Impact of Medical Advancement: Prostheses

This chapter shall provide a brief introduction to the prostheses and their development in the current advance technological era. The prosthesis design, control, and architecture completely changed with the change in the amputation level. The transradial amputee stump design, electronics, battery, and circuit placement change significantly with the change of the residual arm of the amputee. This leads to designing the prostheses with the focus of the amputation level and ease of customization. Recent development in the 3D printing and open source prosthetic design leads the user to choose, modify, and print the prostheses with the required sets of functionalities. In this chapter, a brief introduction of the prostheses has been given, starting with the types of prostheses according to the level of amputation and functionality. Then, the state-of-the-art prostheses available commercially and under research will be introduced. Afterward, the 3D printed prostheses are discussed. This chapter will end with the comparison of the medical advancement over the average life of people in general and comparison of the same for countries with low and high per capita income

Muscle Mechanics and Electromyography

This chapter will begin with the introduction to biomechanics and its relationship with the physiology and anatomy. Then it introduces the basic concepts of kinematics, kinetics, and anthropometry and discusses in detail the muscle mechanics and electromyography. The muscle is the actuator of the human body, especially the skeletal muscles which are attached with the skeleton play an important role in defining the movements of the human body. The human body controls the muscle through the nervous system, and this nervous system generates signals called electroencephalogram (EEG) which upon leaving the nerves excites the muscle and converted into muscle signals usually called electromyogram (EMG). In this chapter, we will discuss the mechanics of the muscle in conjunction with the EMG. EMG is the tool to study the activity of the muscles and hence the key to understand the mechanics of the human body

”Det var en flyktzon man flydde till” : En kvalitativ studie: om föräldraskap, skolgång och socioekonomisk bakgrund är faktorer till att ungdomar utvecklar en kriminell livsstil

2024-01-08</p

”Det var en flyktzon man flydde till” : En kvalitativ studie: om föräldraskap, skolgång och socioekonomisk bakgrund är faktorer till att ungdomar utvecklar en kriminell livsstil

2024-01-08</p

Automated Camera Placement using Hybrid Particle Swarm Optimization

Context. Automatic placement of surveillance cameras&apos; 3D models in an arbitrary floor plan containing obstacles is a challenging task. The problem becomes more complex when different types of region of interest (RoI) and minimum resolution are considered. An automatic camera placement decision support system (ACP-DSS) integrated into a 3D CAD environment could assist the surveillance system designers with the process of finding good camera settings considering multiple constraints. Objectives. In this study we designed and implemented two subsystems: a camera toolset in SketchUp (CTSS) and a decision support system using an enhanced Particle Swarm Optimization (PSO) algorithm (HPSO-DSS). The objective for the proposed algorithm was to have a good computational performance in order to quickly generate a solution for the automatic camera placement (ACP) problem. The new algorithm benefited from different aspects of other heuristics such as hill-climbing and greedy algorithms as well as a number of new enhancements. Methods. Both CTSS and ACP-DSS were designed and constructed using the information technology (IT) research framework. A state-of-the-art evolutionary optimization method, Hybrid PSO (HPSO), implemented to solve the ACP problem, was the core of our decision support system. Results. The CTSS is evaluated by some of its potential users after employing it and later answering a conducted survey. The evaluation of CTSS confirmed an outstanding satisfactory level of the respondents. Various aspects of the HPSO algorithm were compared to two other algorithms (PSO and Genetic Algorithm), all implemented to solve our ACP problem. Conclusions. The HPSO algorithm provided an efficient mechanism to solve the ACP problem in a timely manner. The integration of ACP-DSS into CTSS might aid the surveillance designers to adequately and more easily plan and validate the design of their security systems. The quality of CTSS as well as the solutions offered by ACP-DSS were confirmed by a number of field experts.Sarmad Rohani: 004670606805 Reza Shams: 004670403089

Automated Camera Placement using Hybrid Particle Swarm Optimization

Context. Automatic placement of surveillance cameras&apos; 3D models in an arbitrary floor plan containing obstacles is a challenging task. The problem becomes more complex when different types of region of interest (RoI) and minimum resolution are considered. An automatic camera placement decision support system (ACP-DSS) integrated into a 3D CAD environment could assist the surveillance system designers with the process of finding good camera settings considering multiple constraints. Objectives. In this study we designed and implemented two subsystems: a camera toolset in SketchUp (CTSS) and a decision support system using an enhanced Particle Swarm Optimization (PSO) algorithm (HPSO-DSS). The objective for the proposed algorithm was to have a good computational performance in order to quickly generate a solution for the automatic camera placement (ACP) problem. The new algorithm benefited from different aspects of other heuristics such as hill-climbing and greedy algorithms as well as a number of new enhancements. Methods. Both CTSS and ACP-DSS were designed and constructed using the information technology (IT) research framework. A state-of-the-art evolutionary optimization method, Hybrid PSO (HPSO), implemented to solve the ACP problem, was the core of our decision support system. Results. The CTSS is evaluated by some of its potential users after employing it and later answering a conducted survey. The evaluation of CTSS confirmed an outstanding satisfactory level of the respondents. Various aspects of the HPSO algorithm were compared to two other algorithms (PSO and Genetic Algorithm), all implemented to solve our ACP problem. Conclusions. The HPSO algorithm provided an efficient mechanism to solve the ACP problem in a timely manner. The integration of ACP-DSS into CTSS might aid the surveillance designers to adequately and more easily plan and validate the design of their security systems. The quality of CTSS as well as the solutions offered by ACP-DSS were confirmed by a number of field experts.Sarmad Rohani: 004670606805 Reza Shams: 004670403089

Fuzzy smart framework for diagnosis of liver disorder in Rheumatoid arthritis

Despite most of the centralization techniques used in medical diagnosis, a right finding is yet considered a priority. Most of this condition is due to the fact that clinical issue requires both expertise and knowledge in managing with complexity. In this paper, we intend a fuzzy expert framework for studying and examining the risk of anemia and liver dysfunction due to the usage of drugstherapy (DMARDS) among  patients in Rhematoid arthritis. The data illustration of this system is given from a significant level, taking into account the recorded data about signs and symptoms in rheumatic patients as well as the clinical appraisal. This framework imitates the professional doctor's behavior. The system predicts the risk of anemia and liver dysfunction in patients treated with DMARDS for rheumatoid arthritis.The framework is designed in such a manner that the patient can access it individually and has correlation with other normal indicative frameworks is quicker, less expensive, and furthermore more liable and exact

Mobility and Health Monitoring in People with Different Abilities: A Prototype Enhancing Independence: Innovating an IoT-Integrated Wheelchair for

Wheelchair is an essential tool for people with disabilities, enabling them to move around independently and participate fully in society. They come in different types, such as manual wheelchairs, power wheelchairs, sports wheelchairs, and pediatric wheelchairs among others. Certain types of disabilities such as Monoplegia, Hemiplegia, Paraplegia, and Quadriplegia pose difficulties in using conventional power wheelchairs. To overcome these hurdles and provide ease to differently-abled individuals, an Advance Monitoring and Assistive Wheelchair (AMAW) is proposed in this work. The Prototype includes a voice-controlled system for controlling the movement of a wheelchair, an IoT-based real-time health monitoring system to monitor the vitals of the patient remotely, a fall detection system for detecting falls, a tracking system for position and location, and an alarm system to alert caretaker in case of a fall. The real-time embedded monitoring system allows the monitoring of the user’s vital signs like temperature, pulse rate and oxygen saturation and the assistive part allows the wheelchair to move around electronically either through voice or through mobile application.  With the assistance of various sensors, the data can easily be monitored remotely by the caretaker at regular intervals of the time. The data display on the LCD fitted onto the wheelchair and in the designed mobile application. Furthermore, the whereabouts of the user are sent via the alert system that notifies the caretaker through GSM in case of changes in parameters and if the user has lost the balance. The vitals through the sensors on the prototype has undergone testing on number of individuals with precise outcomes. In comparison to typical joystick-controlled wheelchairs, this project excels in several aspects, such as its ability to stop or turn using voice commands and avoid collisions with people, furniture, fixed objects, and walls. The user friendly AMAW prototype with real-time monitoring, assistance and alert system may serve as a cost-effective solution in maintaining and providing an independent quality life to differently-abled individuals

Detection of Crackle and Wheeze in Lung Sound using Machine Learning Technique for Clinical Decision Support System

This study aims to develop a computer-based clinical decision support system that will help clinicians and healthcare personnel to make an early and correct decision to prevent the patient from nontransmissible respiratory diseases. The main contribution of this study is to analyze, investigate, and extraction of the useful feature of pathological respiration and Classification of Crackle and Wheeze from recorded lungs sound by using machine learning techniques. In the particular spectrogram, Time-frequency and Mel-Frequency cepstral coefficient (MFCC)technique is applied for feature analysis and data conversion into a format that can be useful for feature extraction and training models. PCA dimensional reduction technique is used to reduce the dimensionality of the extracted feature. In order to apply various machine learning techniques a widely used dataset freely available dataset ICBHI-2017 is used. The respiratory lungs sound is comprised of 126 patients with 920 Chest sound annotations that include adventitious sounds such as “Crackle” and “Wheeze”. Machine learning algorithms such as MusicANN, VGGish, and OpenL3 were applied for testing the better accuracy of the classification model. The accuracy of the utilized classifier with the extracted feature set is determined as 72%, 81%, and 69% respectively