The University of British Columbia

Each new anesthesia monitor requires careful observation from the clinician to detect any abnormality, exceeding the bounds of human concentration. In addition, observing monitors limits the amount of time that clinicians can spend observing patients directly. To avoid missing an abnormality, alarms are set to attract the clinician's attention to significant state changes. Such alarms are triggered only when a potentially critical situation is imminent - they do not help track small changes in a patient's condition.
We propose to develop a new means of connecting clinicians with their patients. By bridging the gap between monitoring equipment and human attention, our device would act as a 'tap on the shoulder' prompting scrutiny of monitors at the first sign of change in their patient's conditions, allowing action to be taken before a critical situation develops. To do this without adding to the already busy streams of auditory and visual information, we propose to harness the relatively under-utilized sense of touch. Using technology developed for Virtual Reality, sensory receptors will be stimulated, via a tactile device, to provide pulses of vibration that correspond to changes in the patient. Tactile communication can provide subtle cues, rather than outright alarms. It does not detract from patient observation and will not disturb other individuals in the clinical environment. Our experiments suggest that tactile signals compete more successfully for attention than auditory ones.

A number of different monitors are attached to patients under anesthesia or in the intensive care unit. To detect an abnormality in a patient's state, the clinician must repeatedly look at the numerous monitors. As the number of monitored parameters increases, so the demands on the clinician escalate. The clinician can set simple alarm limits on each monitor to warn of a change in heart rate or a change in blood pressure. However, these alarm limits carry the problem of false alarms as they are based on a single parameter. In addition, small changes in a patient's state, within the alarm limits, are not recognized by the system.
We propose to apply methods that are used to indicate faults in engineering processes to this problem. These methods have been successfully used in other industries. We want to see if they can be used to provide better indications of faults, or abnormalities, during anesthesia and in the intensive care unit. Using advanced data processing techniques, we hope to support the role of the clinician. To improve on single parameter alarm systems, we also propose to combine multiple parameters in a single monitoring system. A sensitive multi-parameter system is essential as the number of monitors in the clinical environment continues to increase.
The benefits of the system we are proposing extend beyond the clinician's bedside diagnosis. Currently, each individual monitor collects very large amounts of physiological data. Data from the monitors may be stored for future analysis.