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Patient machine interface for the control of mechanical ventilation devices.

Grave de Peralta R, Gonzalez Andino S, Perrig S - Brain Sci (2013)

Bottom Line: This is surprising since the amount of patients that might benefit from such assistance is considerably larger than the number of patients requiring BCI for motor control.To illustrate the full approach, we present data from a healthy subject, where the inspiration and expiration periods during voluntary breathing were discriminated with a 92% accuracy (10-fold cross-validation) from the scalp EEG data.The paper ends with a discussion on the advantages and obstacles that can be forecasted in this novel application of the concept of BCI.

View Article: PubMed Central - PubMed

Affiliation: Electrical Neuroimaging Group, Albert Gos 18, Geneva 1206, Switzerland. rolando.grave@electrical-neuroimaging.ch.

ABSTRACT
The potential of Brain Computer Interfaces (BCIs) to translate brain activity into commands to control external devices during mechanical ventilation (MV) remains largely unexplored. This is surprising since the amount of patients that might benefit from such assistance is considerably larger than the number of patients requiring BCI for motor control. Given the transient nature of MV (i.e., used mainly over night or during acute clinical conditions), precluding the use of invasive methods, and inspired by current research on BCIs, we argue that scalp recorded EEG (electroencephalography) signals can provide a non-invasive direct communication pathway between the brain and the ventilator. In this paper we propose a Patient Ventilator Interface (PVI) to control a ventilator during variable conscious states (i.e., wake, sleep, etc.). After a brief introduction on the neural control of breathing and the clinical conditions requiring the use of MV we discuss the conventional techniques used during MV. The schema of the PVI is presented followed by a description of the neural signals that can be used for the on-line control. To illustrate the full approach, we present data from a healthy subject, where the inspiration and expiration periods during voluntary breathing were discriminated with a 92% accuracy (10-fold cross-validation) from the scalp EEG data. The paper ends with a discussion on the advantages and obstacles that can be forecasted in this novel application of the concept of BCI.

No MeSH data available.


Related in: MedlinePlus

Main indications for mechanical ventilation in the intensive care unit (ICU). The causes leading to the need for mechanical ventilation are much more varied than the causes leading to motor paralysis. Therefore, the amount of patients that might benefit from a patient ventilator interface is considerably larger than the number of patients that might benefit from a motor oriented Brain Computer Interface.
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brainsci-03-01554-f001: Main indications for mechanical ventilation in the intensive care unit (ICU). The causes leading to the need for mechanical ventilation are much more varied than the causes leading to motor paralysis. Therefore, the amount of patients that might benefit from a patient ventilator interface is considerably larger than the number of patients that might benefit from a motor oriented Brain Computer Interface.

Mentions: Mechanical ventilation is required when there are clinical or para-clinical signs that the patient cannot maintain an airway or adequate oxygenation or ventilation [13]. Causes are multiple, ranging from chronic to acute diseases or emergency situations such as drowning or toxic effects to the CNS (Central Nervous System) caused by drugs. The leading indications for mechanical ventilation in the ICU are summarized in Figure 1 and were derived from a study of 1638 patients in eight countries [14]. The first group includes the acute respiratory distress syndrome, heart failure, pneumonia, sepsis, complications of surgery, and trauma (with each subgroup accounting for about 8% to 11% of the overall group). Neuromuscular diseases leading or not to complete paralysis can also impair the ability of respiratory muscles to impel air in/out the lungs. Examples of additional diseases requiring mechanical ventilation are: muscular dystrophies, motor neuron disease, including ALS, damage to the brain’s respiratory centers, polio, myasthenia gravis, myopathies affecting the respiratory muscles or even severe scoliosis.


Patient machine interface for the control of mechanical ventilation devices.

Grave de Peralta R, Gonzalez Andino S, Perrig S - Brain Sci (2013)

Main indications for mechanical ventilation in the intensive care unit (ICU). The causes leading to the need for mechanical ventilation are much more varied than the causes leading to motor paralysis. Therefore, the amount of patients that might benefit from a patient ventilator interface is considerably larger than the number of patients that might benefit from a motor oriented Brain Computer Interface.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4061889&req=5

brainsci-03-01554-f001: Main indications for mechanical ventilation in the intensive care unit (ICU). The causes leading to the need for mechanical ventilation are much more varied than the causes leading to motor paralysis. Therefore, the amount of patients that might benefit from a patient ventilator interface is considerably larger than the number of patients that might benefit from a motor oriented Brain Computer Interface.
Mentions: Mechanical ventilation is required when there are clinical or para-clinical signs that the patient cannot maintain an airway or adequate oxygenation or ventilation [13]. Causes are multiple, ranging from chronic to acute diseases or emergency situations such as drowning or toxic effects to the CNS (Central Nervous System) caused by drugs. The leading indications for mechanical ventilation in the ICU are summarized in Figure 1 and were derived from a study of 1638 patients in eight countries [14]. The first group includes the acute respiratory distress syndrome, heart failure, pneumonia, sepsis, complications of surgery, and trauma (with each subgroup accounting for about 8% to 11% of the overall group). Neuromuscular diseases leading or not to complete paralysis can also impair the ability of respiratory muscles to impel air in/out the lungs. Examples of additional diseases requiring mechanical ventilation are: muscular dystrophies, motor neuron disease, including ALS, damage to the brain’s respiratory centers, polio, myasthenia gravis, myopathies affecting the respiratory muscles or even severe scoliosis.

Bottom Line: This is surprising since the amount of patients that might benefit from such assistance is considerably larger than the number of patients requiring BCI for motor control.To illustrate the full approach, we present data from a healthy subject, where the inspiration and expiration periods during voluntary breathing were discriminated with a 92% accuracy (10-fold cross-validation) from the scalp EEG data.The paper ends with a discussion on the advantages and obstacles that can be forecasted in this novel application of the concept of BCI.

View Article: PubMed Central - PubMed

Affiliation: Electrical Neuroimaging Group, Albert Gos 18, Geneva 1206, Switzerland. rolando.grave@electrical-neuroimaging.ch.

ABSTRACT
The potential of Brain Computer Interfaces (BCIs) to translate brain activity into commands to control external devices during mechanical ventilation (MV) remains largely unexplored. This is surprising since the amount of patients that might benefit from such assistance is considerably larger than the number of patients requiring BCI for motor control. Given the transient nature of MV (i.e., used mainly over night or during acute clinical conditions), precluding the use of invasive methods, and inspired by current research on BCIs, we argue that scalp recorded EEG (electroencephalography) signals can provide a non-invasive direct communication pathway between the brain and the ventilator. In this paper we propose a Patient Ventilator Interface (PVI) to control a ventilator during variable conscious states (i.e., wake, sleep, etc.). After a brief introduction on the neural control of breathing and the clinical conditions requiring the use of MV we discuss the conventional techniques used during MV. The schema of the PVI is presented followed by a description of the neural signals that can be used for the on-line control. To illustrate the full approach, we present data from a healthy subject, where the inspiration and expiration periods during voluntary breathing were discriminated with a 92% accuracy (10-fold cross-validation) from the scalp EEG data. The paper ends with a discussion on the advantages and obstacles that can be forecasted in this novel application of the concept of BCI.

No MeSH data available.


Related in: MedlinePlus