LivingLab care@home 16 09_2014
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- The document presents the Care@Home prototype for remote patient monitoring. - It monitors vital signs like heart rate, respiration rate, ECG, posture and acceleration using a BioPatch device. - The BioPatch sensor data is sent to the Omniacare remote monitoring platform which stores the clinical/diagnostic records and patient data in a database for health operator management and patient monitoring.
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This document describes a Zigbee-based patient monitoring system that measures important vital signs like temperature and heart rate from sensors attached to ICU patients. The sensor data is sent wirelessly via Zigbee modules to a receiving system that allows doctors to monitor multiple patients from anywhere in the hospital. This helps reduce the patient to doctor ratio in ICUs and ensures patients can be monitored constantly even when unconscious. The system uses an AT89S52 microcontroller, temperature and heart rate sensors, and Zigbee wireless technology to remotely monitor and alert doctors to changes in patients' conditions.
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This project monitors important body parameters like temperature, ECG, pulse using sensors connected to a processing unit interfaced with a computer. This allows doctors to remotely analyze patient conditions and reduces their workload. It also incorporates alarms for when the saline bottle is empty or if the patient needs assistance. The hardware is built on a printed circuit board with a DSPIC30F4013 processor. It interfaces with a computer via RS232. Software is compiled using Visual Basic to modify alarm settings and record data.
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The document discusses data loggers used in Indian Railways. It provides an overview of RDSO which tests railway equipment. It then discusses the signal testing laboratory and its facilities. A key point is that data loggers monitor relay activities to generate reports on the signaling system. The document describes how data is collected via sensors and sent to the data logger. It outlines the types of data loggers and their applications in Indian Railways. Areas for improvement are also noted such as measuring train load and track failures to prevent accidents.
ECG SIGNAL ACQUISITION, FEATURE EXTRACTION AND HRV ANALYSIS USING BIOMEDICAL ...
This document describes a system for acquiring electrocardiogram (ECG) signals, extracting features from the signals, and analyzing heart rate variability. The system uses Arduino hardware to amplify, filter, and digitize ECG signals. LabVIEW software interfaces with the Arduino to acquire the digital data and save it in file formats for analysis. Biomedical Workbench software then processes the ECG data, extracting features like QRS complexes and heart rate. It also performs heart rate variability analysis using time and frequency domain measures on the extracted RR intervals. The complete system provides a low-cost way to acquire, process, and analyze ECG signals.
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The heart acts as a pump that circulates oxygen and
nutrient carrying blood around the body in order to keep
it functioning. When the body is exerted the rate at which
the heart beats will vary proportional to the amount of
effort being exerted. By detecting the voltage created by
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and used for a number of health purposes. Heart pounds
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The Evity Pacemaker Series from BIOTRONIK combines small size with powerful features for diagnostics, therapy and handling. Key features include physiological rate adaptation using Closed Loop Stimulation, MRI compatibility with AutoDetect sensor, remote monitoring capabilities, and long battery life despite small size. The series provides efficient MRI access, time savings through remote monitoring, and true physiological pacing response.
A wearable device Biometric Data acquisition
This document summarizes a seminar presentation about a wearable device for acquiring biometric data for sports applications. The device uses MEMS sensors to track movement and collect biometric information like pulse rate, temperature, and more. It is designed to be worn on the wrist and uses miniature sensors, data storage, and a battery to allow for continuous monitoring during activities like tennis matches. The data is analyzed both on the device and through cloud services to provide performance analysis and insights into an athlete's physical and mental condition.
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The document describes several medical diagnostic systems and technologies from XAI MEDICA including electrocardiography (ECG/EKG), heart rate variability (HRV) analysis, electroencephalography (EEG), rheography, spirometry, telemedicine, and fetal ECG monitoring. It provides details on specific products like the CardioLab ECG system, CardioSens ECG holter monitor, NeuroCom EEG system, ReoCom bioimpedance/rheography system, and SpiroCom spirometry system. It includes information on hardware specifications, software features and interfaces for analysis, reporting and data management.
Review on crop monitoring system using GSM technology
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This document describes a project to develop a fingertip ECG acquisition system. The system aims to make ECG monitoring more portable and accessible for cardiovascular patients. It uses dry sensors on the fingertip to detect heartbeats and converts the signals to an electrical signal processed by an Arduino board. The Arduino filters and analyzes the signals to generate and display the ECG waveform. The system provides a simple, portable way to monitor heart activity without bulky equipment or gel sensors.
Final Project Slides Buchheit Harings Hussein
The document describes a cardiovascular monitoring system (CMS) that measures blood pressure, heart rate, and blood oxygen levels. It operates by using light sensors on the finger to non-invasively measure these vital signs. The data is wirelessly transmitted to a base monitor and can be viewed or programmed by a physician using software. The CMS is intended for at-home patient monitoring under a doctor's supervision. It functions similarly to previously cleared predicate devices and a comparison table shows the CMS has substantially equivalent intended use, technological characteristics, and accuracy to predicates.
Non-Contact Health Monitoring System Using Image and Signal Processing
Presently digital medical devices promise to transform the future of medicine because of their ability to produce exquisitely detailed individual physiological data. As ordinary people start to have access and control over their own physiological data so that they can play a more active role in the management of their health. Currently many techniques are available for counting our heartbeat but it all needs bundles of sensors and wires. For heartbeat measurement using Electrocardiograph(ECG) method, we have to attach a bundle of leads in our chest and have to use adhesive gel. It is very difficult to patients and it can cause irritation to the skin. Another type is pulse oximeters and sensors, in this method sensors are attached to the finger tips or earlobes. This is also difficult for user.
In case of "Non-contact health monitoring system using image and signal processing" which gives contact free measurement about our physiological information using basic image processing devices. Users have the experience of real time health monitoring by just looking into "medical mirror". It recognizes our heartbeat without any external or internal sensor and displays it in real time. This invention helps people to access their own physiological data.
IOT – Based Health Monitoring System
This document describes an IOT-based health monitoring system that measures a patient's temperature, heart rate, and oxygen levels remotely. Sensors are used to monitor these vital signs, which are sent to a microcontroller and displayed on an LCD screen and website. This allows healthcare providers to remotely track patients' conditions in real-time. The system aims to improve medical care, especially for those in rural areas or those wanting to avoid hospital visits during infectious disease outbreaks. Results showed the IOT system was low-cost, non-invasive, and flexible in monitoring health from different locations. Future work could involve adding more sensors to monitor additional physiological parameters.
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LivingLab care@home 16 09_2014
- 1. Care@Home: Allegato tecnico Presentazione: Pasquale Lannunziato @ eResult San Giovanni Rotondo (FG) 16 Settembre 2014
- 3. Patients END-USERS BioPatch Device Sensor Acquisition Station (Matrix) Omniacare Platform OMNIACARE VITAL and ENVIRONTMENTAL PARAMETER RECORDING PATIENT MONITORING PATIENT CLINICAL/DIAGNOSTIC RECORD. HEALTH OPERATOR MANAGEMENT. MPI test module DB DB Web services Web Portal Care@Home Prototype
- 4. Parametri monitorati: • Heart Rate • Respiration Rate • ECG • Posture • Acceleration 3 Axis: fall detection (CNR) Caratteristiche: • Heart Rate Range: 0-240 BPM • Posture: ± 180° • ECG Type: EC38 Type 3 ECG • Respiration Rate Range: 0-70 Breaths per minute • BioModule weight: 18 grams • BioModule dimensions: 28mm Diameter x 7mm thick • Battery Life: 24 Hours per charge Un modulo per il monitoraggio di parametri fisiologici Biopatch device
- 5. DOMESTIC SERVER LOCAL DB MAIN SERVER Program Layer MAIN DB SENSOR PLATORM RESTful / SOAP Web Services data sync get configuration write data Omniacare Platform Architecture
- 6. LOCAL DB Biopatch device SENSOR PLATORM Service Entity Framework (ORM) WS Caller Reflection loader Sensor Acquisition Station (Matrix) Omniacare Platform Architecture
- 7. SERVICE LOCAL DB DEVICE SENSOR LIBRARY •Connect(…) •GetData(…) SENSOR DEVICE Data acquire process 3. Push data Data request Data response Data acquire process 1. Get active sensors 1a. Get write policy MAIN DB check for unsent data Data acquire process 4. Write sensor data Data acquire process 2. Init sensor lifetime Data sync process 1. Get data to send Data sync process 2. Consume data write call ws WS Data sync process 3. Write data & check for alert Sensor Platform: Data acquisition
- 8. Program Layer MAIN DBWS Data sync process 3a. Write data Data sync process 3b. Raise alert check Data sync process 4. Check alert conditions Data sync process 5. Get contact info SENSOR ALERT ASSISTITO TUTOR MEDICO Data sync process 6a. Send mail 6b. Send sms Sensor Platform: Alert generation
Editor's Notes
- BioModule unit snaps into the BioModule Holder that attaches to the patient via traditional disposable ECG electrodes. Can be disinfected with standard cleaning agents