Fall Detection System for the Elderly Based on the Classification of Shimmer Sensor Prototype Data

Moiz Ahmed,Nadeem Mehmood,Adnan Nadeem,Amir Mehmood,Kashif Rizwan 대한의료정보학회 2017 Healthcare Informatics Research Vol.23 No.3

Objectives: Falling in the elderly is considered a major cause of death. In recent years, ambient and wireless sensor platforms have been extensively used in developed countries for the detection of falls in the elderly. However, we believe extra efforts are required to address this issue in developing countries, such as Pakistan, where most deaths due to falls are not even reported. Considering this, in this paper, we propose a fall detection system prototype that s based on the classification on real time shimmer sensor data. Methods: We first developed a data set, ‘SMotion’ of certain postures that could lead to falls in the elderly by using a body area network of Shimmer sensors and categorized the items in this data set into age and weight groups. We developed a feature selection and classification system using three classifiers, namely, support vector machine (SVM), Knearest neighbor (KNN), and neural network (NN). Finally, a prototype was fabricated to generate alerts to caregivers, health experts, or emergency services in case of fall. Results: To evaluate the proposed system, SVM, KNN, and NN were used. The results of this study identified KNN as the most accurate classifier with maximum accuracy of 96% for age groups and 93% for weight groups. Conclusions: In this paper, a classification-based fall detection system is proposed. For this purpose, the SMotion data set was developed and categorized into two groups (age and weight groups). The proposed fall detection system for the elderly is implemented through a body area sensor network using third-generation sensors. The evaluation results demonstrate the reasonable performance of the proposed fall detection prototype system in the tested scenarios.

Integrated Power Optimization with Battery Friendly Algorithm in Wireless Capsule Endoscopy

Mehmood, Tariq,Naeem, Nadeem,Parveen, Sajida International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.11

The recently continuous enhancement and development in the biomedical side for the betterment of human life. The Wireless Body Area Networks is a significant tool for the current researcher to design and transfer data with greater data rates among the sensors and sensor nodes for biomedical applications. The core area for research in WBANs is power efficiency, battery-driven devices for health and medical, the Charging limitation is a major and serious problem for the WBANs.this research work is proposed to find out the optimal solution for battery-friendly technology. In this research we have addressed the solution to increasing the battery lifetime with variable data transmission rates from medical equipment as Wireless Endoscopy Capsules, this device will analyze a patient's inner body gastrointestinal tract by capturing images and visualization at the workstation. The second major issue is that the Wireless Endoscopy Capsule based systems are currently not used for clinical applications due to their low data rate as well as low resolution and limited battery lifetime, in case of these devices are more enhanced in these cases it will be the best solution for the medical applications. The main objective of this research is to power optimization by reducing the power consumption of the battery in the Wireless Endoscopy Capsule to make it battery-friendly. To overcome the problem we have proposed the algorithm for "Battery Friendly Algorithm" and we have compared the different frame rates of buffer sizes for Transmissions. The proposed Battery Friendly Algorithm is to send the images on average frame rate instead of transmitting the images on maximum or minimum frame rates. The proposed algorithm extends the battery lifetime in comparison with the previous baseline proposed algorithm as well as increased the battery lifetime of the capsule.

Soft b-separation axioms in neutrosophic soft topological structures

Arif Mehmood Khattak,Nazia Hanif,Fawad Nadeem,Muhammad Zamir,박춘길,Giorgio Nordo 원광대학교 기초자연과학연구소 2019 ANNALS OF FUZZY MATHEMATICS AND INFORMATICS Vol.18 No.1

The idea of neutrosophic set was floated by Smarandache by supposing a truth membership, an indeterminacy membership and a falsehood or falsity membership functions. Neutrosophic soft sets bonded by Maji have been utilized successfully to model uncertainty in several areas of application such as control, reasoning, pattern recognition and computer vision. The first aim of this article bounces the idea of neutrosophic soft b-open set, neutrosophic soft b-closed sets and their properties. Also the idea of neutrosophic soft b-neighborhood and neutrosophic soft b-separation axioms in neutrosophic soft topological structures are also reflected here. Later on the important results are discussed related to these newly defined concepts with respect to soft points. The concept of neutrosophic soft b-separation axioms of neutrosophic soft topological spaces is diffused in different results with respect to soft points. Furthermore, properties of neutrosophic soft b-$T^i$-space $(i = 0, 1, 2, 3,4)$ and some linkage between them are discussed.

Ensemble-classifiers-assisted detection of cerebral microbleeds in brain MRI

Ateeq, Tayyab,Majeed, Muhammad Nadeem,Anwar, Syed Muhammad,Maqsood, Muazzam,Rehman, Zahoor-ur,Lee, Jong Weon,Muhammad, Khan,Wang, Shuihua,Baik, Sung Wook,Mehmood, Irfan Elsevier 2018 Computers & electrical engineering Vol.69 No.-

<P>Cerebral Microbleeds (CMBs) are considered as an essential indicator in the diagnosis of critical cerebrovascular diseases such as ischemic stroke and dementia. Manual detection of CMBs is prone to errors due to complex morphological nature of CMBs. In this paper, an efficient method is presented for CMB detection in Susceptibility-Weighted Imaging (SWI) scans. The proposed framework consists of three phases: i) brain extraction, ii) extraction of initial candidates based on threshold and size based filtering, and iii) feature extraction and classification of CMBs from other healthy tissues in order to remove false positives using Support Vector Machine, Quadratic Discriminant Analysis (QDA) and ensemble classifiers. The proposed technique is validated on a dataset of 20 subjects with CMBs that consists of 14 subjects for training and 6 subjects for testing. QDA classifier achieved the best sensitivity of 93.7% with 56 false positives per patient and 5.3 false positives per CMB. (C) 2018 Elsevier Ltd. All rights reserved.</P>

Implementation of Class-Based Low Latency Fair Queueing (CBLLFQ) Packet Scheduling Algorithm for HSDPA Core Network

( Sohail Ahmed ),( Malik Muhammad Asim ),( Nadeem Qaisar Mehmood ),( Mubashir Ali ),( Babar Shahzaad ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.2

To provide a guaranteed Quality of Service (QoS) to real-time traffic in High-Speed Downlink Packet Access (HSDPA) core network, we proposed an enhanced mechanism. For an enhanced QoS, a Class-Based Low Latency Fair Queueing (CBLLFQ) packet scheduling algorithm is introduced in this work. Packet classification, metering, queuing, and scheduling using differentiated services (DiffServ) environment was the points in focus. To classify different types of real-time voice and multimedia traffic, the QoS provisioning mechanisms use different DiffServ code points (DSCP).The proposed algorithm is based on traffic classes which efficiently require the guarantee of services and specified level of fairness. In CBLLFQ, a mapping criterion and an efficient queuing mechanism for voice, video and other traffic in separate queues are used. It is proved, that the algorithm enhances the throughput and fairness along with a reduction in the delay and packet loss factors for smooth and worst traffic conditions. The results calculated through simulation show that the proposed calculations meet the QoS prerequisites efficiently.

Recent advancements in supercapacitor technology

Raza, Waseem,Ali, Faizan,Raza, Nadeem,Luo, Yiwei,Kim, Ki-Hyun,Yang, Jianhua,Kumar, Sandeep,Mehmood, Andleeb,Kwon, Eilhann E. Elsevier 2018 Nano energy Vol.52 No.-

<P><B>Abstract</B></P> <P>Supercapacitors (SCs) are attracting considerable research interest as high-performance energy storage devices that can contribute to the rapid growth of low-power electronics (e.g., wearable, portable electronic devices) and high-power military applications (e.g., guided missile techniques and highly sensitive naval warheads). The performance of SCs can be assessed in terms of the electrochemical properties determined through a combination between the electrode and the electrolyte materials. Likewise, the charge storage capacities of SCs can be affected significantly by selection of such materials (e.g., via surface redox mechanisms). Enormous efforts have thus been put to make them more competitive with existing options for energy storage such as rechargeable batteries. This article reviews recent advances in SC technology with respect to charge storage mechanisms, electrode materials, electrolytes (e.g., particularly paper/fiber-like 3D porous structures), and their practical applications. The challenges and opportunities associated with the commercialization of SCs are also discussed.</P> <P><B>Highlights</B></P> <P> <UL> <LI> There has been great demand for a reliable technical platform for electrochemical storage. </LI> <LI> SCs are highly attractive option due to their fast storage capability and enhanced cyclic stability. </LI> <LI> This review covers the charge storage mechanisms of SCs along with comparison of selected SCs. </LI> <LI> We also discuss the technical challenges for developing SCs with high enough energy density. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Characterization and Comparative Evaluation of Milk Protein Variants from Pakistani Dairy Breeds

Iqra Yasmin,Rabia Iqbal,Atif Liaqat,Wahab Ali Khan,Muhamad Nadeem,Aamir Iqbal,Muhammad Farhan Jahangir Chughtai,Syed Junaid Ur Rehman,Saima Tehseen,Tariq Mehmood,Samreen Ahsan,Saira Tanweer,Saima Naz 한국축산식품학회 2020 한국축산식품학회지 Vol.40 No.5

The aim of study was to scrutinize the physicochemical and protein profile of milk obtained from local Pakistani breeds of milch animals such as Nilli-Ravi buffalo, Sahiwal cow, Kajli sheep, Beetal goat and Brela camel. Physicochemical analysis unveiled maximum number of total solids and protein found in sheep and minimum in camel. Buffalo milk contains the highest level of fat (7.45%) while camel milk contains minimum (1.94%). Ash was found maximum in buffalo (0.81%) and sheep (0.80%) while minimum in cow’s milk (0.71%). Casein and whey proteins were separated by subjecting milk to isoelectric pH and then analyzed through sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE). The results showed heterogeneity among these species. Different fractions including αS1, αS2, κ-casein, β-casein and β-lactoglobulen (β-Lg) were identified and quantitatively compared in all milk samples. Additionally, this electrophoretic method after examining the number and strength of different protein bands (αS1, αS2, β- CN, α-LAC, BSA, and β-Lg, etc.), was helpful to understand the properties of milk for different processing purposes and could be successfully applied in dairy industry. Results revealed that camel milk was best suitable for producing allergen free milk protein products. Furthermore, based on the variability of milk proteins, it is suggested to clarify the phylogenetic relationships between different cattle breeds and to gather the necessary data to preserve the genetic fund and biodiversity of the local breeds. Thus, the study of milk protein from different breed and species has a wide range of scope in producing diverse protein based dairy products like cheese.