LuSi is a lung simulator used for NICU (neonatal intensive care unit) medical training and teaching. LuSi is suitable for all simulation-based training for NICU staff, from crisis resource management, high-fidelity skills training and best-practices training, to knobology drills, error recognition, and error reduction.
What does LuSi include?
LuSi is comprised of a mechanical lung model with wireless electronic control built into a realistic, 2500 g baby body, which is constructed from skillfully hand-painted silicone. The baby’s airways are accessible via the nostrils, which enables trainees and teachers to insert nasal endotracheal tubes and nasal prongs and carry out high-flow oxygen therapy.
The airway opening leads to a lung compartment complete with both lung compliance and resistance. The lungs are able to take tidal volumes up to 35 ml, and pressures of up to 50 mbar. Users can render the lungs fully recruited or collapsed with integrated motors, depending on the pathology needed for the simulation. Additionally, users are able to create variable and programmable respiratory activities.
Airflow resistance is adjustable, and the integrated pressure, oxygen and volume sensors are capable of measuring level of therapy given to the simulated pediatric patient, while the integrated microprocessor calculates real-time outcome parameters such as venous admixture and pre-ductal and arterial oxygenation.
What simulation experience does LuSi offer NICU staff and trainees?
LuSi offers a fully immersive simulation experience for NICU trainees and teachers, with real-time data being transferred wirelessly to a monitor, where it is shown as wave forms and trends, including ECG, SpO2 plethysmogram, capnogram, respiratory impedance curves and transcutaneous PCO2. Adding to the authentic simulation is the blood pressure, heart rate and temperature display, and access to blood gas values and spirometric data allows to obtain lab data with timing determined by the trainer.
LuSi comes programmed with LuSiLIFE: a scenario building, PC-based program that facilitates the fast execution of pre-assembled simulation scenarios, loading patient case libraries, ad-hoc changes when they are needed, note-taking capabilities so that trainees and teachers can remember certain incidents for debriefing, and complete data recording for post-simulation analysis. Patient cases can readily be imported and exported for sharing with other LuSi users, with all data made completely transparent in .JSON format.
LuSi connects to any laptop through a bluetooth connection and can be used in the NICU hospital setting or in training facilities outside of the NICU hospital setting without requiring any additional equipment or setup. LuSi is entirely tetherless and wireless.
LuSi can also be calibrated to take into account any sensor drift and inaccuracies, and calibration is an entirely automatic process, creating a pass or fail report for quality assurance records.
The tables below offer a complete list of LuSi’s features.
- Sensor Data measured (Sensor Data)
- Parameters to configure LuSi (Control Parameters)
- Measured and calculated variables (Resulting Outcome)
- Technical data available for quality assurance (Technical Data).
Figure 1 illustrates the technical components seen in LuSi.
Figure 1. Components comprising LuSi, the baby lung simulator for NICU staff and training. The physiological models are built into the microprocessor, including a respiratory control center that adjusts inspiratory pressure and respiratory rate to maintain the PaCO2 set by the user. Image Credit: neosim AG
Sensor data
The built-in sensors constantly measure the data detailed below.
Table 1. Source: neosim AG
| Sensor/Signal |
Range |
| Lung volume, VL (measured at 200 Hz) |
0 to 200.00 |
| Alveolar pressure, Palv (measured at 200 Hz) |
+/- 60.0 |
| Airway pressure, Paw (measured at 200 Hz) |
+/- 60.0 |
| Alveolar PO2 (measured at 200 Hz) |
100 to 1100 mbar |
| Patient position |
|
Control parameters
The parameters set out below are set by the operator and define LuSi's pathologies. The parameters can be influenced by either the physiological model, or that pre-set by the user. This decision is at the discretion of the trainer, who should use the parameters in bold in the table below.
Autonomous is defined as model-based (simulates gas exchange), and central respiratory PaCO2 control refers to the built-in respiratory center (simulates central breath control).
Table 2. Source: neosim AG
| Control Parameter |
Range |
Autonomous or user |
| Airways resistance, Rtot (mbar/(L/s)) |
20..40, 30..45,45..65,60..115,250..350 |
user set |
| Expected FRC (ml) |
10 to 100 |
user set |
| Degree of lung collapse (%) |
0 to 100 |
both |
| Recruitability (ml/mbar) |
0 to 10 |
user set |
| Recruitability threshold (mbar) |
0 to 50 |
user set |
| Recruitment time constant (sec) |
1 to 30 |
user set |
| Lung collapse threshold ( mbar) |
0 to 50 |
user set |
| Lung collapse time constant (sec) |
1 to 30 |
user set |
| P/V curve (24 combinations) |
0 to 30 |
both |
| Total respiratory compliance Crs (ml/mbar) |
0.8 to 1.9 |
both |
| Chest wall compliance (ml/mbar) |
1 to 50 |
user set |
| Lower inflection point LIP (ml) |
0 to 60 |
user set |
| Compliance below LIP (ml/mbar) |
fixed value at 0.2 |
user set |
| Upper inflection point UIP (ml) |
fixed value at 25 |
user set |
| Compliance above UIP ( ml/mbar) |
fixed value at 0.2 |
user set |
| Maximal volume change (ml) |
1 to 100 |
both |
| Airways dead space (ml) |
1 to 20 |
user set |
| Alveolar dead space ventilation (%) |
0 to 100 |
user set |
| Diffusion limitation (Torr) |
40 to 800 |
user set |
| Total blood volume (ml) |
100 to 1000 |
user set |
| Cardiac Output (ml/min) |
50 to 1000 |
user set |
| BP sys (Torr) |
0 to 200 |
user set |
| BP dia (Torr) |
0 to 200 |
user set |
| BP mean (Torr) |
0 to 200 |
user set |
| Plethysmogram Variation (%/mbarPpl) |
0 to 100 |
user set |
| Pulse rate (/min) |
0 to 360 |
both |
| Pulse variability (%) |
0 to 100 |
both |
| Central bradycardia (/min) |
0 to -50 |
user set |
| O2 diss.curve shift DP50 (Torr) |
+/-20 |
user set |
| Fetal Hb (%) |
0 to 100 |
user set |
| CO2 production (ml/min STPD) |
0 to 60 |
user set |
| Patent ductus arteriosus (%) |
0 to 100 |
user set |
| Inspiratory effort Pinsp (mbar) |
0 to 35 |
both |
| Inspiratory curve form |
square, exponential, sinusoidal, linear |
user set |
| Variation of Pinsp (mbar) |
0 to 10 |
both |
| Respiratory Rate (/min) |
5 to 120 |
both |
| Variation of Resp.Rate (%) |
0 to 100 |
user set |
| Expiratory wave form |
square, exponential, sinusoidal, grunting |
user set |
| Sigh rate (/hour at 2* Pinsp) |
0 to 60 |
user set |
| Expiratory muscle tone (% Pinsp) |
0 to 50 |
user set |
| Apnea rate (/h) |
0 to 60 |
user set |
| Variation Apnea Rate (%) |
0 to 100 |
user set |
| Apnea time (sec) |
0 to 100 |
user set |
| Variation Apnea Time (%) |
0 to 100 |
user set |
| Gas exchange control |
user set or autonomous |
user set |
| Base Excess (mEq/L) |
-40 to +40 |
user set |
| Temperature (Degree C) |
20 to 44 |
user set |
| PtcCO2 Bias (mmHg) |
-20 to +20 |
user set |
| Central respiratory PaCO2 control |
user set or autonomous |
user set |
| Leak (on, off) |
2 values |
user set |
| Capnometer T90 |
20 to 500 |
user set |
| O2 Saturation pre-ductal (%) |
30 to 100 |
both |
| O2 Saturation post-ductal (%) |
30 to 100 |
both |
| PaCO2 (mmHg) |
5 to 100 |
both |
| Arterial pH |
6.5 to 8.0 |
both |
| End-tidal CO2 (mmHg) |
0 to 100 |
both |
| Movement artifacts |
0-10 |
user set |
| Added dead space (ml) |
0 to 20 |
user set |
Resulting outcome
The real-time data detailed below has been calculated based on the actually measured sensor data and the entered parameters using physiological models.
Table 3. Source: neosim AG
| Sensor/Signal |
Range |
| Pleural pressure, Pes (calculated based on Palv and Cw) |
+/- 60.0 |
| PeCO2 (calculated) |
0 to 150.0 |
| Plethysmogramm (calculated) |
0 to 100 |
| ECG (calculated) |
0 to 100 |
| Chest Impedance (calculated) |
0 to 100 |
The following data is measured breath-by-breath for use by the physiological models and is displayed on the vital signs monitor:
Table 4. Source: neosim AG
| Breath-by-breath measurements |
Range |
| FO2 |
0 to 100 |
| Lung volume (VL_ee) |
0 to 200.00 |
| PaO2 |
0 to 1100 |
| Vt |
0 to 100.00 |
| RR |
0 to 100 |
| Pmax in mbar |
0 to 100 |
| Pmin in mbar |
0 to 100 |
| V’A |
0 to 500 ml/min |
| Patient Pitch |
Degrees |
| Patient Roll |
Degrees |
The data in the table below is being calculated breath-by-breath using the physiological models built into LuSi and using the constantly measured data:
Table 5. Source: neosim AG
| Breath-by-breath calculations |
Range |
| TLV in ml |
0 to 300 |
| Vbellows_EE |
0 to 200.00 |
| SvO2 |
0 too 100 |
| SpO2 pre-ductal |
0 to 100.0 |
| SpO2 arterial |
0 to 100.0 |
| etCO2 |
0 to 150 |
| Pmin in mbar |
0 to 100 |
| V’A |
0 to 500 ml/min |
| pH |
6.00 to 8.00 |
| CollapsedLung |
0 to 100 |
| Pulse rate |
0 to 300 |
| QsQt |
0 to 100 |
| PtcCO2 |
0 to 300.0 |
The NICU trainer pre-sets the following additional data in order to complete the clinical simulation. It remains unchanged by the physiological model.
Table 6. Source: neosim AG
| Trainer set data for display |
Range |
| Temperature |
20 to 50 |
| BPsys |
0 to 300 |
| BPdia |
0 to 300 |
| BPmean |
0 to 300 |
The LuSiLIFE virtual vital-signs monitor receives continuous wireless data from LuSi. Vital signs are displayed in real-time as curves, trends, and in numeric format, too. NICU trainers are able to decide what data is displayed or not displayed as they need, depending on the simulation they are using with NICU staff. Because of this, more real-world situations can be simulated, such as the the availability or sudden failure of sensors, enriching the simulation experience.
Table 7. Source: neosim AG
| Vital signs displayed |
Format |
| ECG |
real-time curve |
| pre-ductal SpO2 plethysmogram |
real-time curve |
| SpO2 plethysmogram |
real-time curve |
| respiratory impedance |
real-time curve |
| end-tidal CO2 |
real-time curve |
| pulse |
numeric and trend curve |
| pre-ductal SpO2 |
numeric and trend curve |
| arterial SpO2 |
numeric and trend curve |
| respiratory rate |
numeric and trend curve |
| etCO2 |
numeric and trend curve |
| transcutaneous PCO2 |
numeric and trend curve |
| non-invasive SBP |
number and past values |
| non-invasive DBP |
number and past values |
| non-invasive MBP |
number and past values |
| temperature |
number |
NICU trainers and trainees are able to configure the vital signs’ position, color and presence. As a result, the vital signs monitor can be replicated for optimal training effects in order to best represent real-world NICU conditions.
Technical data
The data set out in the table below is generated and measured for technical service and quality management purposes.
Table 8. Source: neosim AG
| Technical information |
Range |
| Calibration status |
0 or 1 |
| Battery status |
0 to 100 |
| Motor Temperature |
-100 to +100 |
| HW status |
16 bit coded |
| LuSi Hardware Version |
0 to 100 |
| LuSi Firmware Version |
0 to 100 |
| LuSi use time in minutes |
0 to 100000 |
About neosim AG
neosim is a Swiss company founded by experts with strong background in lung physiology and mechanical ventilation of intensive care patients. The mission of neosim is to bring high-fidelity physiology and pathophysiology to the patient simulator community.
For training and education of clinicians, especially respiratory therapists and intensive care professionals, neosim simulators create realistic breathing in health and disease. In contrast to other simulators, neosim’s simulators can be treated with intensive care therapy methods and responds like a real human patient. The result manifests itself clinically and can be measured quantitatively with state-of-the-art monitoring in real-time.
Sponsored Content Policy: News-Medical.net publishes articles and related content that may be derived from sources where we have existing commercial relationships, provided such content adds value to the core editorial ethos of News-Medical.Net which is to educate and inform site visitors interested in medical research, science, medical devices and treatments.