scholarly journals Design of an Obstacle and Location-Based Detector with Microcontroller System

2021 ◽  
Vol 5 (2) ◽  
pp. 55-62
Author(s):  
Adedotun O. Owojori ◽  
Jane O. O. Mebawondu ◽  
Jacob O. Mebawondu
Keyword(s):  
Visually Impaired ◽  
Detection System ◽  
Feedback Mechanism ◽  
Obstacle Detection ◽  
World Health ◽  
C Programming Language ◽  
Impaired Patient ◽  
C Programming ◽  
Health Organization ◽  
Efficient Power

Out of seven billion of the world’s population, two billion and two million that amounts to 31.43% have visual impairment or blindness according to the World Health Organization (WHO) statistics report. Hence, the need to develop a wearable device with reduced size, efficient power usage, and for more comfortability of the visually impaired or blind people. This work aims at designing an obstacle detection system using an ultrasonic sensor interfaced with an Arduino board to track location, alert patient, and send location messages of visually impaired patient to guardians as a feedback mechanism using a GPRS and GSM module. The C programming language was used as the instruction code to interface Arduino device to carry out given tasks. At the design level, the circuit was first tested on Proteus software for simulation purposes before its hardware implementation. The results obtained from the test show the variation of distance as the patient approaches the obstacle, and messages received when a fix was obtained. This design concept would help reduce danger across the way of those with sight defects and allow them to go to familiar places without any aid smoothly.

scholarly journals Object Identification and Safe Route Recommendation Based on Human Flow for the Visually Impaired

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5343 ◽  
Author(s):  
Yusuke Kajiwara ◽  
Haruhiko Kimura
Keyword(s):  
Visually Impaired ◽  
Object Identification ◽  
Obstacle Detection ◽  
World Health ◽  
Detection Methods ◽  
Monocular Camera ◽  
Visually Impaired People ◽  
Average Accuracy ◽  
Impaired People ◽  
Health Organization

It is difficult for visually impaired people to move indoors and outdoors. In 2018, world health organization (WHO) reported that there were about 253 million people around the world who were moderately visually impaired in distance vision. A navigation system that combines positioning and obstacle detection has been actively researched and developed. However, when these obstacle detection methods are used in high-traffic passages, since many pedestrians cause an occlusion problem that obstructs the shape and color of obstacles, these obstacle detection methods significantly decrease in accuracy. To solve this problem, we developed an application “Follow me!”. The application recommends a safe route by machine learning the gait and walking route of many pedestrians obtained from the monocular camera images of a smartphone. As a result of the experiment, pedestrians walking in the same direction as visually impaired people, oncoming pedestrians, and steps were identified with an average accuracy of 0.92 based on the gait and walking route of pedestrians acquired from monocular camera images. Furthermore, the results of the recommended safe route based on the identification results showed that the visually impaired people were guided to a safe route with 100% accuracy. In addition, visually impaired people avoided obstacles that had to be detoured during construction and signage by walking along the recommended route.

Design and Construction of a Posterior Walker for Older Adults “Moviclinic”

2020 ◽  
Author(s):  
Gianina Garrido Silva ◽  
Juan Manuel Arguello Espinosa ◽  
Jessica Gissella Maradey Lázaro ◽  
Geidy Alexandra Bayona Velasco ◽  
Angela Dayana Suescun Mejia
Keyword(s):  
Older Adults ◽  
Mobile Devices ◽  
Design Thinking ◽  
Detection System ◽  
Obstacle Detection ◽  
Assistive Devices ◽  
World Health ◽  
Element Analysis ◽  
Peace Of Mind ◽  
Health Organization

Abstract In recent years, the population of older adults (i.e age over 65) will double from 11% to 22% according to statistics from the World Health Organization (i.e WHO). The assistive devices for gait (i.e Assistive Devices and Mobility Aids, ADMA) allow the movement and mobility of people with reduced abilities to walk, providing additional support of the human body to the ground. Some authors have classified these devices as fixed and mobile. Fixed devices are made up of parallel bars or handrails and mobile devices that include walking sticks, crutches, and walkers. Especially, mobile devices allow the gait to be carried out by leaning on the device so that the patient will have greater stability and balance; as well as autonomy on regular terrain. Likewise, these reduce the risk of complications such as falls and immobilizations, which greatly improves the patient’s functionality and in rehabilitation can help to reduce pain in the muscles and joints by redistributing weight. The “Moviclinic” rear walker is made up of a metal frame, equipped with forearm support and a front safety stop, which provides security for the user and his family. The rear wheels allow to direct the element and with the front wheels regulates the speed. Besides, it has an obstacle detection system which is based on the ultrasound principle, generating an audible alarm when detecting them with two priority levels, and the alarm system activated directly by the user. This feature always allows both the user and his family or caregiver to have peace of mind at all the times. Electronic design is also included. This article aims to show the design, construction and validation of a support device for elderly patients with gait disturbances called “Moviclinic” based on the application of the “Design Thinking” methodology, Finite Element Analysis (FEA) and a technological surveillance analysis to make a comparison with current walkers and be able to offer a quality, efficient and affordable product. Finally, the test protocols carried out and the results obtained when testing their operation.

scholarly journals The use of geocoding for home healthcare application and management an epidemic situation: Case of COVID-19 virus outbreak

2020 ◽  
Vol 24 (4) ◽  
pp. 285-293
Author(s):  
Ahmed Akakba ◽  
Belkacem Lahmar
Keyword(s):  
Social Contact ◽  
Decision Makers ◽  
Home Healthcare ◽  
World Health ◽  
C Programming Language ◽  
Spatial Approach ◽  
The Social ◽  
C Programming ◽  
Healthcare Application ◽  
Health Organization

The lack of an addressing system is one of the problems of urban management in Algeria, which makes it hard to find the addresses concerned, especially in case of crisis where the decision-makers need accurate data in real-time. Like many countries, Algeria follows up the world health organization guidelines that declared the COVID-19 virus as pandemic and recommended the full quarantine and reduces the social contact as much as possible; however, these procedures weren't enough to control the increasing number of confirmed cases, which exceeded the hospital's capacities. To face up the outbreak of this pandemic, the Algerian health professionals decided to treat most coronavirus cases at home. This study aims to use a geocoding tool developed in C# programming language and ArcGIS Software Development Kit (SDK) to help in the epidemiological control operation in Ain Touta city and simplifies the interventions using a spatial approach. These problems are addressed by a tool to collect, analyze, store, and process archiving of the geographic data using a geodatabase server.

scholarly journals Leading causes of blindness and visual impairment in the region of Eastern Herzegovina

2006 ◽  
Vol 59 (1-2) ◽  
pp. 15-18 ◽  
Author(s):  
Lala Ceklic ◽  
Slobodanka Latinovic ◽  
Petar Aleksic
Keyword(s):  
Visual Impairment ◽  
Visually Impaired ◽  
Age Distribution ◽  
Epidemiological Studies ◽  
Population Based ◽  
World Health ◽  
Visual Disability ◽  
Common Causes ◽  
Health Organization ◽  
Blind Persons

Introduction. Visual impairment and blindness are serious social and health problems in the world. 1992 classification of visual disorders by World Health Organization has recently been implemented. The goal of this study was to determine common causes of visual impairment and blindness in the region of Eastern Herzegovina. Material and methods. In this population based study we have analyzed medical records stored in the regional Association of Visually Impaired and Blind Persons of the Republic of Srpska (Trebinje, Bileca, Foca, Eastern Sarajevo). The analysis included sex and age distribution of registered population, classification and leading causes of visual disability and blindness. Results. There are 298 registered persons with visual disability and blindness in the region of Eastern Herzegovina and Eastern Sarajevo. The prevalence of visual impairment and blindness in the aforementioned region is 0.1%. Among the studied population, there are more males than females with visual disability or blindness (56% versus 44%). Most (78%) of registered persons are blind, and only 22% are visually impaired. 43% of registered population are in the IV category and only 8.38% are registered in the II category. Only 2% of registered population are children. Common causes of visual disability and blindness in the region of Eastern Herzegovina are: glaucoma (22%), cataract (17%), myopia alta (13%), diabetic retinopathy (12%) and ocular trauma (11%). Common causes of children's visual impairment include: optic nerve anomalies, congenital cataract and premature retinopathy. Discussion and conclusion Compared with literature data, common causes of blindness and visual impairment in the region of Eastern Herzegovina do not differ significantly from those in other regions. Registration is based on the WHO model, but it is possible only by performing active epidemiological studies. .

scholarly journals Machine Learning based Human Fall Detection System

2021 ◽  
Vol 9 (VI) ◽  
pp. 2677-2682
Author(s):  
Nishanth P
Keyword(s):  
Machine Learning ◽  
Detection System ◽  
Wearable Sensors ◽  
Fall Detection ◽  
The Elderly ◽  
World Health ◽  
Support Vector ◽  
Data Output ◽  
Health Organization ◽  
Context Features

Falls have become one of the reasons for death. It is common among the elderly. According to World Health Organization (WHO), 3 out of 10 living alone elderly people of age 65 and more tend to fall. This rate may get higher in the upcoming years. In recent years, the safety of elderly residents alone has received increased attention in a number of countries. The fall detection system based on the wearable sensors has made its debut in response to the early indicator of detecting the fall and the usage of the IoT technology, but it has some drawbacks, including high infiltration, low accuracy, poor reliability. This work describes a fall detection that does not reliant on wearable sensors and is related on machine learning and image analysing in Python. The camera's high-frequency pictures are sent to the network, which uses the Convolutional Neural Network technique to identify the main points of the human. The Support Vector Machine technique uses the data output from the feature extraction to classify the fall. Relatives will be notified via mobile message. Rather than modelling individual activities, we use both motion and context information to recognize activities in a scene. This is based on the notion that actions that are spatially and temporally connected rarely occur alone and might serve as background for one another. We propose a hierarchical representation of action segments and activities using a two-layer random field model. The model allows for the simultaneous integration of motion and a variety of context features at multiple levels, as well as the automatic learning of statistics that represent the patterns of the features.

scholarly journals Development of the Troponin Detection System Based on the Nanostructure

Micromachines ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 203 ◽  
Author(s):  
Taek Lee ◽  
Jae-Hyuk Ahn ◽  
Jinha Choi ◽  
Yeonju Lee ◽  
Jin-Myung Kim ◽  
...  
Keyword(s):  
Detection System ◽  
Surface Enhanced Raman Spectroscopy ◽  
The Body ◽  
World Health ◽  
Detection Techniques ◽  
Number Of Patients ◽  
Creatine Kinase Mb ◽  
High Death ◽  
Surface Enhanced Raman ◽  
Health Organization

During the last 30 years, the World Health Organization (WHO) reported a gradual increase in the number of patients with cardiovascular disease (CVD), not only in developed but also in developing countries. In particular, acute myocardial infarction (AMI) is one of the severe CVDs because of the high death rate, damage to the body, and various complications. During these harmful effects, rapid diagnosis of AMI is key for saving patients with CVD in an emergency. The prompt diagnosis and proper treatment of patients with AMI are important to increase the survival rate of these patients. To treat patients with AMI quickly, detection of a CVD biomarker at an ultra-low concentration is essential. Cardiac troponins (cTNs), cardiac myoglobin (cMB), and creatine kinase MB are typical biomarkers for AMI detection. An increase in the levels of those biomarkers in blood implies damage to cardiomyocytes and thus is related to AMI progression. In particular, cTNs are regarded as a gold standard biomarker for AMI diagnosis. The conventional TN detection system for detection of AMI requires long measurement time and is labor-intensive and tedious. Therefore, the demand for sensitive and selective TN detection techniques is increasing at present. To meet this demand, several approaches and methods have been applied to develop a TN detection system based on a nanostructure. In the present review, the authors reviewed recent advances in TN biosensors with a focus on four detection systems: (1) An electrochemical (EC) TN nanobiosensor, (2) field effect transistor (FET)-based TN nanobiosensor, (3) surface plasmon resonance (SPR)-based TN nanobiosensor and (4) surface enhanced Raman spectroscopy (SERS)-based TN nanobiosensor.

scholarly journals Smart helmet using internet of things

2021 ◽  
Vol 10 (2) ◽  
pp. 90
Author(s):  
Mohamed A. Torad
Keyword(s):  
Emergency Department ◽  
Internet Of Things ◽  
Detection System ◽  
Electrical Signal ◽  
Piezoelectric Sensors ◽  
World Health ◽  
The World ◽  
Health Organization ◽  
Tracking Device ◽  
Accident Detection

The rate of death relative to the size of the world's population has remained constant, according to the world health organization (WHO). WHO targets to minimize the ratio of road death to the half by 2022. This paper discusses a way for accident detection and notification which can decrease this ratio. Piezoelectric sensors used inside a helmet to detect degree of trauma which interpret into electrical signal that used to determine if trauma is serious or not based on predetermined threshold. This trauma can be a result of any type of accidents. So, a detection system established to request immediate help from relatives and emergency department by sending SMS to them contains the longitude and latitude. In normal mode helmet can work as tracking device for the relatives.

Sign in / Sign up

Export Citation Format

Share Document