35 research outputs found
System for Detection of Vital Signals with an Embedded System
Rapid advancement in the field of Embedded Systems and Wireless communications has permitted development of Revolutionary Medical Monitoring Systems and thus improving the lifestyle of patients. The system captures and analyzes the ECG signals in real time through a low cost embedded development board. The system can detect cardiac abnormalities with high precision. One of the objectives at the time of building the proposed system has been to optimize the resources, memory size and communication costs
Design of a Health Monitoring Device
Home medical monitoring systems allow care providers to reduce their patient load, but no available systems offer portable operation. This effectively tethers patients to a specific location. In conjunction with the University of Limerick, our team desiged and implemented a proof-of-concept portable medical monitor able to transfer medical data wirelessly. Our completed project supports USB and 802.11b, includes a display and basic user interface, and runs Linux, making it a highly flexible platform for future progression toward marketability
Medical microprocessor systems
The practical classes and laboratory work in the discipline "Medical microprocessor systems", performed using software in the programming environment of microprocessors Texas Instruments (Code Composer Studio) and using of digital microprocessors of the Texas Instruments DSK6400 family, and models of electrical equipment in the environment of graphical programming LabVIEW 2010.ΠΠ°Π±ΠΎΡΠ°ΡΠΎΡΠ½ΠΈΠΉ ΠΏΡΠ°ΠΊΡΠΈΠΊΡΠΌ Π· ΠΏΡΠΎΠ³ΡΠ°ΠΌΡΠ²Π°Π½Π½Ρ ΡΠ° ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ ΠΌΠ΅Π΄ΠΈΡΠ½ΠΈΡ
ΠΌΡΠΊΡΠΎΠΏΡΠΎΡΠ΅ΡΠΎΡΠ½ΠΈΡ
ΡΠΈΡΡΠ΅ΠΌ, ΡΠΊΠΈΠΉ Π²ΠΈΠΊΠ»Π°Π΄Π΅Π½ΠΎ Ρ Π½Π°Π²ΡΠ°Π»ΡΠ½ΠΎΠΌΡ ΠΏΠΎΡΡΠ±Π½ΠΈΠΊΡ Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°Ρ Π½Π°ΠΊΠΎΠΏΠΈΡΡΠ²Π°ΡΠΈ ΠΉ Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎ Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΠ²Π°ΡΠΈ ΠΎΡΡΠΈΠΌΠ°Π½Ρ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΡ Π· ΡΠ΅ΠΎΡΠ΅ΡΠΈΡΠ½ΠΎΠ³ΠΎ ΠΊΡΡΡΡ Π½Π° Π²ΡΡΡ
ΡΡΠ°Π΄ΡΡΡ
Π½Π°Π²ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡ, ΡΠΎ Ρ Π²Π°ΠΆΠ»ΠΈΠ²ΠΈΠΌ Π΄Π»Ρ ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠΈ ΠΌΠ°Π³ΡΡΡΡΡΠ² ΡΠ° Π½Π΅ΠΎΠ±Ρ
ΡΠ΄Π½ΠΎΡ Π»Π°Π½ΠΊΠΎΡ Ρ Π½Π°ΡΠΊΠΎΠ²ΠΎΠΌΡ ΠΏΡΠ·Π½Π°Π½Π½Ρ ΠΏΡΠ°ΠΊΡΠΈΡΠ½ΠΈΡ
ΠΎΡΠ½ΠΎΠ² Π±ΡΠΎΠΌΠ΅Π΄ΠΈΡΠ½ΠΎΡ Π΅Π»Π΅ΠΊΡΡΠΎΠ½ΡΠΊΠΈ.The laboratory workshop on the programming and construction of medical microprocessor systems, which is outlined in the tutorial, helps to accumulate and effectively use the information obtained from a theoretical course at all stages of the educational process, which is important for the preparation of masters and a necessary link in the scientific knowledge of the practical basics of biomedicine.ΠΠ°Π±ΠΎΡΠ°ΡΠΎΡΠ½ΡΠΉ ΠΏΡΠ°ΠΊΡΠΈΠΊΡΠΌ ΠΏΠΎ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΠΌΠΈΠΊΡΠΎΠΏΡΠΎΡΠ΅ΡΡΠΎΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ, ΠΊΠΎΡΠΎΡΡΠΉ ΠΈΠ·Π»ΠΎΠΆΠ΅Π½ Π² ΡΡΠ΅Π±Π½ΠΎΠΌ ΠΏΠΎΡΠΎΠ±ΠΈΠΈ ΠΏΠΎΠΌΠΎΠ³Π°Π΅Ρ Π½Π°ΠΊΠ°ΠΏΠ»ΠΈΠ²Π°ΡΡ ΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΈΠ· ΡΠ΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΡΡΡΠ° Π½Π° Π²ΡΠ΅Ρ
ΡΡΠ°Π΄ΠΈΡΡ
ΡΡΠ΅Π±Π½ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ°, ΡΡΠΎ Π²Π°ΠΆΠ½ΠΎ Π΄Π»Ρ ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠΈ ΠΌΠ°Π³ΠΈΡΡΡΠΎΠ² ΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΡΠΌ Π·Π²Π΅Π½ΠΎΠΌ Π² Π½Π°ΡΡΠ½ΠΎΠΌ ΠΏΠΎΠ·Π½Π°Π½ΠΈΠΈ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΎΡΠ½ΠΎΠ² Π±ΠΈΠΎΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠ½ΠΈΠΊΠΈ
Design of a Personal Health Monitor Interface for Wireless, IP-based, Data Logging
Collaborating with the Enterprise Research Centre at the University of Limerick (UL) in Ireland, we designed, developed, and implemented a proof-of-concept glucose meter adapter that allows blood glucose level readings to be securely transmitted to a remote database via existing WiFi technology. By using open source software and embedded components, we have created a highly flexible platform that allows healthcare professionals to monitor patients in near real-time. Our device aims to simplify the lifestyle of diabetics while providing new opportunities for statistical research and analysis of diabetes
Low power body sensor network design based on relaying of creeping waves in the unlicensed 2.4GHz band
Body Sensor Networks are an important enabling technology for future applications in remote medical diagnostics. Practical deployments of these systems have only recently edged closer to viability, due in part to advances in low power electronics and System-On-Chip devices. Wireless communication between these sensors remains a daunting challenge, and designers typically leverage existing industrial standards designed for applications with significantly different communications requirements. This Thesis proposes a wireless communications platform designed specifically for body mounted sensors, exploiting a phenomenon in electromagnetic wave propagation known as a creeping wave. Relaying of these waves leads to a highly reliable body sensor network with very low power consumption in the unlicensed 2.4 GHz band. A link budget is derived based on the creeping wave component of the transmitted signal, which is then used to design a spread spectrum wireless transceiver. Significant attention is given to interference mitigation, allowing the system to co-exist with other wireless devices on the internationally unlicensed band. Fading statistics from both anechoic and high multipath scenarios are used to define a channel model for the system. The link budget and channel model lead to the proposed use of relaying as a power savings technique, and this concept is a core feature of the design. This technique is shown to provide reliable total body coverage with very low transmission power, a result that has eluded body sensor networks to date. Various relaying topologies are discussed, and robust operation for highly mobile users is achieved via sensor handoffs, a concept that resembles a similar solution in cellular networks. The design extends to define a polling protocol and packet structures. Objective performance metrics are defined, and the proposed system is evaluated in line with these metrics. The power reduction of the suggested approach is analyzed by comparing the network lifetime and energy-per-bit to those of a reference system offering the same quality of service without relaying. The analysis results in generic closed form expressions of significant gains. The improvement in network lifetime increases with the number of sensors and settles at approximately 8x104, 7x106, 7x107 and 3x108 for 2,4,6 and 8 relaying nodes respectively. The energy-per-bit is shown to decrease by 2, 116, 828 and 2567 for 2, 4, 6 and 8 relay nodes respectively
Design for energy-efficient and reliable fog-assisted healthcare IoT systems
Cardiovascular disease and diabetes are two of the most dangerous diseases as they are the leading causes of death in all ages. Unfortunately, they cannot be completely cured with the current knowledge and existing technologies. However, they can be effectively managed by applying methods of continuous health monitoring. Nonetheless, it is difficult to achieve a high quality of healthcare with the current health monitoring systems which often have several limitations such as non-mobility support, energy inefficiency, and an insufficiency of advanced services. Therefore, this thesis presents a Fog computing approach focusing on four main tracks, and proposes it as a solution to the existing limitations. In the first track, the main goal is to introduce Fog computing and Fog services into remote health monitoring systems in order to enhance the quality of healthcare.
In the second track, a Fog approach providing mobility support in a real-time health monitoring IoT system is proposed. The handover mechanism run by Fog-assisted smart gateways helps to maintain the connection between sensor nodes and the gateways with a minimized latency. Results show that the handover latency of the proposed Fog approach is 10%-50% less than other state-of-the-art mobility support approaches.
In the third track, the designs of four energy-efficient health monitoring IoT systems are discussed and developed. Each energy-efficient system and its sensor nodes are designed to serve a specific purpose such as glucose monitoring, ECG monitoring, or fall detection; with the exception of the fourth system which is an advanced and combined system for simultaneously monitoring many diseases such as diabetes and cardiovascular disease. Results show that these sensor nodes can continuously work, depending on the application, up to 70-155 hours when using a 1000 mAh lithium battery.
The fourth track mentioned above, provides a Fog-assisted remote health monitoring IoT system for diabetic patients with cardiovascular disease. Via several proposed algorithms such as QT interval extraction, activity status categorization, and fall detection algorithms, the system can process data and detect abnormalities in real-time. Results show that the proposed system using Fog services is a promising approach for improving the treatment of diabetic patients with cardiovascular disease
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Wireless In-home Ecg Monitoring System with Remote Access
The thesis work details the design and testing of a wireless electrocardiogram (ECG) system. This system includes a wireless ECG device, as well as software packages to visually display the waveform locally on a computer and remotely on a web page. The remote viewing capability also extends to using an Android phone application. The purpose of the system is to serve as a means for a doctor or physician to check up on a patient away from a hospital setting. This system allows for a patient to be in their home environment while giving health vital information, primarily being the heartβs activity through the ECG, to medical personnel