THE T-SHIRT
camiseta copcar

• Elastic and breathable tissue which allows its use for a prolonged time by picking up 3 ECG channels through its 6 incorporated sensors.
• Rear enclosure.
• Different sizes.
• Sensor composition: polyester covered with silver.
• Garment composition: 52% viscose, 43% polyamide, 5% elastane.
• Applicable community directive: 93/42/CEE, modified by 2007/47/EC directive about sanitary products. I Class.

THE DEVICE
minder, dispositivo copcar

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.

MOBILE APPLICATION
aplicacion copcar, app, monitorización remota

• 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
ecg brain copcar

• 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.