Automatic Facial Feature Extraction for Predicting Designers' Comfort With Engineering Equipment During Prototype Creation

2017 ◽  
Vol 139 (2) ◽  
Author(s):  
Shruthi Bezawada ◽  
Qianyu Hu ◽  
Allison Gray ◽  
Timothy Brick ◽  
Conrad Tucker
Keyword(s):  
Facial Feature ◽  
Specific Model ◽  
Comfort Level ◽  
Support Vector ◽  
Design Teams ◽  
Concept Generation ◽  
Engineering Equipment ◽  
Comfort Levels ◽  
Machine Learning Model ◽  
Before And After

Designers frequently utilize engineering equipment to create physical prototypes during the iterative concept generation and prototyping phases of design. Currently, evaluating designers' efficiency during prototype creation is a manual process that either involves observational or survey based approaches. Real-time feedback when using engineering equipment has the potential to enhance designers' efficiency or mitigate potential injuries that may result from incorrect use of equipment. Toward an automated approach to addressing these challenges, the authors of this work test the hypotheses that (i) there exists a difference in designers' comfort levels before and after they use a piece of engineering prototyping equipment and (ii) a machine learning model predicts the level of comfort a designer has while using engineering prototyping equipment with accuracies greater than random chance. It has been shown that the level of comfort that an individual has while completing a task impacts their performance. The authors investigate whether automatic tracking of designers' facial expressions during prototype creation predicts their level of comfort. A study, involving 37 participants using various engineering equipment, is used to validate the approach. The support vector machine (SVM) regression model yielded a range of R squared values from 0.82 to 0.86 for an equipment-specific model. A general model built to predict comfort level across all engineering equipment yielded an R squared value of 0.68. This work has the potential to transform the manner in which design teams utilize engineering equipment toward more efficient concept generation and prototype creation processes.

Abstract TP298: Code Stroke Simulation Training Benefits Junior Neurology Residents

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Linda C Wendell ◽  
Bradford B Thompson ◽  
Mahesh Jayaraman ◽  
Muhib Khan ◽  
David Lindquist ◽  
...  
Keyword(s):  
Emergency Medicine ◽  
Ischemic Stroke ◽  
Stroke Patient ◽  
Clinical Training ◽  
Simulation Training ◽  
Comfort Level ◽  
Ischemic Stroke Patient ◽  
Comfort Levels ◽  
Before And After ◽  
Perceived Preparedness

Introduction: Junior neurology residents frequently receive the first call for emergency neurological conditions, including acute ischemic stroke and intracerebral hemorrhage (ICH) (Code Stroke). Code Stroke simulations allow residents to gain experience in the evaluation and treatment of a potential stroke patient without compromising patient care. Simulations also give residents the opportunity to improve their skills through direct observation and feedback. We hypothesized that simulation training would increase junior neurology residents’ confidence, comfort level and preparedness in leading a Code Stroke. Methodology: Ten neurology residents in their first months of training each took turns leading a Code Stroke simulation – either assessment of an ischemic stroke patient for intravenous thrombolytics, coordination of an ischemic stroke patient for embolectomy, or management of an ICH patient. Standardized patients were used in each case. Emergency medicine, vascular neurology and neurointerventional radiology attendings were active participants in the cases and gave feedback. Residents completed a survey before and after the simulation. Results: On a 5-point Likert scale (1 – least true and 5 – most true), confidence in leading a Code Stroke significantly increased from 2.80 to 3.95 (p=0.01) and perceived preparedness for the next Code Stroke significantly improved from 2.80 to 4.30 (p<0.01). Residents reported significantly improved comfort levels in rapidly assessing the National Institutes of Health Stroke Scale score (3.35 vs. 4.25, p=0.03) and rapidly assessing a Code Stroke patient for thrombolytics (3.15 vs. 4.25, p=0.02), making the decision to give thrombolytics (2.80 vs. 4.00, p=0.02) and assessing a patient for embolectomy (3.33 vs. 4.67, p=0.03). There was a perception of enhanced mutli-disciplinary collaboration with emergency medicine providers (3.55 vs. 4.40, p=0.04) and neurointerventional radiologists (3.00 vs. 4.50, p=0.07). Conclusion: Simulation training is a beneficial part of medical education for junior neurology residents and should be considered in addition to traditional didactics and clinical training.

A longitudinal method of teaching pediatric palliative care to interns: Preliminary findings regarding changes in interns' comfort level

2010 ◽  
Vol 8 (1) ◽  
pp. 35-40 ◽  
Author(s):  
Shahram Yazdani ◽  
Elana Evan ◽  
Danielle Roubinov ◽  
Paul J. Chung ◽  
Lonnie Zeltzer
Keyword(s):  
Palliative Care ◽  
Los Angeles ◽  
Assessment Tool ◽  
Death And Dying ◽  
Comfort Level ◽  
Pediatric Palliative Care ◽  
First Year ◽  
Comfort Levels ◽  
Before And After ◽  
Life Threatening

AbstractObjective:A longitudinal pediatric palliative care curriculum was introduced into the pediatric residency program at the University of California, Los Angeles. The present study explores the possible effects of this curriculum on the interns' self-assessed comfort levels regarding caring for children with life-threatening conditions.Methods:A newly created assessment tool was administered to interns in order to rate their comfort regarding pediatric palliative care at the beginning and conclusion of their intern year.Results:Twenty-two of the 29 interns completed this survey. Baseline data indicated 55% of the interns had some experience with taking care of a dying pediatric patient during their medical school training, and 79% indicated that they had taken care of a dying adult. Only 7% of the interns felt adequately prepared to deal with death and dying, but all interns indicated interest in further learning about pediatric palliative care. Comparison of the overall comfort levels of the 22 responding residents before and after the first year of training in 20 different related tasks demonstrated a significant self-assessed improvement of comfort in seven areas. There was no increase in self-reported comfort in communication related to palliative care.Significance of results:Residents indicated increased comfort in some areas of pediatric palliative care after the first year of their training. The underlying cause of this increased comfort is unclear at this time. The overall effect of longitudinal palliative care curriculums on residents' level of comfort in caring for this population deserves further assessment.

scholarly journals Improving Psychological Comfort of Paramedics for Field Termination of Resuscitation through Structured Training

2021 ◽  
Vol 18 (3) ◽  
pp. 1050
Author(s):  
Chungli Bang ◽  
Desmond Ren Hao Mao ◽  
Rebacca Chew Ying Cheng ◽  
Jen Heng Pek ◽  
Mihir Gandhi ◽  
...  
Keyword(s):  
Training Session ◽  
Comfort Level ◽  
Domain Specific ◽  
Sociocultural Attitudes ◽  
Comfort Levels ◽  
Before And After ◽  
Change In The Mean ◽  
The Mean ◽  
The Impact ◽  
Self Administered Questionnaire

This study examines the impact of a newly developed structured training on Singapore paramedics’ psychological comfort before the implementation of a prehospital termination of resuscitation (TOR) protocol. Following a before and after study design, the paramedics underwent a self-administered questionnaire to assess their psychological comfort level applying the TOR protocol, 22 months before and one month after a 3-h structured training session. The questionnaire addressed five domains: sociocultural attitudes on resuscitation and TOR, multi-tasking, feelings towards resuscitation and TOR, interactions with colleagues and bystanders and informing survivors. Overall psychological comfort total (PCT) scores and domain-specific scores were compared using the paired t-test with higher scores representing greater comfort. Ninety-six of the 345 eligible paramedics responded. There was no statistically significant change in the mean PCT scores at baseline and post-training; however, the “feelings towards resuscitation and TOR” domain improved by 4.77% (95% CI 1.42 to 8.13 and p = 0.006) and the multi-tasking domain worsened by 4.11% (95% CI −7.82 to −0.41 and p = 0.030). While the structured training did not impact on the overall psychological comfort levels, it led to improvements in the feelings of paramedics towards resuscitation and TOR. Challenges remain in improving paramedics’ psychological comfort levels towards TOR.

Speech-Language Pathologists' Comfort Level With Use of Term “Stuttering” During Evaluations

2020 ◽  
Vol 29 (2) ◽  
pp. 841-850 ◽  
Author(s):  
Courtney T. Byrd ◽  
Danielle Werle ◽  
Kenneth O. St. Louis
Keyword(s):  
Communication Disorders ◽  
Academic Experiences ◽  
Comfort Level ◽  
Future Research ◽  
Clinical Experiences ◽  
Speech Language Pathologists ◽  
Comfort Levels ◽  
Parents And Children ◽  
Evaluation Feedback ◽  
Study Participants

Purpose Speech-language pathologists (SLPs) anecdotally report concern that their interactions with a child who stutters, including even the use of the term “stuttering,” might contribute to negative affective, behavioral, and cognitive consequences. This study investigated SLPs' comfort in providing a diagnosis of “stuttering” to children's parents/caregivers, as compared to other commonly diagnosed developmental communication disorders. Method One hundred forty-one school-based SLPs participated in this study. Participants were randomly assigned to one of two vignettes detailing an evaluation feedback session. Then, participants rated their level of comfort disclosing diagnostic terms to parents/caregivers. Participants provided rationale for their ratings and answered various questions regarding academic and clinical experiences to identify factors that may have influenced ratings. Results SLPs were significantly less likely to feel comfortable using the term “stuttering” compared to other communication disorders. Thematic responses revealed increased experience with a specific speech-language population was related to higher comfort levels with using its diagnostic term. Additionally, knowing a person who stutters predicted greater comfort levels as compared to other clinical and academic experiences. Conclusions SLPs were significantly less comfortable relaying the diagnosis “stuttering” to families compared to other speech-language diagnoses. Given the potential deleterious effects of avoidance of this term for both parents and children who stutter, future research should explore whether increased exposure to persons who stutter of all ages systematically improves comfort level with the use of this term.

60. Using a pocket card to improve end-of-life care on clinical teaching units: A controlled trials

2007 ◽  
Vol 30 (4) ◽  
pp. 61
Author(s):  
J. Downar ◽  
J. Mikhael
Keyword(s):  
End Of Life ◽  
Symptom Management ◽  
End Of Life Care ◽  
Palliative Medicine ◽  
Clinical Teaching ◽  
Intervention Group ◽  
Comfort Level ◽  
Control Group ◽  
Life Care ◽  
Comfort Levels

Although palliative and end-of-life is a critical part of in-hospital medical care, residents often have very little formal education in this field. To determine the efficacy of a symptom management pocket card in improving the comfort level and knowledge of residents in delivering end-of-life care on medical clinical teaching units, we performed a controlled trial involving residents on three clinical teaching units. Residents at each site were given a 5-minute questionnaire at the start and at the end of their medicine ward rotation. Measures of self-reported comfort levels were assessed, as were 5 multiple-choice questions reflecting key knowledge areas in end-of-life care. Residents at all three sites were given didactic teaching sessions covering key concepts in palliative and end-of-life care over the course of their medicine ward rotation. Residents at the intervention site were also given a pocket card with information regarding symptom management in end-of-life care. Over 10 months, 137 residents participated on the three clinical teaching units. Comfort levels improved in both control (p < 0.01) and intervention groups (p < 0.01), but the intervention group was significantly more comfortable than the control group at the end of their rotations (z=2.77, p < 0.01). Knowledge was not significantly improved in the control group (p=0.07), but was significantly improved in the intervention group (p < 0.01). The knowledge difference between the two groups approached but did not reach statistical significance at the end of their rotation. In conclusion, our pocket card is a feasible, economical educational intervention that improves resident comfort level and knowledge in delivering end-of-life care on clinical teaching units. Oneschuk D, Moloughney B, Jones-McLean E, Challis A. The Status of Undergraduate Palliative Medicine Education in Canada: a 2001 Survey. Journal Palliative Care 2004; 20:32. Tiernan E, Kearney M, Lynch AM, Holland N, Pyne P. Effectiveness of a teaching programme in pain and symptom management for junior house officers. Support Care Cancer 2001; 9:606-610. Okon TR, Evans JM, Gomez CF, Blackhall LJ. Palliative Educational Outcome with Implementation of PEACE Tool Integrated Clinical Pathway. Journal of Palliative Medicine 2004; 7:279-295.

A Novel Amino Acid Sequence-based Computational Approach to Predicting Cell-penetrating Peptides

2019 ◽  
Vol 15 (3) ◽  
pp. 206-211 ◽  
Author(s):  
Jihui Tang ◽  
Jie Ning ◽  
Xiaoyan Liu ◽  
Baoming Wu ◽  
Rongfeng Hu
Keyword(s):  
Machine Learning ◽  
Amino Acid ◽  
Amino Acid Position ◽  
Cell Penetrating Peptides ◽  
Support Vector ◽  
Cell Penetration ◽  
Drug Candidates ◽  
Machine Learning Model ◽  
Cell Penetrating ◽  
Novel Method

<P>Introduction: Machine Learning is a useful tool for the prediction of cell-penetration compounds as drug candidates. </P><P> Materials and Methods: In this study, we developed a novel method for predicting Cell-Penetrating Peptides (CPPs) membrane penetrating capability. For this, we used orthogonal encoding to encode amino acid and each amino acid position as one variable. Then a software of IBM spss modeler and a dataset including 533 CPPs, were used for model screening. </P><P> Results: The results indicated that the machine learning model of Support Vector Machine (SVM) was suitable for predicting membrane penetrating capability. For improvement, the three CPPs with the most longer lengths were used to predict CPPs. The penetration capability can be predicted with an accuracy of close to 95%. </P><P> Conclusion: All the results indicated that by using amino acid position as a variable can be a perspective method for predicting CPPs membrane penetrating capability.</P>

scholarly journals Prediction of 3D Cardiovascular hemodynamics before and after coronary artery bypass surgery via deep learning

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Gaoyang Li ◽  
Haoran Wang ◽  
Mingzi Zhang ◽  
Simon Tupin ◽  
Aike Qiao ◽  
...  
Keyword(s):  
Deep Learning ◽  
Artery Bypass ◽  
Computational Cost ◽  
Specific Model ◽  
Arterial System ◽  
Patient Specific ◽  
Cardiovascular Hemodynamics ◽  
Before And After ◽  
Deep Learning Network ◽  
Cfd Method

AbstractThe clinical treatment planning of coronary heart disease requires hemodynamic parameters to provide proper guidance. Computational fluid dynamics (CFD) is gradually used in the simulation of cardiovascular hemodynamics. However, for the patient-specific model, the complex operation and high computational cost of CFD hinder its clinical application. To deal with these problems, we develop cardiovascular hemodynamic point datasets and a dual sampling channel deep learning network, which can analyze and reproduce the relationship between the cardiovascular geometry and internal hemodynamics. The statistical analysis shows that the hemodynamic prediction results of deep learning are in agreement with the conventional CFD method, but the calculation time is reduced 600-fold. In terms of over 2 million nodes, prediction accuracy of around 90%, computational efficiency to predict cardiovascular hemodynamics within 1 second, and universality for evaluating complex arterial system, our deep learning method can meet the needs of most situations.

Detection of Vigil And Fatigue States During The Execution of Laparoscopic Tasks Based On EEG Patterns

2021 ◽  
Author(s):  
Yeremi Pérez ◽  
Roberto Borboa-Gastelum ◽  
Luz Maria Alonso-Valerdi ◽  
David I. Ibarra-Zarate ◽  
Eduardo A. Flores-Villalba ◽  
...  
Keyword(s):  
Medical Students ◽  
Individual Component ◽  
Support Vector ◽  
Patient Death ◽  
Professional Activities ◽  
Health Area ◽  
Before And After ◽  
Lack Of Sleep ◽  
Eeg Signal Processing

Abstract Fatigue decreases performance in several professional activities. Fatigue can lead to commit technical mistakes which consequences might be lethal, such as in health area, where a surgical error due to the absence of rest can provoke the patient death. Therefore, this study aims to detect vigil and fatigue (due to lack of sleep) states in medical students through the classification of electroencephalographic (EEG) patterns. The EEG signals of 18 physician students were analyzed within theta band (4 - 8 Hz) over front-central recording sites, and alpha band (8 - 13 Hz) rhythms over temporal and parieto-occipital recording sites during the execution of laparoscopic tasks before and after their medical duties. The EEG signal processing pipeline consisted in pre-processing based on individual component analysis, absolute band power estimates, and Support Vector Machine classification. The F-score to differ between vigil and fatigue states was 90.89%, where the first class was slightly more identifiable reaching a sensitivity of 90.18%. Based on this outcome, the detection of fatigue in medical students while their laparoscopic training seems achievable and feasible to diminish technical mistakes that could be lethal in health area. For this purpose, EEG recording are provided.

An Efficient Decision-Making Approach for Short Term Indoor Room Temperature Forecasting in Smart Environment: Evidence from India

2021 ◽  
pp. 1-42
Author(s):  
Kamal Pandey ◽  
Bhaskar Basu ◽  
Sandipan Karmakar
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Room Temperature ◽  
Linear Models ◽  
Comfort Level ◽  
Support Vector ◽  
Nonlinear Phenomenon ◽  
Short Term ◽  
Smart Buildings ◽  
Temperature Forecasting

“Smart cities” start with “Smart Buildings” that improve the quality of urban services while ensuring sustainability. The current scenario in India reveals that the corporate and residential building structures are incorporating various self-sustainable techniques. Out of the multiple factors governing the comfort of smart buildings, indoor room temperature is an important one, since it drives the need of cooling or heating through controlling systems. Around one-third of total energy consumption of commercial buildings in India is attributed to Heating, Ventilation and Air Conditioning (HVAC) systems. Accurate prediction of indoor room temperature helps in creating an efficient equilibrium between energy consumption and comfort level of the building, thus providing opportunities for efficient decision making for energy optimization. Considering Indian climatic and geographical conditions, this paper proposes an efficient decision making approach using Bayesian Dynamic Models (BDM) for short-term indoor room temperature forecasting of a corporate building structure. The results obtained from Bayesian Dynamic linear model, using Expectation Maximization (EM) algorithm, have been compared to standard Auto Regressive Integrated Moving Average (ARIMA) model, and have been found to be more accurate. Forecasting of indoor room temperature is a highly nonlinear phenomenon, so to further improve the accuracy of the linear models, a hybrid modeling approach has been proposed. The inclusion of state-of-the-art nonlinear models such as Artificial Neural Networks (ANNs) and Support Vector Regression (SVR) improves the forecasting accuracy of the linear models significantly. Results show that the hybrid model obtained using BDM and ANN is the best fit model.

scholarly journals Evidence-based practice of stereotactic radiosurgery: Outcomes from an educational course for neurosurgery and radiation oncology residents

2021 ◽  
Vol 12 ◽  
pp. 77
Author(s):  
Swathi Chidambaram ◽  
Sergio W. Guadix ◽  
John Kwon ◽  
Justin Tang ◽  
Amanda Rivera ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Stereotactic Radiosurgery ◽  
Radiation Oncology ◽  
Evidence Based Practice ◽  
Evidence Base ◽  
Comfort Level ◽  
Evidence Based ◽  
Senior Faculty ◽  
Exact Test ◽  
Before And After

Background: As the field of brain and spine stereotactic radiosurgery (SRS) continues to grow, so will the need for a comprehensive evidence base. However, it is unclear to what degree trainees feel properly equipped to use SRS. We assess the perceptions and comfort level reported by neurosurgery and radiation oncology residents concerning the evidence-based practice of SRS. Methods: A continuing medical education (CME) course provided peer-reviewed updates regarding treatment with intracranial and spinal SRS. Presentations were given by neurosurgery and radiation oncology residents with mentorship by senior faculty. To gauge perceptions regarding SRS, attendees were surveyed. Responses before and after the course were analyzed using the Fisher’s exact test in R statistical software. Results: Participants reported the greatest knowledge improvements concerning data registries (P < 0.001) and clinical trials (P = 0.026). About 82% of all (n = 17) radiation oncology and neurosurgery residents either agreed or strongly agreed that a brain and spine SRS rotation would be beneficial in their training. However, only 47% agreed or strongly agreed that one was currently part of their training. In addition, knowledge gains in SRS indications (P = 0.084) and ability to seek collaboration with colleagues (P = 0.084) showed notable trends. Conclusion: There are clear knowledge gaps shared by potential future practitioners of SRS. Specifically, knowledge regarding SRS data registries, indications, and clinical trials offer potential areas for increased educational focus. Furthermore, the gap between enthusiasm for increased SRS training and the current availability of such training at medical institutions must be addressed.

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