EB Neuro - Model NeMus 2 - Polyvalent and Innovative System for Neurological Diagnosis
From Neurodiagnostics - EMG & EP
NeMus 2 is an innovative polyvalent system designed to meet neurological diagnostic needs. The integration of advanced hardware component technology and innovative software provides high-quality signal recording, user-friendly and flexible software, and expandable features. The system is available in three configurations (trolley, all-in-one, portable) with different dimensions to adapt to several clinical environments. The multi-modal system includes the Galileo NT Line applicative software to perform clinical exams such as Electromyography (EMG), Electroneurography (ENG), Evoked Potentials (EP), Electroencephalography (EEG), Video EEG, Intensive Care Unit (ICU) monitoring.
Main Characteristics
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Bipolar high dynamic recording channels for EMG/NCS
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Monopolar channels for all kinds of EP/ERP and for EEG/VEEG acquisition
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High signal quality (low noise, high sensitivity for a large dynamic, high CMRR)
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Wide band for EEG and EMG channels
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Integrated five channels electrical stimulator
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Integrated acoustic and visual stimulators for all kinds of EP
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2 Trigger channels to be connected with external stimulators, such as TMS equipment
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Available software packages of Galileo Suite (EMG/NCS EP ERP EEG ICU, EEG/Video EEG, Cerebral Death Assessment and EEG in ICU, aEEG/CFM, EMG and NCS,
Hardware
- Upgradable number of bipolar high dynamic recording channels for EMG/NCS
- Monopolar channels for all kinds of EP/ERP and for EEG/VEEG acquisition
- Integrated five channels for electrical stimulator
- Integrated acoustic and visual stimulators for all kinds of EP
- 2 Trigger channels to be connected with external stimulators, such as TMS equipment
Software
- The Galileo application offers the possibility to create shared databases and workflows, to read the exams on other PCs in the network in the service.
- The (optional) HL7 Compatibility allows integration and communication with other software platforms for the exchange of medical data
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