Papers by atena roshan fekr
JMIR Formative Research, 2022
Background Despite several measures to monitor and improve hand hygiene (HH) in health care setti... more Background Despite several measures to monitor and improve hand hygiene (HH) in health care settings, health care-acquired infections (HAIs) remain prevalent. The measures used to calculate HH performance are not able to fully benefit from the high-resolution data collected using electronic monitoring systems. Objective This study proposes a novel parameter for quantifying the HAI exposure risk of individual patients by considering temporal and spatial features of health care workers’ HH adherence. Methods Patient exposure risk is calculated as a function of the number of consecutive missed HH opportunities, the number of unique rooms visited by the health care professional, and the time duration that the health care professional spends inside and outside the patient’s room without performing HH. The patient exposure risk is compared to the entrance compliance rate (ECR) defined as the ratio of the number of HH actions performed at a room entrance to the total number of entrances in...
Scientific Reports, 2022
Fluid intake is important to prevent dehydration and reduce recurrent kidney stones. There has be... more Fluid intake is important to prevent dehydration and reduce recurrent kidney stones. There has been a trend in recent years to develop tools to monitor fluid intake using “smart” products such as smart bottles. Several commercial smart bottles are available, mainly targeting health-conscious adults. To the best of our knowledge, these bottles have not been validated in the literature. This study compares four commercially available smart bottles in terms of both performance and functionality. These bottles are the H2OPal, HidrateSpark Steel, HidrateSpark 3, and Thermos Smart Lid. One hundred intake events for each bottle were recorded and analyzed versus ground truth obtained from a high-resolution weight scale. The H2OPal had the lowest Mean Percent Error (MPE) and was able to balance out errors throughout multiple sips. The HidrateSpark 3 provided the most consistent and reliable results, with the lowest per sip error. The MPE values for HidrateSpark bottles were further improved ...
Minimum Toe Clearance Estimation Using a Novel Wearable System
Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021), 2021
A novel approach for slip resistance evaluation of winter footwear based on probability of slipping and cost analysis
Safety Science, 2021
Abstract This paper proposes a slip-prediction model to estimate the probability of footwear slip... more Abstract This paper proposes a slip-prediction model to estimate the probability of footwear slipping on ice. The mode is based on slips that are induced when human subjects are challenged by walking in a test chamber with full control over environmental conditions. This technique will help to evaluate the slip resistance quality of winter footwear in an ecologically valid manner. Four styles of winter footwear were tested by 8 participants on wet and dry ice surfaces with different slopes. The tests were repeated three times on different days. The probability of slipping was estimated for each incline angle using logistic regression analysis with three predictors: angle, ice condition and walking direction. In order to rank the quality of the winter footwear, a comprehensive cost analysis was performed to estimate the misclassification cost from the logistic regression. This method makes no assumption regarding the distribution of the data. The probability cutoff for each footwear style is obtained by minimizing the misclassification cost. The results show that increasing the incline angle significantly increases odds of slipping for all four styles ( p 0.01 ). In addition, as indicated by the results, different styles of footwear perform differently on the various winter surfaces. Therefore, this method is able to rank the slip-resistance property of the footwear based on the probability of slipping.
Nutrients, 2021
Fluid intake monitoring is an essential component in preventing dehydration and overhydration, es... more Fluid intake monitoring is an essential component in preventing dehydration and overhydration, especially for the senior population. Numerous critical health problems are associated with poor or excessive drinking such as swelling of the brain and heart failure. Real-time systems for monitoring fluid intake will not only measure the exact amount consumed by the users, but could also motivate people to maintain a healthy lifestyle by providing feedback to encourage them to hydrate regularly throughout the day. This paper reviews the most recent solutions to automatic fluid intake monitoring both commercially and in the literature. The available technologies are divided into four categories: wearables, surfaces with embedded sensors, vision- and environmental-based solutions, and smart containers. A detailed performance evaluation was carried out considering detection accuracy, usability and availability. It was observed that the most promising results came from studies that used data...
Walkway Safety Evaluation and Hazards Investigation for Trips and Stumbles Prevention
Advances in Intelligent Systems and Computing, 2018
Falls are a major healthcare concern especially in the older population and tripping is a primary... more Falls are a major healthcare concern especially in the older population and tripping is a primary cause. Tripping is defined biomechanically as an event at which the lowest part of the foot makes unanticipated contact with either the walking surface or objects during the swing phase of the gait cycle. Identifying an obstacle or uneven surface as a tripping hazard is a subjective assessment, particularly when considering the vulnerabilities of people with knee/hip replacement, stroke, Parkinson disease and osteoarthritis. There is no universally accepted measurement tool or interpretation of the hazards. Walkways can pose a serious risk of tripping and falling because of different factors such as overloading, frost heave, and tree roots. The main goal of this study is to provide a new solution for extracting features of walkway tripping hazards that can be correlated with the Probability of Tripping (PoT). A new scanning device is proposed which uses an array of Time-of-Flight sensors. Before extracting the features we need to make sure the proposed device will provide us accurate measurements. Therefore, in this paper, we have addressed the main challenges associated with accurate sensor readout in a multi-sensory system. The results show that the presented scanning device will provide readouts with accuracy of ±2.5 mm.
The effect of wear on slip-resistance of winter footwear with composite outsoles: A pilot study
Applied Ergonomics, 2022
Falls on icy surfaces are among the top causes of injuries for workers exposed to the outdoor env... more Falls on icy surfaces are among the top causes of injuries for workers exposed to the outdoor environment. Our recent field study showed that a new generation of winter footwear incorporating composite outsoles was able to reduce slips and falls on icy surfaces by 68% and 78%, respectively. The widespread adoption of this type of footwear may lead to substantial reductions in pain, suffering and costs of fall-related injuries. However, these composite materials are sensitive to wear and abrasion, which makes it likely that their slip-resistance performance may degrade with use. The goal of this pilot study was to determine the extent to which the slip-resistance of two types of winter footwear with composite outsoles changed as they wore down with real-world use. Seven participants were recruited for this study and were asked to walk 100K steps with their assigned footwear. Tread depth and slip-resistance performance (using the Maximum Achievable Angle test) were measured at baseline and again after each 25K-step interval up to 100K. Our results showed that the slip-resistance performance of the test footwear dropped significantly after the 75K and 100K step intervals compared to baseline. In addition, significant changes in tread depth were found after only 25K steps. These findings indicate that the performance of this type of footwear degrades relatively quickly with real-world use. Therefore, larger scale study of the slip-resistance of winter footwear with composite outsoles is needed and members of the public should be made aware of the potential loss of slip-resistance of these products.
International Journal of Environmental Research and Public Health, 2021
The use of slip-resistant winter footwear is crucial for the prevention of slips and falls on ice... more The use of slip-resistant winter footwear is crucial for the prevention of slips and falls on ice and snow. The main objective of this paper is to evaluate a mechanical testing method to determine footwear slip resistance on wet and dry ice surfaces and to compare it with the human-centred test method introduced by researchers at KITE (Knowledge, Innovation, Talent, Everywhere)-Toronto Rehabilitation Institute-University Health Network. Phase 1 of this study assessed the repeatability and reproducibility of the mechanical method by evaluating ten different occupational winter boots using two SATRA Slip resistance testers (STM 603, SATRA Technology Centre, Kettering, UK). One tester is located in Toronto and one in Montreal. These boots were chosen based on the needs of the IRSST (Institut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail, Montréal, Quebec, Canada), who were primarily interested in providing safe winter footwear for police, firefighters and municipal worke...
Sensors, 2020
Slip-induced falls are among the most common causes of major occupational injuries and economic l... more Slip-induced falls are among the most common causes of major occupational injuries and economic loss in Canada. Identifying the risk factors associated with slip events is key to developing preventive solutions to reduce falls. One factor is the slip-resistance quality of footwear, which is fundamental to reducing the number of falls. Measuring footwear slip resistance with the recently developed Maximum Achievable Angle (MAA) test requires a trained researcher to identify slip events in a simulated winter environment. The human capacity for information processing is limited and human error is natural, especially in a cold environment. Therefore, to remove conflicts associated with human errors, in this paper a deep three-dimensional convolutional neural network is proposed to detect the slips in real-time. The model has been trained by a new dataset that includes data from 18 different participants with various clothing, footwear, walking directions, inclined angles, and surface ty...
International Journal of Environmental Research and Public Health, 2020
Tripping hazards on the sidewalk cause many falls annually, and the inspection and repair of thes... more Tripping hazards on the sidewalk cause many falls annually, and the inspection and repair of these hazards cost cities millions of dollars. Currently, there is not an efficient and cost-effective method to monitor the sidewalk to identify any possible tripping hazards. In this paper, a new portable device is proposed using an Intel RealSense D415 RGB-D camera to monitor the sidewalks, detect the hazards, and extract relevant features of the hazards. This paper first analyzes the effects of environmental factors contributing to the device’s error and compares different regression techniques to calibrate the camera. The Gaussian Process Regression models yielded the most accurate predictions with less than 0.09 mm Mean Absolute Errors (MAEs). In the second phase, a novel segmentation algorithm is proposed that combines the edge detection and region-growing techniques to detect the true tripping hazards. Different examples are provided to visualize the output results of the proposed me...
Sensors, 2021
With new advances in technology, remote monitoring of heart failure (HF) patients has become incr... more With new advances in technology, remote monitoring of heart failure (HF) patients has become increasingly prevalent and has the potential to greatly enhance the outcome of care. Many studies have focused on implementing systems for the management of HF by analyzing physiological signals for the early detection of HF decompensation. This paper reviews recent literature exploring significant physiological variables, compares their reliability in predicting HF-related events, and examines the findings according to the monitored variables used such as body weight, bio-impedance, blood pressure, heart rate, and respiration rate. The reviewed studies identified correlations between the monitored variables and the number of alarms, HF-related events, and/or readmission rates. It was observed that the most promising results came from studies that used a combination of multiple parameters, compared to using an individual variable. The main challenges discussed include inaccurate data collect...
Sensors, 2021
Trip-related falls are one of the major causes of injury among seniors in Canada and can be attri... more Trip-related falls are one of the major causes of injury among seniors in Canada and can be attributable to an inadequate Minimum Toe Clearance (MTC). Currently, motion capture systems are the gold standard for measuring MTC; however, they are expensive and have a restricted operating area. In this paper, a novel wearable system is proposed that can estimate different foot clearance parameters accurately using only two Time-of-Flight (ToF) sensors located at the toe and heel of the shoe. A small-scale preliminary study was conducted to investigate the feasibility of foot clearance estimation using the proposed wearable system. We recruited ten young, healthy females to walk at three self-selected speeds (normal, slow, and fast) while wearing the system. Our data analysis showed an average correlation coefficient of 0.94, 0.94, 0.92 for the normal, slow, and fast speed, respectively, when comparing the ToF signals with motion capture. The ANOVA analysis confirmed these results furthe...
Haptic feedback and human performance in a wearable sensor system
2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2016
Citrine: A Methodology for Application-Specific Network-on-Chips Design
Bandwidth/Fault tolerance/Contention Aware Application-Specific NoC Using PSO as a Mapping Generator
Analysis of Motion Patterns for Recognition of Human Activities
Proceedings of the 5th EAI International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies", 2015
Application-Specific Networks-on-Chips Design
Movement analysis of the chest compartments and a real-time quality feedback during breathing therapy
Network Modeling Analysis in Health Informatics and Bioinformatics, 2015
Respiration Disorders Classification with Informative Features for m-health Applications
IEEE Journal of Biomedical and Health Informatics, 2015
Respiratory disorder is a highly prevalent condition associated with many adverse health problems... more Respiratory disorder is a highly prevalent condition associated with many adverse health problems. As the current means of diagnosis are obtrusive and ill-suited for real-time m-health applications, we explore a convenient and low-cost automatic approach that uses wearable MEMS sensor technology. The proposed system introduces the use of motion sensors to detect the changes in the anterior-posterior diameter of the chest wall during breathing function as well as extracting the informative respiratory features to be used for breathing disorders classification. An extensive evaluations are provided on six well-known classifiers with novel feature extraction techniques to distinguish among eight different pathological breathing patterns. The effects of the number of sensors, sensor placement as well as feature selection on the classification performance are discussed. The experimental results conducted with 10 subjects show the best accuracy rates of 97.50% by Support Vector Machine (SVM) and 97.37% with Decision Tree Bagging (DTB) with all features and after feature selection, correspondingly. Furthermore, a binary classification is proposed for distinguishing between healthy people and patients with breath problems. The different assessments of classification parameters are provided by measuring the accuracy, sensitivity, specificity, F1-score and Mathew Correlation Coefficient (MCC). The accuracy rates above 98% suggest superior performance of DTB in binary recognition supported by the suggested new features.
Development of a Remote Monitoring System for Respiratory Analysis
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2015
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Papers by atena roshan fekr