving a contribution in the fight against SRSCD.

Photoplethysmogram Signal Quality Assessment Using Support Vector Machine and Multi-Feature Fusion

2018 ◽  
Vol 8 (9) ◽  
pp. 1757-1762 ◽  
Author(s):  
Jie Zhang ◽  
Licai Yang ◽  
Zhonghua Su ◽  
Xueqin Mao ◽  
Kan Luo ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Quality Assessment ◽  
Feature Fusion ◽  
Poor Quality ◽  
Heart Beat ◽  
Support Vector ◽  
Signal Quality ◽  
Physiological Signal ◽  
Quality Signals

Background: Noise is unavoidable in the physiological signal measurement system. Poor quality signals can affect the results of analysis and disable the following clinical diagnosis. Thus, it is necessary to perform signal quality assessment before we interpreting the signal. Objective: In this work, we describe a method combing support vector machine (SVM) and multi-feature fusion for assessing the signal quality of pulsatile waveforms, concentrating on the photoplethysmogram (PPG). Methods: PPG signals from 53 healthy volunteers were recorded. Each had a 5 min length. Signal quality in each heart beat was manual annotated by clinical expert, and then the signal quality in 5 s episode was automatically calculated according to the results from each beat segments, resulting in a total of 13,294 5-s PPG segments. Then a SVM was trained to classify clean/noisy PPG recordings by inputting a set of twelve signal quality features. Further experiments were carried out to verify the proposed SVM based signal quality classifier method. Results: An average accuracy of 87.90%, a sensitivity of 88.10% and a specificity of 87.66% were found on the 10-fold cross validation. Conclusions: The signal quality of PPGs can be accurately classified by using the proposed method.

Parasite defense mechanisms in bees: behavior, immunity, antimicrobials, and symbionts

2019 ◽  
Vol 4 (1) ◽  
pp. 59-76 ◽  
Author(s):  
Alison E. Fowler ◽  
Rebecca E. Irwin ◽  
Lynn S. Adler
Keyword(s):  
Defense Mechanisms ◽  
Poor Quality ◽  
Future Research ◽  
Immune Priming ◽  
Social Bees ◽  
Bee Health ◽  
Landscape Scales ◽  
And Function ◽  
Solitary Species

Parasites are linked to the decline of some bee populations; thus, understanding defense mechanisms has important implications for bee health. Recent advances have improved our understanding of factors mediating bee health ranging from molecular to landscape scales, but often as disparate literatures. Here, we bring together these fields and summarize our current understanding of bee defense mechanisms including immunity, immunization, and transgenerational immune priming in social and solitary species. Additionally, the characterization of microbial diversity and function in some bee taxa has shed light on the importance of microbes for bee health, but we lack information that links microbial communities to parasite infection in most bee species. Studies are beginning to identify how bee defense mechanisms are affected by stressors such as poor-quality diets and pesticides, but further research on this topic is needed. We discuss how integrating research on host traits, microbial partners, and nutrition, as well as improving our knowledge base on wild and semi-social bees, will help inform future research, conservation efforts, and management.

Automatic detection of epileptiform spikes in the electrocorticogram: a comparison of two algorithms

Seizure ◽  
1998 ◽  
Vol 7 (2) ◽  
pp. 145-152 ◽  
Author(s):  
M DUMPELMANN ◽  
C ELGER
Keyword(s):  
Automatic Detection

The Impact of Missing and Error-Prone Auxiliary Information on Sparse-Matrix Sub-Population Parameter Estimates

Methodology ◽  
2015 ◽  
Vol 11 (3) ◽  
pp. 89-99 ◽  
Author(s):  
Leslie Rutkowski ◽  
Yan Zhou
Keyword(s):  
Sparse Matrix ◽  
Small Body ◽  
Auxiliary Information ◽  
Poor Quality ◽  
Quality Data ◽  
Estimation Methods ◽  
Parameter Estimates ◽  
Population Parameter ◽  
Conditioning Model ◽  
The Impact

Abstract. Given a consistent interest in comparing achievement across sub-populations in international assessments such as TIMSS, PIRLS, and PISA, it is critical that sub-population achievement is estimated reliably and with sufficient precision. As such, we systematically examine the limitations to current estimation methods used by these programs. Using a simulation study along with empirical results from the 2007 cycle of TIMSS, we show that a combination of missing and misclassified data in the conditioning model induces biases in sub-population achievement estimates, the magnitude and degree to which can be readily explained by data quality. Importantly, estimated biases in sub-population achievement are limited to the conditioning variable with poor-quality data while other sub-population achievement estimates are unaffected. Findings are generally in line with theory on missing and error-prone covariates. The current research adds to a small body of literature that has noted some of the limitations to sub-population estimation.

The automatic detection of unattended social category information from unfamiliar faces

2014 ◽  
Author(s):  
Douglas Martin ◽  
Rachel Swainson ◽  
Gillian Slessor ◽  
Jacqui Hutchison ◽  
Diana Marosi
Keyword(s):  
Automatic Detection ◽  
Social Category ◽  
Category Information ◽  
Unfamiliar Faces
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