Monitoring (medicine)

An anesthetic machine with integrated systems for monitoring of several vital parameters, including blood pressure and heart rate.

Monitoring of vital parameters can include several of the ones mentioned above, and most commonly include at least blood pressure and heart rate, and preferably also pulse oximetry and respiratory rate. Multimodal monitors that simultaneously measure and display the relevant vital parameters are commonly integrated into the bedside monitors in critical care units, and the anesthetic machines in operating rooms. These allow for continuous monitoring of a patient, with medical staff being continuously informed of the changes in general condition of a patient. Some monitors can even warn of pending fatal cardiac conditions before visible signs are noticeable to clinical staff, such as atrial fibrillation or premature ventricular contraction (PVC).

Sensors of medical monitors include biosensors and mechanical sensors. For example, photodiode is used in pulse oximetry, Pressure sensor used in Non Invasive bood pressure measurement.

The translating component of medical monitors is responsible for converting the signals from the sensors to a format that can be shown on the display device or transferred to an external display or recording device.

Physiological data are displayed continuously on a CRT, LED or LCD screen as data channels along the time axis, They may be accompanied by numerical readouts of computed parameters on the original data, such as maximum, minimum and average values, pulse and respiratory frequencies, and so on.

Besides the tracings of physiological parameters along time (X axis), digital medical displays have automated numeric readouts of the peak and/or average parameters displayed on the screen.

Modern medical display devices commonly use digital signal processing (DSP), which has the advantages of miniaturization, portability, and multi-parameter displays that can track many different vital signs at once.

Old analog patient displays, in contrast, were based on oscilloscopes, and had one channel only, usually reserved for electrocardiographic monitoring (ECG). Therefore, medical monitors tended to be highly specialized. One monitor would track a patient's blood pressure, while another would measure pulse oximetry, another the ECG. Later analog models had a second or third channel displayed on the same screen, usually to monitor respiration movements and blood pressure. These machines were widely used and saved many lives, but they had several restrictions, including sensitivity to electrical interference, base level fluctuations and absence of numeric readouts and alarms.

Several models of multi-parameter monitors are networkable, i.e., they can send their output to a central ICU monitoring station, where a single staff member can observe and respond to several bedside monitors simultaneously. Ambulatory telemetry can also be achieved by portable, battery-operated models which are carried by the patient and which transmit their data via a wireless data connection.

Digital monitoring has created the possibility, which is being fully developed, of integrating the physiological data from the patient monitoring networks into the emerging hospital electronic health record and digital charting systems, using appropriate health care standards which have been developed for this purpose by organizations such as IEEE and HL7. This newer method of charting patient data reduces the likelihood of human documentation error and will eventually reduce overall paper consumption. In addition, automated ECG interpretation incorporates diagnostic codes automatically into the charts. Medical monitor's embedded software can take care of the data coding according to these standards and send messages to the medical records application, which decodes them and incorporates the data into the adequate fields.

Long-distance connectivity can avail for telemedicine, which involves provision of clinical health care at a distance.

A medical monitor can also have the function to produce an alarm (such as using audible signals) to alert the staff when certain criteria are set, such as when some parameter exceeds of falls the level limits.

An entirely new scope is opened with mobile carried monitors, even such in sub-skin carriage. This class of monitors delivers information gathered in body-area networking (BAN) to e.g. smart phones and implemented autonomous agents.

When monitoring a clinical parameters, differences between test results (or values of a continuously monitored parameter after a time interval) can reflect either (or both) an actual change in the status of the condition or a test-retest variability of the test method.

In practice, the possibility that a difference is due to test-retest variability can almost certainly be excluded if the difference is larger than a predefined "critical difference". This "critical difference" (CD) is calculated as:[2]

${\displaystyle CD=K\times {\sqrt {CV_{a}^{2}+CV_{i}^{2}}}}$

, where:[2]

• K, is a factor dependent on the preferred probability level. Usually, it is set at 2.77, which reflects a 95% prediction interval, in which case there is less than 5% probability that a test result would become higher or lower than the critical difference by test-retest variability in the absence of other factors.
• CV_a is the analytical variation
• CV_i is the intra-individual variability

For example, if a patient has a hemoglobin level of 100 g/L, the analytical variation (CV_a) is 1.8% and the intra-individual variability CV_i is 2.2%, then the critical difference is 8.1 g/L. Thus, for changes of less than 8 g/L since a previous test, the possibility that the change is completely caused by test-retest variability may need to be considered in addition to considering effects of, for example, diseases or treatments.

Critical differences for other tests include early morning urinary albumin concentration, with a critical difference of 40%.[2]

In a clinical laboratory, a delta check is a laboratory quality control method that compares a current test result with previous test results of the same person, and detects whether there is a substantial difference, as can be defined as a critical difference as per previous section, or defined by other pre-defined criteria. If the difference exceeds the pre-defined criteria, the result is reported only after manual confirmation by laboratory personnel, in order to exclude a laboratory error as a cause of the difference.[4]

The development cycle in medicine is extremely long, up to 20 years, because of the need for U.S. Food and Drug Administration (FDA) approvals, therefore many of monitoring medicine solutions are not available today in conventional medicine.

The PASCAL Dynamic Contour Tonometer. A monitor for detection of increased intraocular pressure.

Blood glucose monitoring

In vivo blood glucose monitoring devices can transmit data to a computer that can assist with daily life suggestions for lifestyle or nutrition and with the physician can make suggestions for further study in people who are at risk and help prevent diabetes mellitus type 2 .[10]

Stress monitoring

Bio sensors may provide warnings when stress levels signs are rising before human can notice it and provide alerts and suggestions.[11] Deep neural network models using photoplethysmography imaging (PPGI) data from mobile cameras can assess stress levels with a high degree of accuracy (86%).[12]

Serotonin biosensor

Future serotonin biosensors may assist with mood disorders and depression.[13]

Continuous blood test based nutrition

In the field of evidence-based nutrition, a lab-on-a-chip implant that can run 24/7 blood tests may provide a continuous results and a computer can provide nutrition suggestions or alerts.

Psychiatrist-on-a-chip

In clinical brain sciences drug delivery and in vivo Bio-MEMS based biosensors may assist with preventing and early treatment of mental disorders

Epilepsy monitoring

In epilepsy, next generations of long-term video-EEG monitoring may predict epileptic seizure and prevent them with changes of daily life activity like sleep, stress, nutrition and mood management.[14]

Toxicity monitoring

Smart biosensors may detect toxic materials such mercury and lead and provide alerts.[15]