scholarly journals Temporal and Hierarchical HMM for Activity Recognition Applied in Visual Medical Monitoring using a Multi-Camera System

2015 ◽  
Vol Volume 21 - 2015 - Special... ◽  
Author(s):  
Arnaud Ahouandjinou ◽  
Eugène C. Ezin ◽  
Cina Motamed
Keyword(s):  
Monitoring System ◽  
Vision System ◽  
Recognition Performance ◽  
Automatic Recognition ◽  
Medical Monitoring ◽  
Prise De Décision ◽  
Camera System ◽  
Reconnaissance Automatique ◽  
State Duration ◽  
Système De Surveillance

International audience We address in this paper an improved medical monitoring system through an automatic recognition of human activity in Intensive Care Units (ICUs). A multi camera vision system approach is proposed to collect video sequence for automatic analysis and interpretation of the scene. The latter is performed using Hidden Markov Model (HMM) with explicit state duration combine at the management of the hierarchical structure of the scenario. Significant experiments are carried out on the proposed monitoring system in a hospital's cardiology section in order to prove the need for computer-aided patient supervision to help clinicians in the decision making process. Temporal and hierarchical HMM handles explicitly the state duration and then provides a suitable solution for the automatic recognition of temporal events. Finally, the use of Temporal HMM (THMM) based approach improves the scenario recognition performance compared to the result of standard HMM models. Nous proposons dans cet article une solution pour améliorer le système actuel de surveillance médicale en Unité de Soins Intensifs (USIs) cardiologique grâce à un système de reconnaissance automatique d'activités humaines. Une approche de vidéo surveillance multicaméras est proposée à cet effet et permet l'acquisition des données pour l'analyse et l'interprétation automatique de la scène. Cette dernière est basée sur le Modèle de Markov Caché (MMC) avec une durée d'état explicite et intégrant une gestion de la structure hiérarchique interne des scénarios. Plusieurs séries d'expérimentations sont effectuées sur le nouveau système de surveillance proposé en USIs et démontre ainsi la nécessité d'une surveillance assistée par ordinateur des patients afin d'aider les médecins surveillants et les cliniciens dans le processus de prise de décision. De plus, le MMC temporel offre une solution très adaptée pour la reconnaissance automatique des événements en USIs. Enfin, les résultats obtenus avec le modèle de MMC temporel et hiérarchique ont été comparés à ceux des MMC classiques.

Implementing Internet of Things in a Remote Patient Medical Monitoring System

2018 ◽  
Vol 6 (8) ◽  
pp. 159 ◽  
Author(s):  
Ifeoma V. Ngonadi
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
Medical Records ◽  
Research Work ◽  
Healthcare Delivery ◽  
Vital Signs ◽  
Personal Digital Assistant ◽  
Computer Applications ◽  
Medical Monitoring ◽  
Remote Patient

The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Remote patient monitoring enables the monitoring of patients’ vital signs outside the conventional clinical settings which may increase access to care and decrease healthcare delivery costs. This paper focuses on implementing internet of things in a remote patient medical monitoring system. This was achieved by writing two computer applications in java in which one simulates a mobile phone called the Intelligent Personal Digital Assistant (IPDA) which uses a data structure that includes age, smoking habits and alcohol intake to simulate readings for blood pressure, pulse rate and mean arterial pressure continuously every twenty five which it sends to the server. The second java application protects the patients’ medical records as they travel through the networks by employing a symmetric key encryption algorithm which encrypts the patients’ medical records as they are generated and can only be decrypted in the server only by authorized personnel. The result of this research work is the implementation of internet of things in a remote patient medical monitoring system where patients’ vital signs are generated and transferred to the server continuously without human intervention.

SU-D-201-05: On the Automatic Recognition of Patient Safety Hazards in a Radiotherapy Setup Using a Novel 3D Camera System and a Deep Learning Framework

2016 ◽  
Vol 43 (6Part3) ◽  
pp. 3334-3335 ◽  
Author(s):  
A Santhanam ◽  
Y Min ◽  
P Beron ◽  
N Agazaryan ◽  
P Kupelian ◽  
...  
Keyword(s):  
Patient Safety ◽  
Deep Learning ◽  
Automatic Recognition ◽  
Safety Hazards ◽  
Camera System ◽  
Learning Framework ◽  
3D Camera

scholarly journals A Methodology for Multi-Camera Surface-Shape Estimation of Deformable Unknown Objects

Robotics ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 69 ◽  
Author(s):  
Evgeny Nuger ◽  
Beno Benhabib
Keyword(s):  
Particle Filtering ◽  
Surface Deformation ◽  
Vision System ◽  
Three Dimensional ◽  
Target Object ◽  
Surface Shape ◽  
Shape Estimation ◽  
Formal Approach ◽  
Camera System ◽  
Unknown Objects

A novel methodology is proposed herein to estimate the three-dimensional (3D) surface shape of unknown, markerless deforming objects through a modular multi-camera vision system. The methodology is a generalized formal approach to shape estimation for a priori unknown objects. Accurate shape estimation is accomplished through a robust, adaptive particle filtering process. The estimation process yields a set of surface meshes representing the expected deformation of the target object. The methodology is based on the use of a multi-camera system, with a variable number of cameras, and range of object motions. The numerous simulations and experiments presented herein demonstrate the proposed methodology’s ability to accurately estimate the surface deformation of unknown objects, as well as its robustness to object loss under self-occlusion, and varying motion dynamics.

Secured Communication for Remote Bio-Medical Monitoring System Using LoRa

2019 ◽  
Vol 17 (11) ◽  
pp. 888-897 ◽  
Author(s):  
Anto Merline Manoharan ◽  
Vimalathithan Rathinasabapathy
Keyword(s):  
Monitoring System ◽  
Medical Application ◽  
Vital Role ◽  
Heart Beat ◽  
Smart Phones ◽  
Elderly Persons ◽  
Medical Monitoring ◽  
Ease Of Access ◽  
4G Lte ◽  
Near Future

Recent advancement in IoT technology made profound changes in life style of people. Ease of access of information through smart phones becomes attractive. Everyone like to access datas through their smart phones. IoT enabled application fulfils this requirements. Researchers focusses on developing the Smart monitoring system using IoT. Since these IoT applications uses existing cellular network for accessing internet. Research says that 50 Billion devices will be willed worldwide in 2020. Providing connectivity to these applications is a challenging task. The existing 4G-LTE network could not support for these much number of devices. Hence an alternative IoT-LoRa network is proposed for these type of application. In this research, a special application in Bio-Medical monitoring System is developed using LoRa Communication. BioMedical Parameters like Weight, Blood Pressure, Heart beat, Body temperature are measured, encrypted using AES to provide security and transmitted using LoRa to monitoring system through Gateway. The developed system satisfies the need for elderly persons suffering from disabilities and reduces the time for the care taker to monitor the data. Also the proposed system is highly secured. Our research says, in near future IoT will play vital role in Bio Medical application and Connectivity, Security will be some of the challenging issues in implementation. Without addressing these problems, Bio-Medical Monitoring System cannot be prognosticated. Finally the potentiality of IoT in Medical field is discussed.

Quick Registration Method Based on Image Region Correlation

2014 ◽  
Vol 608-609 ◽  
pp. 555-558
Author(s):  
Na Zhu
Keyword(s):  
Monitoring System ◽  
High Speed ◽  
Vision System ◽  
Automatic Measurement ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Image Region ◽  
Registration Method ◽  
Implementation Effect ◽  
Accurate Matching

Binocular vision system can be widely used in CNC machine tools chatter monitoring, due to its simple system and automatic measurement function. Traditional registration method cannot balance the contradiction between precision and speed of registration; restrict its application in high speed monitoring system. So based on traditional feature point registration method, it proposes a new method to obtain more accurate matching feature points by using complexity distribution feature of image region to determine the distribution of feature region and the bidirectional similarity and triangle similar method, which realize quick registration. From the simulation and implementation effect perspective, this method is feasible for the image registration in high-speed monitoring system.

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