Televet 100 Telemetric ECG&Holter

TELEVET
Engel Engineering Services GmbH
3.300,00€ (ALV 0%)

Convenient ECG recordings at rest as well as during exercise!

With traditional ECG systems the veterinary surgeon has been limited to obtaining a resting ECG. With the development of Televet® the veterinary surgeon is able to monitor the animal during its normal daily activities. This allows the detection of cardiac rhythm abnormalities which may only occur during exercise or at rest.

The Televet 100 provides telemetric two channel (3 / 6 vector) ECG recording. It was developed to be used both in small and large animals. The Televet 100 conveniently allows excellent quality ECG recordings both at rest as well as during exercise.

In telemetric mode the Televet 100 transmits data in real-time. The ECG is displayed on a laptop or PC and it is stored on the hard disk. In Holter mode, data is stored on a standard SD-Card which is plugged into the ECG device for up to 30 hours. A telemetric connection to host PC or notebook is not required in this mode. Telemetric mode and Holter mode can be used in parallel, this ensures that an ECG is always recorded.

The system includes software which enables ECG recordings to be reviewed at any time, printed or e-mailed for a second opinion.

Holter Option

Record the ECG when the animal is in its common environment.

More than 24 hours of ECG data can be recorded and stored to a SD-card and later transmitted to the PC

In parallel the ECG signal can be transmitted to a laptop or PC by Bluetooth wireless technology

  • the ECG trace can be displayed ”live” on the PC screen during the animals normal daily activities
  • the ECG trace can be recorded to the hard disk of the PC or laptop

Manual analysis of large ECG files is time consuming and error prone
Analysis Software for Human medicine often inappropriate for small animals

  • Televet 100 Holter-Analysis was specially developed for small animals
  • It significantly reduce time and effort for an ECG Holter analysis. This was achieved by a semi-automatic classification approach

 

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