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J A Blom

Publications and source records attributed to J A Blom.

17 recordsLinked to original sources
PubMed1997

Evaluation of automatically learned intelligent alarm systems.

In this contribution it is investigated whether a combination of mathematical simulation and inductive machine learning can replace the usual knowledge elicitation techniques. To test this a domain was selected for which knowledge based systems had a high performance: intelligent alarm systems. A mathematical model of a breathing circuit and ventilated patient was implemented in PSpice. Airway pressure, gas flows and CO2 concentration were simulated with this model, during normal functioning of the breathing circuit and during several mishaps, for a wide range of simulated patients. With an inductive machine learning program, classification trees were created from the simulated patient data. The classification trees described each breathing circuit mishap in terms of changes in signal feature values with respect to the normal situation and were implemented as alarm system knowledge bases. The alarm systems were tested with data measured at 17 mechanically ventilated animals. During ventilation of the animals several mishaps were introduced. For each animal, 93-100% of all mishaps could be detected correctly by the alarm systems. The false alarm rate ranged on average from one false alarm per h to one false alarm every 2.5 h. It was concluded that the suggested approach to knowledge elicitation was successful.

Animals↗
PubMed1997

Clinical evaluation of an automatic blood pressure controller during cardiac surgery.

OBJECTIVE: During surgery, computers can be of great use to support the anesthesiologist in providing task automation. In this paper we describe a closed loop blood pressure controller and show the results of its clinical evaluation. METHODS: The controller is based on a simple and robust Proportional-Integral controller and a supervising, rule based, expert system. Adaptive control is necessary because the sensitivity of the patients to sodium nitroprusside varies over a wide range. Thirty-three clinical tests during cardiac surgery, including the cardiopulmonary bypass phase, were performed. RESULTS: On average the controller was in automatic mode for 90.6 +/- 9.6% of the time. The performance during automatic control showed the mean arterial pressure to be within 10 mmHg of the setpoint for 71.4 +/- 15.5% of the time. The average absolute distance to the setpoint was 8.1 +/- 7.2 mmHg. CONCLUSIONS: The overall performance of the controller was noted as very satisfactory by the anesthesiologists.

Algorithms↗
PubMed1997

Detection of dicrotic notch in arterial pressure signals.

OBJECTIVE: A novel algorithm to detect the dicrotic notch in arterial pressure signals is proposed. Its performance is evaluated using both aortic and radial artery pressure signals, and its robustness to variations in design parameters is investigated. METHODS: Most previously published dicrotic notch detection algorithms scan the arterial pressure waveform for the characteristic pressure change that is associated with the dicrotic notch. Aortic valves, however, are closed by the backwards motion of aortic blood volume. We developed an algorithm that uses arterial flow to detect the dicrotic notch in arterial pressure waveforms. Arterial flow is calculated from arterial pressure using simulation results with a three-element windkessel model. Aortic valve closure is detected after the systolic upstroke and at the minimum of the first negative dip in the calculated flow signal. RESULTS: In 7 dogs ejection times were derived from a calculated aortic flow signal and from simultaneously measured aortic flow probe data. A total of 86 beats was analyzed; the difference in ejection times was -0.6 +/- 5.4 ms (means +/- SD). The algorithm was further evaluated using 6 second epochs of radial artery pressure data measured in 50 patients. Model simulations were carried out using both a linear windkessel model and a pressure and age dependent nonlinear windkessel model. Visual inspection by an experienced clinician confirmed that the algorithm correctly identified the dicrotic notch in 98% (49 of 50) of the patients using the linear model, and 96% (48 of 50) of the patients using the nonlinear model. The position of the dicrotic notch appeared to be less sensitive to variations in algorithm's design parameters when a nonlinear windkessel model was used. CONCLUSIONS: The detection of the dicrotic notch in arterial pressure signals is facilitated by first calculating the arterial flow waveform from arterial pressure and a model of arterial afterload. The method is robust and reduces the problem of detecting a dubious point in a decreasing pressure signal to the detection of a well-defined minimum in a derived signal.

Algorithms↗
PubMed1996

Automated infusion of nitroglycerin to control arterial hypertension during cardiac surgery.

OBJECTIVE: To evaluate the feasibility of closed-loop blood pressure control during cardiac surgery. DESIGN: A closed-loop system regulated peroperative hypertension by controlling the infusion rate of the vasodilator nitroglycerin (NTG). The controller consisted of a regulator which was monitored by a supervisory computer program. Mean arterial pressure (MAP) was calculated every 5 s from measurements of the radial artery pressure signal. The regulator calculated an NTG infusion rate with each new MAP measurement. The supervisory computer program monitored the regulator's actions and adapted or overruled the regulator when required. SETTING: The cardiac surgery operating room. PATIENTS: 46 patients who were scheduled for cardiac surgery and who developed peroperative hypertension. INTERVENTIONS: Patients were scheduled for either bypass or valve replacement surgery. The closed-loop system was used to control hypertension before and after cardiopulmonary bypass. The use of the closed-loop system did not require deviation from the protocol normally used during cardiac surgery. All patients received standard continuous anaesthesia with opioids. MEASUREMENTS AND RESULTS: Initial automatic control was achieved in 9.4 (4.1 SD) min. The percentage of time that MAP remained in a range around the target MAP of +/- 10 and +/- 20 mmHg was 74 and 94%, respectively. The mean NTG infusion rate while MAP was within 5 mmHg of target MAP was 1.14 (0.84 SD) micrograms kg-1 min-1. Target MAP was set between 65 and 90 mmHg. There was a small group of patients (6 out of 46) who did not respond to NTG and required alternative drug therapy. CONCLUSIONS: The controller provided fast and stable control in all patients. The expert knowledge implemented through the supervisory computer program enabled the controller to respond adequately to the rapid changes in arterial pressures commonly associated with cardiac surgery. We conclude that closed-loop control of arterial pressure is feasible not only in the cardiac surgical care unit but also during cardiac surgery.

Adult↗
PubMed1996

Correction for respiration artifact in pulmonary blood pressure signals of ventilated patients.

OBJECTIVE: To develop an algorithm that corrects pulmonary artery pressure signals of ventilated patients for the respiration artifact. The algorithm should test the validity of the pulmonary pressure signal and differentiate between the cyclic respiration artifact and true measurement artifacts. METHODS: The shape of each pulmonary pressure beat is described by eight characteristic features, including mean pressure value and the systolic and diastolic timing and pressure values. The features are corrected for the respiration artifact by fitting them in a least-squares sense on the first and second harmonics of the ventilator frequency. The corrected features are used by a signal validation algorithm, which adds a validity flag to each pressure beat. The validation algorithm rejects pressure beats with sudden changes in their shape but adapts itself when the changes persist. RESULTS: The performance of the correction and validation technique was evaluated using pulmonary artery pressure signals of 30 patients who were scheduled for open heart surgery. The algorithm correctly recognized as invalid data those pressure signals disturbed by coagulation, surgical manipulations, or flushes of the pressure line. The algorithm marked on average 77 +/- 11% of the pulmonary pressure beats as valid. CONCLUSIONS: The validation algorithm marked sufficient pressure beats as valid to update a trend display every 5 sec. The correction algorithm enabled the validation algorithm to differentiate between true measurement artifacts and the respiration artifact.

Algorithms↗
PubMed1996

Optimal surface electrode positioning for reliable train of four muscle relaxation monitoring.

In the clinic, a major problem in train of four (TOF) muscle relaxation monitoring is incorrect placement of stimulation and recording electrodes, frequently resulting in incorrect estimates of the patient's degree of relaxation or in abandonment of relaxation monitoring. The aim of this study was to arrive at recommendations that describe how to find optimal positions for the electrodes, where 'optimal' is taken in the sense that small deviations from these positions introduce no or only a small decline in the accuracy of the computed degree of muscle relaxation. This study, which employed the Relaxograph as the stimulation and measuring device, established that incorrect positioning is a real problem that frequently occurs; that the correctness of positioning is not guaranteed when the calibration of the Relaxograph succeeds; that the inadequacy of the electrode position is sometimes discovered for the first time when relaxation deepens; that positioning errors can be discovered by analysing the shape of the evoked compound action potential (ECAP), not only upon calibration but also when relaxation deepens; that a set of optimal electrode positions can be found; and that recommendations of how to find these optimal positions could help clinicians to place the electrodes in such a way, that reliable relaxation monitoring was possible in 100% of the investigated cases. In a first test in 30 adult patients, we surveyed how clinicians routinely positioned electrodes and found that in 14 of the 30 cases positioning was unsuccessful. In a second test in 10 patients, we tested a variety of electrode positions in order to discover 'optimal' stimulation, recording and ground electrode sites. In a third test in 10 patients, electrodes were positioned at these 'optimal' sites; stimulation and recording at these sites was successful in all 10 cases.

Adult↗
PubMed1996

Building intelligent alarm systems by combining mathematical models and inductive machine learning techniques.

In this article a technique is described to develop knowledge-based alarm systems for ventilator therapy, using mathematical modeling and machine learning. With a mathematical model airway pressure, expiratory gas flow and CO2 concentration at the endotracheal tube are simulated for patients, undergoing volume-controlled ventilation with constant ventilator settings, during normal functioning of the breathing circuit and during breathing circuit mishaps (leaks and obstructions). Simulations were performed for 94 physiologically different 'patients', by varying airway resistance and lung/thorax compliance values in the model. Each simulated breath was described by a set of derived signal features and a label that constituted during which event (normal function or mishap) the breath was recorded. With an inductive machine learning algorithm rules, linking signal feature values to breathing circuit events, were created from data of 54 of the simulated patients. The resulting set of rules was able to classify 99% of events in the data of the remaining 40 patients correctly. Of signals, measured at a ventilated lung simulator, 100% of events were classified correctly.

Airway Resistance↗
PubMed1996

Building intelligent alarm systems by combining mathematical models and inductive machine learning techniques Part 2--sensitivity analysis.

In an earlier study an approach was described to generate intelligent alarm systems for monitoring ventilation of patients via mathematical simulation and machine learning. However, ventilator settings were not varied. In this study we investigated whether an alarm system could be created with which a satisfactory classification performance could be obtained under a wide variety of ventilator settings, by varying inspiratory to expiratory time (I:E) ratio, tidal volume and respiratory rate. In a first experiment three patient data sets were modeled, each with a different I:E ratio. A part of each data set was used to construct an alarm system for each I:E ratio. The remaining part was used to test the performance of the alarm systems. The three training sets were also combined to construct one alarm system, which was tested with the three test sets. Finally, all alarm systems were tested with data generated by a patient simulator. Similar experiments were performed for the tidal volume and the respiratory rate. It was concluded that an optimally functioning alarm system should contain a library of rule sets, one for each set of ventilator settings. A second best alternative is to take all possible settings into consideration when constructing the training set. Classification performance of the trees that were trained with multiple ventilator settings ranged from 98 to 100% for all test sets. When tested with the independent patient simulator data the classification performance of these trees ranged from 80 to 100%.

Airway Resistance↗
PubMed1996

OpenLabs services for ordering laboratory investigations.

An automated system is described that screens requests for laboratory investigations from GPs and delivers feedback with respect to the adequacy of the requests. The system has to replace and extend the current system in which feedback is provided on a manual basis each half year, based on the tests requested during a period of one month, randomly selected from the previous half year. It has been reported elsewhere that the manual system reduced the number of tests requested considerably. The criteria used by the automated system and the manual system are based on guidelines and work agreements that GPs have agreed to follow when requesting investigations. It is concluded that the automated system is very user-friendly and that in the order of 4-17% of the requested tests could be identified as unnecessary, with a false negative rate in between 4% (for hyperthyroidism) and 23% (for hypothyroidism). The achieved reduction in the number of tests is in addition to the reduction obtained in the manual system.

Clinical Laboratory Information Systems↗
PubMed1996

Temporal logics and real time expert systems.

This paper introduces temporal logics. Due to the eternal compromise between expressive adequacy and reasoning efficiency that must decided upon in any application, full (first order logic or modal logic based) temporal logics are frequently not suitable. This is especially true in real time expert systems, where a fixed (and usually small) response time must be guaranteed. One such expert system, Fagan's VM, is reviewed, and a delineation is given of how to formally describe and reason with time in medical protocols. It is shown that Petri net theory is a useful tool to check the correctness of formalised protocols.

Expert Systems↗
PubMed1991

Expert control of the arterial blood pressure during surgery.

During and after many surgical procedures the patient's arterial blood pressure must be artificially decreased to a lower than normal level. Although there are alternatives, infusion of the drug sodium nitroprusside (SNP) is frequently the preferred technique to achieve this controlled hypotension. The fast action of the drug and the danger of a too low pressure make manual control of the SNP infusion flow rate, even if done by an expert, a difficult and demanding task. This is mainly due to an occasional large unpredictable variability over time of the patient's sensitivity to SNP, and to the fact that a multitude of other factors also influence the arterial pressure. Due to these and several other causes, current automatic controllers cannot handle all cases equally well. A new expert system based SNP controller was designed to perform well for all patients, regardless of their characteristics. It monitors and adjusts its own performance, employing a number of heuristics derived from a careful study of the properties of the arterial pressure signal, the effects of SNP and other clinical provocations on the arterial pressure, and the ways in which expert clinicians manually manage the SNP infusion. Expert systems technology allows the new controller to access and employ this type of expert medical knowledge, resulting in expert-level performance. The controller was tested on 30 patients undergoing cardiac surgery, both before, during and after bypass. It was safe, needed little attention, and performed well in all cases.

Animals↗
PubMed1989

Correction of ocular artifacts in EEGs using an autoregressive model to describe the EEG; a pilot study.

The basic idea in eye movement (EM) artifact corrections is that the actual recording is the summation of brain potentials (true EEG) and artifact. Often a regression analysis is performed, using simultaneous EEG and EOG data, to find the parameters describing the relationship between artifact and EOG derivations (EOGs). Our method uses a maximum likelihood parameter estimation and considers data from preceding sample moments as well, since there may be a delay in the artifact transferring over the scalp. For the error term (true EEG) an autoregressive function is used. Results from estimations on data from one volunteer indicate that a delay need not be considered and that 3 autoregressive parameters are sufficient. For F3 4 EOGs give only somewhat better results than 2 EOGs. For C3 and C4 2 EOGs are sufficient. For practical reasons for each of these 3 EEG recordings, 2 EOGs were used to perform corrections. Corrections were performed using either the parameters estimated for EMs and blinks together, or the parameters estimated for EMs only (used for EMs), or the parameters estimated for blinks only (used for blinks). For EMs the differences between these corrections are very small. For blinks the differences are much larger. Parameters estimated for one trial may be used to correct other trials, recorded within a period of about 15 min preceding or following that trial.

Blinking↗
PubMed1979

Prognosis, trend and prediction in patient management.

A survey was conducted to get to know the 'state of the art' in trend prediction as a basis for optimal therapy, with emphasis on research being done in the countries of the European Community. Special areas of interest are quantitative prognosis (prognostic indices), the detection and use of trends in the patient's state, the use of models in prediction and their possible use for deciding which therapy is optimal for a specific patient. An extensive list of centres working in these fields as well as an extensive reference list is included.

Computers↗