Drowsiness Detection Using Viola–Jones Object Detection Algorithm for Real-Time Data

Author(s):  
Raghavendra Kumar ◽  
Himanshu Rathore ◽  
Palak Agrawal ◽  
Prakhar Gupta
2018 ◽  
Vol 23 (40) ◽  
Author(s):  
Navina Sarma ◽  
Alexander Ullrich ◽  
Hendrik Wilking ◽  
Stéphane Ghozzi ◽  
Andreas K. Lindner ◽  
...  

Europe received an increased number of migrants in 2015. Housing in inadequate mass accommodations (MA) made migrants prone to infectious disease outbreaks. In order to enhance awareness for infectious diseases (ID) and to detect clusters early, we developed and evaluated a syndromic surveillance system in three MA with medical centres in Berlin, Germany. Healthcare workers transferred daily data on 14 syndromes to the German public health institute (Robert Koch-Institute). Clusters of ID syndromes and single cases of outbreak-prone diseases produced a signal according to a simple aberration-detection algorithm that computes a statistical threshold above which a case count is considered unusually high. Between May 2016–April 2017, 9,364 syndromes were reported; 2,717 (29%) were ID, of those 2,017 (74%) were respiratory infections, 262 (10%) skin parasites, 181 (7%) gastrointestinal infections. The system produced 204 signals, no major outbreak was detected. The surveillance reinforced awareness for public health aspects of ID. It provided real-time data on migrants' health and stressed the burden of non-communicable diseases. The tool is available online and was evaluated as being feasible and flexible. It complements traditional notification systems. We recommend its usage especially when laboratory testing is not available and real-time data are needed.


Author(s):  
Indranil Majumder ◽  
Nagi G. Naganathan ◽  
Young-Gon Kim

Abstract An algorithm has been developed for detecting a collision-free path for an Automated Guided Vehicle (AGV) when it is required to navigate in an unstructured environment. Real time implementation issues are discussed and investigated experimentally using an ultrasonic sensor system. Concepts of obstacle matrix and path penalty are used in the guidance of the vehicle in a work area discretized as matrix cells. Two search methods namely, the arc searching method and obstacle crawling method, are developed for the AGV to facilitate navigation. The algorithm is capable of admitting the appropriate search method depending on the nature of the obstacles in the work area. Case studies using real time data from ultrasonic sensors demonstrate an excellent level of performance for the algorithm.


Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 399-P
Author(s):  
ANN MARIE HASSE ◽  
RIFKA SCHULMAN ◽  
TORI CALDER

2021 ◽  
Vol 31 (6) ◽  
pp. 7-7
Author(s):  
Valerie A. Canady
Keyword(s):  

Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.


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