Wearable Sensors and Their Metrics for Measuring Comprehensive Occupational Fatigue: A Scoping Review

2017 ◽  
Vol 61 (1) ◽  
pp. 1041-1045 ◽  
Author(s):  
Yibo Zhu ◽  
Rasik R Jankay ◽  
Laura C Pieratt ◽  
Ranjana K. Mehta
Keyword(s):  
Heart Rate ◽  
Scoping Review ◽  
Wearable Sensors ◽  
Health And Safety ◽  
Exclusion Criteria ◽  
Multidimensional Construct ◽  
Ovid Medline ◽  
Rate Sensor ◽  
Sleep Length ◽  
Occupational Fatigue

Extensive research has been conducted to study the effects of physical and sleep related fatigue on occupational health and safety. However, fatigue is a complex multidimensional construct, that is task- and occupation-dependent, and our knowledge on how to measure this complex construct is limited. A scoping review was conducted to: 1) review sensors and their metrics currently employed in occupational fatigue studies, 2) identify overlap between sensors and associated metrics that can be leveraged to assess comprehensive fatigue, 3) investigating the effectiveness of the sensors/metrics, and 4) recommended potential sensor/metric combinations to evaluate comprehensive fatigue. 512 unique abstracts were identified through Ovid-MEDLINE, MEDLINE, Embase and Cinal databases and application of the inclusion/exclusion criteria resulted in 27 articles that were included for the review. Heart rate sensors and actigraphs were identified to be the most suitable devices to study comprehensive fatigue. Heart rate trend within the heart rate sensor, and sleep length and sleep efficiency within actigraphs were found to be the most popular and reliable metrics for measuring occupational fatigue.

scholarly journals Framework for Intelligent Swimming Analytics with Wearable Sensors for Stroke Classification

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5162
Author(s):  
Joana Costa ◽  
Catarina Silva ◽  
Miguel Santos ◽  
Telmo Fernandes ◽  
Sérgio Faria
Keyword(s):  
Heart Rate ◽  
High Performance ◽  
Wearable Sensors ◽  
Feature Representation ◽  
Time Data ◽  
Immediate Feedback ◽  
Iot Devices ◽  
And Performance ◽  
Rate Sensor ◽  
Sports Coaching

Intelligent approaches in sports using IoT devices to gather data, attempting to optimize athlete’s training and performance, are cutting edge research. Synergies between recent wearable hardware and wireless communication strategies, together with the advances in intelligent algorithms, which are able to perform online pattern recognition and classification with seamless results, are at the front line of high-performance sports coaching. In this work, an intelligent data analytics system for swimmer performance is proposed. The system includes (i) pre-processing of raw signals; (ii) feature representation of wearable sensors and biosensors; (iii) online recognition of the swimming style and turns; and (iv) post-analysis of the performance for coaching decision support, including stroke counting and average speed. The system is supported by wearable inertial (AHRS) and biosensors (heart rate and pulse oximetry) placed on a swimmer’s body. Radio-frequency links are employed to communicate with the heart rate sensor and the station in the vicinity of the swimming pool, where analytics is carried out. Experiments were carried out in a real training setup, including 10 athletes aged 15 to 17 years. This scenario resulted in a set of circa 8000 samples. The experimental results show that the proposed system for intelligent swimming analytics with wearable sensors effectively yields immediate feedback to coaches and swimmers based on real-time data analysis. The best result was achieved with a Random Forest classifier with a macro-averaged F1 of 95.02%. The benefit of the proposed framework was demonstrated by effectively supporting coaches while monitoring the training of several swimmers.

EMFi material as wearable heart rate sensor for night time recordings

2010 ◽  
Author(s):  
Antti Vehkaoja ◽  
Timo Salpavaara ◽  
Jarmo Verho ◽  
Jukka Lekkala
Keyword(s):  
Heart Rate ◽  
Night Time ◽  
Rate Sensor

scholarly journals 651 Longitudinal, unobtrusive, and ecologically valid sleep metric estimation from a smart bed to predict the pathology of COVID-19

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A255-A255
Author(s):  
Dmytro Guzenko ◽  
Gary Garcia ◽  
Farzad Siyahjani ◽  
Kevin Monette ◽  
Susan DeFranco ◽  
...  
Keyword(s):  
Heart Rate ◽  
Sleep Quality ◽  
Predictive Model ◽  
Sleep Duration ◽  
Wearable Sensors ◽  
Test Results ◽  
Cloud Data ◽  
Cardiorespiratory Function ◽  
Group Data ◽  
Rich Information

Abstract Introduction Pathophysiologic responses to viral respiratory challenges such as SARS-CoV-2 may affect sleep duration, quality and concomitant cardiorespiratory function. Unobtrusive and ecologically valid methods to monitor longitudinal sleep metrics may therefore have practical value for surveillance and monitoring of infectious illnesses. We leveraged sleep metrics from Sleep Number 360 smart bed users to build a COVID-19 predictive model. Methods An IRB approved survey was presented to opting-in users from August to November 2020. COVID-19 test results were reported by 2003/6878 respondents (116 positive; 1887 negative). From the positive group, data from 82 responders (44.7±11.3 yrs.) who reported the date of symptom onset were used. From the negative group, data from 1519 responders (48.4±12.9 yrs.) who reported testing dates were used. Sleep duration, sleep quality, restful sleep duration, time to fall asleep, respiration rate, heart rate, and motion level were obtained from ballistocardiography signals stored in the cloud. Data from January to October 2020 were considered. The predictive model consists of two levels: 1) the daily probability of staying healthy calculated by logistic regression and 2) a continuous density Hidden Markov Model to refine the daily prediction considering the past decision history. Results With respect to their baseline, significant increases in sleep duration, average breathing rate, average heart rate and decrease in sleep quality were associated with symptom exacerbation in COVID-19 positive respondents. In COVID-19 negative respondents, no significant sleep or cardiorespiratory metrics were observed. Evaluation of the predictive model resulted in cross-validated area under the receiving-operator curve (AUC) estimate of 0.84±0.09 which is similar to values reported for wearable-sensors. Considering additional days to confirm prediction improved the AUC estimate to 0.93±0.05. Conclusion The results obtained on the smart bed user population suggest that unobtrusive sleep metrics may offer rich information to predict and track the development of symptoms in individuals infected with COVID-19. Support (if any):

Joy in the Workplace: A Scoping Review of Positive Emotion and Electroencephalogram

2020 ◽  
Vol 64 (1) ◽  
pp. 1493-1497
Author(s):  
Yaqoub Yusuf ◽  
Jodi Boutte’ ◽  
Asante’ Lloyd ◽  
Emma Fortune ◽  
Renaldo C. Blocker
Keyword(s):  
Real Time ◽  
Scoping Review ◽  
Positive Emotion ◽  
Positive Emotions ◽  
Wearable Sensors ◽  
Recent Advances ◽  
Electrode Systems ◽  
Electroencephalogram Eeg ◽  
Occupational Settings

A workplace that is a conduit for positive emotions can be important to employees retention and can contribute optimal levels of productivity. Validated tools for examining emotions are primarily subjective and retrospective in nature. Recent advances in technology have led to more novel and passive ways of measuring emotions. Wearable sensors, such as electroencephalogram (EEG), are being explored to assess cognitive and physical burdens objectively and in real-time. Therefore, there exists a need to investigate and validate the use of EEG to examine emotions objectively and in real-time. In this paper, we conducted a scoping review of EEG to measure positive emotions and/or indicators of joy in the workplace. Our review results in 22 articles that employ EEG to study joy in occupational settings. Three major themes identified in the analysis include (1) EEG for symptoms detection and outcomes, (2) Populations studied using EEG, and (3) EEG electrode systems.

scholarly journals Use of mHealth Technology for Patient-Reported Outcomes in Community-Dwelling Adults with Acquired Brain Injuries: A Scoping Review

2021 ◽  
Vol 18 (4) ◽  
pp. 2173
Author(s):  
Shannon B. Juengst ◽  
Lauren Terhorst ◽  
Andrew Nabasny ◽  
Tracey Wallace ◽  
Jennifer A. Weaver ◽  
...  
Keyword(s):  
Brain Injury ◽  
Scoping Review ◽  
Patient Reported Outcomes ◽  
Brain Injuries ◽  
Community Dwelling ◽  
Ovid Medline ◽  
Affective Symptoms ◽  
Patient Reported ◽  
Mhealth Technology ◽  
Ecological Momentary

The purpose of our scoping review was to describe the current use of mHealth technology for long-term assessment of patient-reported outcomes in community-dwelling individuals with acquired brain injury (ABI). Following PRISMA guidelines, we conducted a scoping review of literature meeting these criteria: (1) civilians or military veterans, all ages; (2) self-reported or caregiver-reported outcomes assessed via mobile device in the community (not exclusively clinic/hospital); (3) published in English; (4) published in 2015–2019. We searched Ovid MEDLINE(R) < 1946 to 16 August 2019, MEDLINE InProcess, EPub, Embase, and PsycINFO databases for articles. Thirteen manuscripts representing 12 distinct studies were organized by type of ABI [traumatic brain injury (TBI) and stroke] to extract outcomes, mHealth technology used, design, and inclusion of ecological momentary assessment (EMA). Outcomes included post-concussive, depressive, and affective symptoms, fatigue, daily activities, stroke risk factors, and cognitive exertion. Overall, collecting patient-reported outcomes via mHealth was feasible and acceptable in the chronic ABI population. Studies consistently showed advantage for using EMA despite variability in EMA timing/schedules. To ensure best clinical measurement, research on post-ABI outcomes should consider EMA designs (versus single time-point assessments) that provide the best timing schedules for their respective aims and outcomes and that leverage mHealth for data collection.

A Low-Power Heart Rate Sensor with Adaptive Heartbeat Locked Loop

2021 ◽  
Author(s):  
Zhouchen Ma ◽  
Cheng Chen ◽  
Min Wang ◽  
Yang Zhao ◽  
Liang Ying ◽  
...  
Keyword(s):  
Heart Rate ◽  
Low Power ◽  
Rate Sensor

scholarly journals 962 Heartlight - Delivery Room Acquisition Time for a Novel Forehead Heart Rate Sensor for Newborn Resuscitation

2010 ◽  
Vol 68 ◽  
pp. 480-480
Author(s):  
C Ward ◽  
J Teoh ◽  
M Grubb ◽  
J Crowe ◽  
B Hayes-Gill ◽  
...  
Keyword(s):  
Heart Rate ◽  
Delivery Room ◽  
Acquisition Time ◽  
Newborn Resuscitation ◽  
Rate Sensor

Mobility Assistants to Support Multi-Modal Routes in Smart Cities: A Scoping Review

2021 ◽  
Vol 3 (1) ◽  
pp. 26-40
Author(s):  
Nelson Pacheco Rocha ◽  
Gonçalo Santinha ◽  
Mário Rodrigues ◽  
Carlos Rodrigues ◽  
Alexandra Queirós ◽  
...  
Keyword(s):  
Scoping Review ◽  
Early Stage ◽  
Smart Cities ◽  
Research Trends ◽  
Exclusion Criteria ◽  
Major Barrier ◽  
Stage Of Development ◽  
Electronic Search ◽  
Inclusion Results

Objectives - This study aimed to identify: (i) the current research trends related to mobility assistants to support multi-modal routes in smart cities; (ii) the types of smart cities’ data being used; (iii) the methods applied to assess the proposed solutions; and iv) the major barriers for their dissemination. Methods - An electronic search was conducted in several databases, combining relevant keywords. Then titles and abstracts were screened against inclusion and exclusion criteria. Finally, the full texts of the eligible articles were retrieved and screened for inclusion. Results - A total of 19 articles were included. These articles either propose algorithms to optimize routes planning or presenting specific applications that make use of a broad range of smart cities’ data. Conclusion - The number of included articles is very reduced when compared with the total number of articles related to smart cities, which means that the mobility assistants to support multi-modal routes are still not significant within the smart cities’ research. Moreover, most of the included articles report applications in an early stage of development, which is a major barrier for the respective dissemination.

Real-time video telemedicine applications in the emergency department: a scoping review of literature

CJEM ◽  
2017 ◽  
Vol 20 (6) ◽  
pp. 920-928 ◽  
Author(s):  
Danielle K. Kelton ◽  
Adam Szulewski ◽  
Daniel Howes
Keyword(s):  
Emergency Department ◽  
Real Time ◽  
Scoping Review ◽  
Exclusion Criteria ◽  
Current State ◽  
Study Selection ◽  
Cochrane Database ◽  
The World ◽  
Data Source ◽  
Widespread Interest

AbstractObjectivesTo collect and synthesize the literature describing the use of real-time video-based technologies to provide support in the care of patients presenting to emergency departments.Data SourceSix electronic databases were searched, including Medline, CINAHL, Embase, the Cochrane Database, DARE, and PubMed for all publications since the earliest date available in each database to February 2016.Study SelectionSelected articles were full text articles addressing the use of telemedicine to support patient care in pre-hospital or emergency department settings. The search yielded 2976 articles for review with 11 studies eligible for inclusion after application of the inclusion and exclusion criteria. A scoping review of the selected articles was performed to better understand the different systems in place around the world and the current state of evidence supporting telemedicine use in the emergency department.ConclusionsTelemedicine support for emergency department physicians is an application with significant potential but is still lacking evidence supporting improved patient outcomes. Advances in technology, combined with more attractive price-points have resulted in widespread interest and implementation around the world. Applications of this technology that are currently being studied include support for minor treatment centres, patient transfer decision-making, management of acutely ill patients and scheduled teleconsultations.

scholarly journals Research on simulation in radiography education: a scoping review protocol

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Mona Vestbøstad ◽  
Klas Karlgren ◽  
Nina Rydland Olsen
Keyword(s):  
Scoping Review ◽  
Search Strategy ◽  
Skills Training ◽  
World Health ◽  
Cochrane Library ◽  
Future Research ◽  
Design Elements ◽  
Ovid Medline ◽  
Scoping Reviews ◽  
Radiography Education

Abstract Background Today, there are fewer opportunities for health care students and staff for skills training through direct patient contact. The World Health Organization therefore recommends learning about patient safety through hands-on experience and simulation. Simulation has the potential to improve skills through training in a controlled environment, and simulation has a positive effect on knowledge and skills, and even patient-related outcomes. Reviews addressing the use of simulation across the different radiography specialties are lacking. Further knowledge on simulation in radiography education is needed to inform curriculum design and future research. The purpose of this scoping review is to explore, map, and summarize the extent, range, and nature of published research on simulation in radiography education. Methods We will follow the methodological framework for scoping reviews originally described by Arksey and O’Malley. We will search the MEDLINE, Embase, Epistemonikos, The Cochrane Library, ERIC, Scopus, and sources of grey literature. A comprehensive search strategy for Ovid MEDLINE was developed in collaboration with a research librarian. An example of a full electronic search from the Ovid MEDLINE (1641 articles records, January 9, 2020) is provided and will be used to adapt the search strategy to each database. Two independent review authors will screen all abstracts and titles, and full-text publications during a second stage. Next, they will extract data from each included study using a data extraction form informed by the aim of the study. A narrative account of all studies included will be presented. We will present a simple numerical analysis related to the extent, nature, and distribution of studies, and we will use content analysis to map the different simulation interventions and learning design elements reported. Any type of simulation intervention within all types of radiography specializations will be included. Our search strategy is not limited by language or date of publication. Discussion An overview of publications on simulation in radiography education across all radiography specialties will help to inform future research and will be useful for stakeholders within radiography education using simulation, both in the academic and clinical settings. Systematic review registration Open Science Framework (OSF). Submitted on October 18, 2020

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