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.

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 High Performance Predictive Analytics in IoT

2019 ◽  
Vol 8 (4) ◽  
pp. 9266-9270
Keyword(s):  
Real Time ◽  
Network Architecture ◽  
High Performance ◽  
Predictive Analytics ◽  
Time Data ◽  
New Techniques ◽  
Real Time Data ◽  
Iot Devices ◽  
Indexing Technique ◽  
To Receive

Internet of things (IoT) is a quick-moving gathering of web associated sensors implanted in a wide-extending assortment of physical articles. While things can be any physical item (energize or lifeless) on the planet, to which you could associate or implant a sensor. Sensors can take countless potential estimations. Sensors produce gigantic measures of new, organized, unstructured, ongoing information, and structures enormous information. IoT information is exceptionally huge and confused, which can give genuine-time setting and supposition data about genuine articles or nature. Among the different challenges that the present IoT is facing, the three prime areas of concern are, need of efficient framework to receive IoT data, a need of a new scalable parallel indexing technique for efficiently storing IoT data and securing IoT generated data at all the stages i.e. from the edge devices to the cloud. A new efficient framework is introduced, which can retrieve meaningful information from these IoT devices and efficiently index it. For processing such enormous real time data generated from IoT devices, new techniques are introducing which are scalable and secure. The research proposes a general IoT network architecture. It describes the interconnectivity among the different things such as sensors, receivers and cloud. The proposed architecture efficiently receives real time data from all the sensors. The prime focus is on the elimination of the existing issues in IoT. Along with this, the provision has to make for standard future proofing against these new proposed schemes.

scholarly journals Enhancing the Isolation and Performance of Control Planes for Fog Computing

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3267 ◽  
Author(s):  
Kyungwoon Lee ◽  
Chiyoung Lee ◽  
Cheol-Ho Hong ◽  
Chuck Yoo
Keyword(s):  
High Performance ◽  
Fog Computing ◽  
Network Control ◽  
Optimization Techniques ◽  
Control Plane ◽  
Multiple Control ◽  
New Techniques ◽  
Iot Devices ◽  
And Performance ◽  
Network Switches

Fog computing, which places computing resources close to IoT devices, can offer low latency data processing for IoT applications. With software-defined networking (SDN), fog computing can enable network control logics to become programmable and run on a decoupled control plane, rather than on a physical switch. Therefore, network switches are controlled via the control plane. However, existing control planes have limitations in providing isolation and high performance, which are crucial to support multi-tenancy and scalability in fog computing. In this paper, we present optimization techniques for Linux to provide isolation and high performance for the control plane of SDN. The new techniques are (1) separate execution environment (SE2), which separates the execution environments between multiple control planes, and (2) separate packet processing (SP2), which reduces the complexity of the existing network stack in Linux. We evaluate the proposed techniques on commodity hardware and show that the maximum performance of a control plane increases by four times compared to the native Linux while providing strong isolation.

scholarly journals Towards Digital Twin Implementation for Assessing Production Line Performance and Balancing

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 97 ◽  
Author(s):  
Marcello Fera ◽  
Alessandro Greco ◽  
Mario Caterino ◽  
Salvatore Gerbino ◽  
Francesco Caputo ◽  
...  
Keyword(s):  
Production Line ◽  
Wearable Sensors ◽  
Numerical Data ◽  
Manufacturing Companies ◽  
Production Chain ◽  
Simulation Tools ◽  
Manual Task ◽  
Industrial Internet ◽  
Iot Devices ◽  
And Performance

The optimization of production processes has always been one of the cornerstones for manufacturing companies, aimed to increase their productivity, minimizing the related costs. In the Industry 4.0 era, some innovative technologies, perceived as far away until a few years ago, have become reachable by everyone. The massive introduction of these technologies directly in the factories allows interconnecting the resources (machines and humans) and the entire production chain to be kept under control, thanks to the collection and the analyses of real production data, supporting the decision making process. This article aims to propose a methodological framework that, thanks to the use of Industrial Internet of Things—IoT devices, in particular the wearable sensors, and simulation tools, supports the analyses of production line performance parameters, by considering both experimental and numerical data, allowing a continuous monitoring of the line balancing and performance at varying of the production demand. A case study, regarding a manual task of a real manufacturing production line, is presented to demonstrate the applicability and the effectiveness of the proposed procedure.

Trace nanoanalysis

1994 ◽  
Vol 52 ◽  
pp. 940-941
Author(s):  
D. E. Newbury ◽  
R. D. Leapman
Keyword(s):  
High Performance ◽  
Secondary Ion Mass Spectrometry ◽  
Detection Efficiency ◽  
Volume Element ◽  
And Performance ◽  
Trace Constituents ◽  
Secondary Ion ◽  
Concentration Levels ◽  
Structure Properties

Trace constituents, which can be very loosely defined as those present at concentration levels below 1 percent, often exert influence on structure, properties, and performance far greater than what might be estimated from their proportion alone. Defining the role of trace constituents in the microstructure, or indeed even determining their location, makes great demands on the available array of microanalytical tools. These demands become increasingly more challenging as the dimensions of the volume element to be probed become smaller. For example, a cubic volume element of silicon with an edge dimension of 1 micrometer contains approximately 5×1010 atoms. High performance secondary ion mass spectrometry (SIMS) can be used to measure trace constituents to levels of hundreds of parts per billion from such a volume element (e. g., detection of at least 100 atoms to give 10% reproducibility with an overall detection efficiency of 1%, considering ionization, transmission, and counting).

https://imsciences.edu.pk/files/journals/vol12_2/New%201%20MA.864.pdf

2020 ◽  
Vol 12 (2) ◽  
pp. 19-50 ◽  
Author(s):  
Muhammad Siddique ◽  
Shandana Shoaib ◽  
Zahoor Jan
Keyword(s):  
Organizational Performance ◽  
Structural Equation ◽  
High Performance ◽  
Service Sector ◽  
Performance Outcomes ◽  
Theory And Practice ◽  
Relational Coordination ◽  
Multiple Sources ◽  
And Performance ◽  
High Level

A key aspect of work processes in service sector firms is the interconnection between tasks and performance. Relational coordination can play an important role in addressing the issues of coordinating organizational activities due to high level of interdependence complexity in service sector firms. Research has primarily supported the aspect that well devised high performance work systems (HPWS) can intensify organizational performance. There is a growing debate, however, with regard to understanding the “mechanism” linking HPWS and performance outcomes. Using relational coordination theory, this study examines a model that examine the effects of subsets of HPWS, such as motivation, skills and opportunity enhancing HR practices on relational coordination among employees working in reciprocal interdependent job settings. Data were gathered from multiple sources including managers and employees at individual, functional and unit levels to know their understanding in relation to HPWS and relational coordination (RC) in 218 bank branches in Pakistan. Data analysis via structural equation modelling, results suggest that HPWS predicted RC among officers at the unit level. The findings of the study have contributions to both, theory and practice.

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 Study on strong spinning preparation method and mechanism of the industrial pure titanium ultrafine crystallization

2019 ◽  
Vol 14 ◽  
pp. 155892501989525
Author(s):  
Yu Yang ◽  
Yanyan Jia
Keyword(s):  
Heat Treatment ◽  
High Performance ◽  
Pure Titanium ◽  
Grain Structure ◽  
Theoretical Research ◽  
Ultrafine Grain ◽  
Forming Process ◽  
Spinning Process ◽  
And Performance ◽  
Material Utilization

Ultrafine crystallization of industrial pure titanium allowed for higher tensile strength, corrosion resistance, and thermal stability and is therefore widely used in medical instrumentation, aerospace, and passenger vehicle manufacturing. However, the ultrafine crystallizing batch preparation of tubular industrial pure titanium is limited by the development of the spinning process and has remained at the theoretical research stage. In this article, the tubular TA2 industrial pure titanium was taken as the research object, and the ultrafine crystal forming process based on “5-pass strong spin-heat treatment-3 pass-spreading-heat treatment” was proposed. Based on the spinning process test, the ultimate thinning rate of the method is explored and the evolution of the surface microstructure was analyzed by metallographic microscope. The research suggests that the multi-pass, medium–small, and thinning amount of spinning causes the grain structure to be elongated in the axial and tangential directions, and then refined, and the axial fiber uniformity is improved. The research results have certain scientific significance for reducing the consumption of high-performance metals improving material utilization and performance, which also promote the development of ultrafine-grain metals’ preparation technology.

scholarly journals Wearable Technologies in Field Hockey Competitions: A Scoping Review

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5242
Author(s):  
Jolene Ziyuan Lim ◽  
Alexiaa Sim ◽  
Pui Wah Kong
Keyword(s):  
Heart Rate ◽  
Inertial Sensors ◽  
Wearable Devices ◽  
Field Hockey ◽  
Heart Rate Monitors ◽  
Search Terms ◽  
Physiological Demands ◽  
And Performance ◽  
Future Work ◽  
Skin Temperatures

The aim of this review is to investigate the common wearable devices currently used in field hockey competitions, and to understand the hockey-specific parameters these devices measure. A systematic search was conducted by using three electronic databases and search terms that included field hockey, wearables, accelerometers, inertial sensors, global positioning system (GPS), heart rate monitors, load, performance analysis, player activity profiles, and competitions from the earliest record. The review included 39 studies that used wearable devices during competitions. GPS units were found to be the most common wearable in elite field hockey competitions, followed by heart rate monitors. Wearables in field hockey are mostly used to measure player activity profiles and physiological demands. Inconsistencies in sampling rates and performance bands make comparisons between studies challenging. Nonetheless, this review demonstrated that wearable devices are being used for various applications in field hockey. Researchers, engineers, coaches, and sport scientists can consider using GPS units of higher sampling rates, as well as including additional variables such as skin temperatures and injury associations, to provide a more thorough evaluation of players’ physical and physiological performances. Future work should include goalkeepers and non-elite players who are less studied in the current literature.

scholarly journals Indices of Heart Rate Variability and Performance During a Response-Conflict Task Are Differently Associated With ADHD and Autism

2021 ◽  
pp. 108705472097279
Author(s):  
Alessio Bellato ◽  
Iti Arora ◽  
Puja Kochhar ◽  
Chris Hollis ◽  
Madeleine J. Groom
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sensory Information ◽  
Response Conflict ◽  
Mediation Model ◽  
Conflict Task ◽  
Accurate Performance ◽  
And Performance ◽  
Comorbid Adhd ◽  
The Relationship

We investigated autonomic arousal, attention and response conflict, in ADHD and autism. Heart rate variability (HRV), and behavioral/electrophysiological indices of performance, were recorded during a task with low and high levels of response conflict in 78 children/adolescents (7–15 years old) with ADHD, autism, comorbid ADHD+autism, or neurotypical. ANOVA models were used to investigate effects of ADHD and autism, while a mediation model was tested to clarify the relationship between ADHD and slower performance. Slower and less accurate performance characterized ADHD and autism; however, atypical electrophysiological indices differently characterized these conditions. The relationship between ADHD and slower task performance was mediated by reduced HRV in response to the cue stimulus. Autonomic hypo-arousal and difficulties in mobilizing energetic resources in response to sensory information (associated with ADHD), and atypical electrophysiological indices of information processing (associated with autism), might negatively affect cognitive performance in those with ADHD+autism.

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