Heart activity is obtained thanks to a sensorized garment with a small incorporated device which sends ECG in a safe way and in real-time to our ECG BRAIN, located in a high-security data centre, where patient parameters are analyzed and a wide range of heart diseases are detected, such as arrhythmia, angina or heart attack.

COPCAR has complete integration with emergency services, so if it detects a serious disorder, such as a heart attack, the system generates an alert which arrives to emergency services automatically in a totally automated way.

As well as ECG analysis, COPCAR is also able to detect abnormal behaviour in the patient’s daily activity, by warning of a potentially risky situation if necessary.

Real-time remote monitoring eliminates human intervention in serious cases, by shortening reaction times enormously, from the moment first symptoms are detected until the patient is treated by emergency services. Without using a remote monitoring system, these times are estimated at 136 minutes, which enormously reduce the probability of a positive diagnose in serious cases of arrhythmia or myocardial infarction.

Thanks to ECG Brain and GPS location, COPCAR is able to send a medical attention unit to the patient’s position in a totally automated way, in an estimated time of 16 minutes.

Furthermore, the use of COPCAR also provides benefits in terms of economic savings for public administrations and private centers, since it avoids unnecessary displacements and other costs.

 

 

Bluetooth

Ila Class (93/42/CEE directive)

€50

• Minder registers electrocardiographic (ECG) signals of 3 derivations which guarantee a three-dimensional heart vision. • 250 Hz sampling frequency and 2,4 μV resolution. • Bandwidth: from 0.05 Hz to 100 Hz. • CA dynamic range: 10 mV p-p. • CC dynamic range: 300 mV. • CC dynamic range: 300 mV. • A1 Class IEC 601-1 Class and Type. CF type interface supply. • Ila Class (93/42/CEE directive). • CE certificate: ES11/10300. • Notified Organism: 2120 SGS. • Wireless communication link with PC: Bluetooth v2.0 +EDR, I Class (+18 dBm, 2.4 GHz). • The device also monitors physical activity parameters thanks to its triaxial accelerometer which obtains the activity index and body position (angles). • Dimensions: 83.5 mm x 50 mm x 20.5 mm. • Weight with battery: 68 g. • Rechargeable lithium ion battery.

 

Heart activity is obtained thanks to a sensorized garment with a small incorporated device which sends ECG in a safe way and in real-time to our ECG BRAIN, located in a high-security data centre, where patient parameters are analyzed and a wide range of heart diseases are detected, such as arrhythmia, angina or heart attack.

COPCAR has complete integration with emergency services, so if it detects a serious disorder, such as a heart attack, the system generates an alert which arrives to emergency services automatically in a totally automated way.

As well as ECG analysis, COPCAR is also able to detect abnormal behaviour in the patient’s daily activity, by warning of a potentially risky situation if necessary.

• App compatible with Android 2.1 devices or higher. • Simple and intuitive design. • Data transmission in a safe way by using specific communication protocols. • GPS location at all times. • Remote monitoring. • Local monitoring in the event of there no being coverage.

 

ECG Brain is the component tasked to analyze and diagnose the patient’s cardiovascular state, by detecting a wide range of heart diseases, such as arrhythmia, angina or heart attack.

ECG Brain intelligence lies in the implementation of detection algorithms which have been designed based on the knowledge and experience base provided by our specialist cardiologists.Moreover, we constantly update our processes through our R&D&Idepartment.

• Central processing application, analysis and diagnose and alarm generation. • Resident in the Walhalla high security Data Center in Castellón, one of the few centers which possess the Tier IV certification. • Equipped with clinical knowledge of specialist cardiologists. • Design and implementation of their own algorithms for stabilization and improvement of electrocardiographic signals and for the detection of heart abnormalities. • Use of statistic methods, HRV algorithms and artificial intelligence techniques. • Continuous improvement and update of algorithms with information coming from the scientific, medical and academic community. • Automated integration with the fress112 platform for the universal access to emergency services.a.