A wireless IOT system towards gait detection technique using FSR sensor and wearable IOT devices

2019 ◽  
Vol 8 (1) ◽  
pp. 43-54 ◽  
Author(s):  
Sampath Dakshina Murthy Achanta ◽  
Karthikeyan T. ◽  
Vinoth Kanna R.
Keyword(s):  
Gait Analysis ◽  
Gait Recognition ◽  
Wearable Sensors ◽  
Research Work ◽  
Biomechanical Model ◽  
Communication Process ◽  
Analysis Model ◽  
Content Type ◽  
Body Sensors ◽  
Physically Challenged

Purpose The recent advancement in gait analysis combines internet of things that provides better observations of person living behavior. The biomechanical model used for elderly and physically challenged persons is related to gait-related parameters, and the accuracy of the existing systems significantly varies according to different person abilities and their challenges. The paper aims to discuss these issues. Design/methodology/approach Deployment of wearable sensors in gait analysis provides a better solution while tracking the changes of the personal style, and this proposed model uses an electronics system using force sensing resistor and body sensors. Findings Experimental results provide an average gait recognition of 95 percent compared to the existing neural network-based gait analysis model based on the walking speeds and threshold values. Originality/value The sensors are used to monitor and update the predicted values of a person for analysis. Using IoT a communication process is performed in the research work by identifying a physically challenged person even in crowded areas.

Intelligent recognition system for viewpoint variations on gait and speech using CNN-CapsNet

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
G. Merlin Linda ◽  
N.V.S. Sree Rathna Lakshmi ◽  
N. Senthil Murugan ◽  
Rajendra Prasad Mahapatra ◽  
V. Muthukumaran ◽  
...  
Keyword(s):  
Spatial Information ◽  
Intelligent System ◽  
Gait Recognition ◽  
Research Work ◽  
Recognition System ◽  
Multimodal Fusion ◽  
Content Type ◽  
Surveillance Videos ◽  
Sensor Devices ◽  
Intelligent Recognition

PurposeThe paper aims to introduce an intelligent recognition system for viewpoint variations of gait and speech. It proposes a convolutional neural network-based capsule network (CNN-CapsNet) model and outlining the performance of the system in recognition of gait and speech variations. The proposed intelligent system mainly focuses on relative spatial hierarchies between gait features in the entities of the image due to translational invariances in sub-sampling and speech variations.Design/methodology/approachThis proposed work CNN-CapsNet is mainly used for automatic learning of feature representations based on CNN and used capsule vectors as neurons to encode all the spatial information of an image by adapting equal variances to change in viewpoint. The proposed study will resolve the discrepancies caused by cofactors and gait recognition between opinions based on a model of CNN-CapsNet.FindingsThis research work provides recognition of signal, biometric-based gait recognition and sound/speech analysis. Empirical evaluations are conducted on three aspects of scenarios, namely fixed-view, cross-view and multi-view conditions. The main parameters for recognition of gait are speed, change in clothes, subjects walking with carrying object and intensity of light.Research limitations/implicationsThe proposed CNN-CapsNet has some limitations when considering for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.Practical implicationsThis research work includes for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.Originality/valueThis proposed research work proves to be performing better for the recognition of gait and speech when compared with other techniques.

Scholarly communication and possible changes in the context of social media

2011 ◽  
Vol 29 (6) ◽  
pp. 762-776 ◽  
Author(s):  
Feng Gu ◽  
Gunilla Widén‐Wulff
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Web 2.0 ◽  
Doctoral Students ◽  
Research Work ◽  
Scholarly Communication ◽  
Main Tool ◽  
Communication Process ◽  
Web 2.0 Tools ◽  
Content Type

PurposeThe focus of this paper is to study the influence of social media on scholarly communication. The aim is to provide an overview of researchers' use of Web 2.0 techniques, and discuss a possible change of information behaviors in the context of scholarly communication.Design/methodology/approachA web survey was distributed to a targeted sample of university staff (professors, teachers, researchers, and doctoral students). SPSS was utilized as a main tool to synthesize and analyze data, and present the results.FindingsWeb 2.0 tools are well‐known to researchers. Most researchers are familiar with blogs, wikis, social networks, multimedia sharing, and online document. Social media provide a convenient environment for scholarly communication. Depending on different aims within the scholarly communication process, researchers choose appropriate modes of communication in their research work.Research limitations/implicationsA combination of content analysis with survey and/or interviews may highlight other aspects of Web 2.0, which is not possible using a single method of content analysis.Originality/valueThere are few studies on the changes of scholarly communication in the context of Web 2.0. This study provides new insights for exploring the effects of Web 2.0 tools on scholarly communication and the development of new information behavior to match the scholarly environment of social media. This understanding can aid the researchers to keep abreast of new characteristics of scholarly communication and help the librarians to develop the correlative services in the scholarly environment of social media.

COVID-19 prediction and symptom analysis using wearable sensors and IoT

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Karthickraja R. ◽  
Kumar R. ◽  
Kirubakaran S. ◽  
Jegan Antony Marcilin L. ◽  
Manikandan R.
Keyword(s):  
Wearable Sensors ◽  
Research Work ◽  
Data Retrieval ◽  
Human Interaction ◽  
Rate Variation ◽  
Chi Square ◽  
Content Type ◽  
Clinical Therapy ◽  
Cloud Server ◽  
Iot Devices

Purpose The purpose of the research work is to focus on the deployment of wearable sensors in addressing symptom Analysis in the Internet of Things (IoT) environment to reduce human interaction in this epidemic circumstances. Design/methodology/approach COVID-19 pandemic has distracted the world into an unaccustomed situation in the recent past. The pandemic has pulled us toward data harnessing and focused on the digital framework to monitor the COVID-19 cases seriously, as there is an urge to detect the disease, wearable sensors aided in predicting the incidence of COVID-19. This COVID-19 has initiated many technologies like cloud computing, edge computing, IoT devices, artificial intelligence. The deployment of sensor devices has tremendously increased. Similarly, IoT applications have witnessed many innovations in addressing the COVID-19 crisis. State-of-the-art focuses on IoT factors and symptom features deploying wearable sensors for predicting the COVID-19 cases. The working model incorporates wearable devices, clinical therapy, monitoring the symptom, testing suspected cases and elements of IoT. The present research sermonizes on symptom analysis and risk factors that influence the coronavirus by acknowledging the respiration rate and oxygen saturation (SpO2). Experiments were proposed to carry out with chi-Square distribution with independent measures t-Test. Findings IoT devices today play a vital role in analyzing COVID-19 cases effectively. The research work incorporates wearable sensors, human interpretation and Web server, statistical analysis with IoT factors, data management and clinical therapy. The research is initiated with data collection from wearable sensors, data retrieval from the cloud server, pre-processing and categorizing based on age and gender information. IoT devices contribute to tracking and monitoring the patients for prerequisites. The suspected cases are tested based on symptom factors such as temperature, oxygen level (SPO2), respiratory rate variation and continuous investigation, and these demographic factors are taken for analyzed based on the gender and age factors of the collected data with the IoT factors thus presenting a cutting edge construction design in clinical trials. Originality/value The contemporary study comprehends 238 data through wearable sensors and transmitted through an IoT gateway to the cloud server. Few data are considered as outliers and discarded for analysis. Only 208 data are contemplated for statistical examination. These filtered data are proclaimed using chi-square distribution with t-test measure correlating the IoT factors. The research also interprets the demographic features that induce IoT factors using alpha and beta parameters showing the equal variance with the degree of freedom (df = 206).

scholarly journals Wearable Sensor-Based Real-Time Gait Detection: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2727
Author(s):  
Hari Prasanth ◽  
Miroslav Caban ◽  
Urs Keller ◽  
Grégoire Courtine ◽  
Auke Ijspeert ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gait Analysis ◽  
Real Time ◽  
Wearable Sensors ◽  
Pressure Sensors ◽  
Clinical Applications ◽  
Performance Comparison ◽  
Heel Strike ◽  
Rule Based ◽  
Pathological Gait

Gait analysis has traditionally been carried out in a laboratory environment using expensive equipment, but, recently, reliable, affordable, and wearable sensors have enabled integration into clinical applications as well as use during activities of daily living. Real-time gait analysis is key to the development of gait rehabilitation techniques and assistive devices such as neuroprostheses. This article presents a systematic review of wearable sensors and techniques used in real-time gait analysis, and their application to pathological gait. From four major scientific databases, we identified 1262 articles of which 113 were analyzed in full-text. We found that heel strike and toe off are the most sought-after gait events. Inertial measurement units (IMU) are the most widely used wearable sensors and the shank and foot are the preferred placements. Insole pressure sensors are the most common sensors for ground-truth validation for IMU-based gait detection. Rule-based techniques relying on threshold or peak detection are the most widely used gait detection method. The heterogeneity of evaluation criteria prevented quantitative performance comparison of all methods. Although most studies predicted that the proposed methods would work on pathological gait, less than one third were validated on such data. Clinical applications of gait detection algorithms were considered, and we recommend a combination of IMU and rule-based methods as an optimal solution.

scholarly journals Diabetes classification application with efficient missing and outliers data handling algorithms

2021 ◽  
Author(s):  
Hanaa Torkey ◽  
Elhossiny Ibrahim ◽  
EZZ El-Din Hemdan ◽  
Ayman El-Sayed ◽  
Marwa A. Shouman
Keyword(s):  
Deep Learning ◽  
Healthcare System ◽  
Wearable Sensors ◽  
Model Performance ◽  
Analysis Model ◽  
Human Errors ◽  
Web Based ◽  
Machine Learning Model ◽  
Complete Dataset ◽  
Smart Wearable

AbstractCommunication between sensors spread everywhere in healthcare systems may cause some missing in the transferred features. Repairing the data problems of sensing devices by artificial intelligence technologies have facilitated the Medical Internet of Things (MIoT) and its emerging applications in Healthcare. MIoT has great potential to affect the patient's life. Data collected from smart wearable devices size dramatically increases with data collected from millions of patients who are suffering from diseases such as diabetes. However, sensors or human errors lead to missing some values of the data. The major challenge of this problem is how to predict this value to maintain the data analysis model performance within a good range. In this paper, a complete healthcare system for diabetics has been used, as well as two new algorithms are developed to handle the crucial problem of missed data from MIoT wearable sensors. The proposed work is based on the integration of Random Forest, mean, class' mean, interquartile range (IQR), and Deep Learning to produce a clean and complete dataset. Which can enhance any machine learning model performance. Moreover, the outliers repair technique is proposed based on dataset class detection, then repair it by Deep Learning (DL). The final model accuracy with the two steps of imputation and outliers repair is 97.41% and 99.71% Area Under Curve (AUC). The used healthcare system is a web-based diabetes classification application using flask to be used in hospitals and healthcare centers for the patient diagnosed with an effective fashion.

Zn diffusion and reflow behaviour of Sn-9Zn and Sn-8.5Zn-0.5Ag-0.01Al-0.1Ga solders on a Ni/Cu substrate under IR reflow

2014 ◽  
Vol 26 (2) ◽  
pp. 87-95 ◽  
Author(s):  
J. Mittal ◽  
K.L. Lin
Keyword(s):  
Theoretical Calculations ◽  
Research Work ◽  
Content Type ◽  
Diffusion Behavior ◽  
Zn Diffusion ◽  
Cu Substrate ◽  
Practical Applications ◽  
Substrate Interface ◽  
Solder Balls ◽  
Practical Implications

Purpose – This paper aims to compare the reflow and Zn diffusion behaviors in Sn-Zn and Sn-8.5Zn-0.5Ag-0.01Al-0.1Ga (5E) solders during soldering on a Ni/Cu substrate under infrared (IR) reflow. The study proposes a model on the effect of various elements particularly Zn diffusion behavior in the solders on the formation of intermetallic compounds (IMCs). Design/methodology/approach – The melting activities of two solders near their melting points on copper substrates are visualized in an IR reflow furnace. Reflowed solder joints were analyzed using scanning electron microscope and energy dispersive X-ray spectroscopy. Findings – Reflow behaviors of the solders are similar. During melting, solder balls are first merged into each other and then reflow on the substrate from top to bottom. Both solders show a reduced amount of Zn in the solder. Theoretical calculations demonstrate a higher Zn diffusion in the 5E solder; however, the amount of Zn actually observed at the solder/substrate interface is lower than Sn-9Zn solder due to the formation of ZnAg3 in the solder. A thinner IMC layer is formed at the interface in the 5E solder than the Sn-Zn solder. Research limitations/implications – The present work compares the 5E solder only with Sn-Zn solder. Additional research work may be required to compare 5E solder with other solders like Sn-Ag, SnAgCu, etc. to further establish its practical applications. Practical implications – The study ascertains the advantages of 5E solder over Sn-Zn solder for all practical applications. Originality/value – The significance of this paper is the understanding of the relation between reflow behavior of solders and reactivity of different elements in the solder alloys and substrate to form various IMCs and their influence on the formation of IMC layer at solder/substrate interface. Emphasis is provided for the diffusion behavior of Zn during reflow and respective reaction mechanisms.

Global food safety: determinants are Codex standards and WTO's SPS food safety regulations

2014 ◽  
Vol 11 (2) ◽  
pp. 176-191 ◽  
Author(s):  
Rajneesh Mahajan ◽  
Suresh Garg ◽  
P.B. Sharma
Keyword(s):  
Food Safety ◽  
Research Work ◽  
The Body ◽  
Successful Implementation ◽  
Processed Food ◽  
Food Sector ◽  
Content Type ◽  
Safety Regulations ◽  
Food Safety Regulations ◽  
Global Food

Purpose – The purpose of this paper is to investigate perspective in explaining how global food safety can be created through stringent implementation of Codex and World Trade Organization (WTOs) Sanitary and Phytosanitary food safety regulations and suggests the appropriate food safety system for India. Design/methodology/approach – The study has been deployed a survey questionnaire using a sample of Indian Processed food sector. In order to collect data 1,000 supply chain professional were contacted for seeking their consent to be part of the survey. Whereas total responses collected were 252 from Delhi and NCR, with response rate 25.2 percent. The data collected was empirical tested using descriptive statistics, correlation analysis, regression and ANOVA. Findings – The results and discussions indicate that all the global food safety norms laid down by WTO such as goods manufacturing practices, good hygienic practice, hazard analysis critical control point, has been developed to embody principles of safe food processing sector globally. India has also developed their food safety norms as per laid down principles by WTO. Originality/value – The present research work makes an important contribution to the body of literature on global food safety. The paper has important implications for the processed food sector since it tries to bring out practices which would help in successful implementation of global food safety standards. It is useful for academic food research as well as for processed food corporate.

scholarly journals Knowledge-based Lean Six Sigma maintenance system for sustainable buildings

2017 ◽  
Vol 8 (1) ◽  
pp. 109-130 ◽  
Author(s):  
Jasim Aldairi ◽  
M.K. Khan ◽  
J. Eduardo Munive-Hernandez
Keyword(s):  
Conceptual Framework ◽  
Six Sigma ◽  
Research Work ◽  
Lean Six Sigma ◽  
Rule Base ◽  
Sustainable Buildings ◽  
Sustainable Building ◽  
Content Type ◽  
Environmentally Sustainable ◽  
Knowledge Based

Purpose This paper aims to develop a knowledge-based (KB) system for Lean Six Sigma (LSS) maintenance in environmentally sustainable buildings (Lean6-SBM). Design/methodology/approach The Lean6-SBM conceptual framework has been developed using the rule base approach of KB system and joint integration with gauge absence prerequisites (GAP) technique. A comprehensive literature review is given for the main pillars of the framework with a typical output of GAP analysis. Findings Implementation of LSS in the sustainable building maintenance context requires a pre-assessment of the organisation’s capabilities. A conceptual framework with a design structure is proposed to tackle this issue with the provision of an enhancing strategic and operational decision-making hierarchy. Research limitations/implications Future research work might consider validating this framework in other type of industries. Practical implications Maintenance activities in environmentally sustainable buildings must take prodigious standards into consideration, and, therefore, a robust quality assurance measure has to be integrated. Originality/value The significance of this research is to present a novel use of hybrid KB/GAP methodologies to develop a Lean6-SBM system. The originality and novelty of this approach will assist in identifying quality perspectives while implementing different maintenance strategies in the sustainable building context.

Mapping the landscape of computer-assisted language learning: an inventory of research

2013 ◽  
Vol 10 (4) ◽  
pp. 252-269 ◽  
Author(s):  
Antigoni Parmaxi ◽  
Panayiotis Zaphiris ◽  
Salomi Papadima-Sophocleous ◽  
Andri Ioannou
Keyword(s):  
Language Learning ◽  
Research Work ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
Card Sorting ◽  
Holistic View ◽  
Content Type ◽  
Coding Scheme ◽  
Sorting Technique ◽  
Version 2.0

Purpose – The purpose of this study is to chart the development in computer-assisted language learning (CALL), by building a map of existing research work in the field. Based on a corpus of 163 manuscripts, published between January 2009 and September 2010 in four major journals devoted to CALL, it sets out to describe the range of topics covered under the umbrella of CALL and provide a holistic view of the field. Design/methodology/approach – The approach adopted in this research includes: development of the 2009-2010 CALL corpus; literature overview and initial coding scheme development; refinement of the initial coding scheme with the help of a focus group and construction of the CALL map version 1.0; refinement of the CALL map version 1.0 following a systematic approach of content analysis and development of the CALL map version 2.0; evaluation of the proposed structure and inclusiveness of all categories in the CALL map version 2.0 using card sorting technique; and finally development of the CALL map version 3.0. Findings – The research trends in the categories of the CALL map are discussed, as well as possible future directions in the field. Originality/value – This paper provides a holistic view of the field of CALL guiding both junior CALL researchers to place themselves in the field, and policy and decision makers who attempt to evaluate the current and future scholar activity in the field. Finally, it caters for more experienced researchers to focus on certain underinvestigated domains.

Application of eco-friendly natural dye obtained from Spathodea campanulata on silk using combination of mordants

2016 ◽  
Vol 27 (1) ◽  
pp. 15-21 ◽  
Author(s):  
M Kumaresan
Keyword(s):  
Large Scale ◽  
Potassium Dichromate ◽  
Ferrous Sulphate ◽  
Research Work ◽  
Natural Dye ◽  
Alkaline Media ◽  
Silk Fabric ◽  
Content Type ◽  
Wide Range ◽  
New Research

Purpose – The purpose of this paper is to extract the eco-friendly natural dye obtained from the flower of Spathodea campanulata and apply on silk fabric using combination of mordants. The fastness properties of the flower of Spathodea campanulata dyed silk fabric have been studied using different combination (1:3, 1:1 and 3:1) of various mordants, such as myrobolan: nickel sulphate, myrobolan: aluminium sulphate, myrobolan: potassium dichromate, myrobolan: ferrous sulphate and myrobolan: stannous chloride. The wash, rub, light and perspiration fastness of the dyed samples have been evaluated. Design/methodology/approach – For dyeing there are three methods are used. They are Pre mordanting, Simultaneous mordanting and Post mordanting methods. Dyed silk materials are tested by using wash fastness, rub fastness, light and perspiration fastness methods. Findings – It is found that Spathodea campanulata dye can be successfully used for the dyeing of silk to obtain a wide range colours by using various combinations of mordants. With regards to colour fastness, test samples exhibit excellent fastness to washing, rubbing, except for pre-mordanting using myrobolan: potassium dichromate combination; and good to excellent fastness to perspiration in both acidic and alkaline media. Originality/value – Availability of literature related to this work is not available. The study of combination of mordants of this natural dye on silk is a new research work and the large scale preparation is definitely very useful to the society.

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