Kenneth C. Mylrea

Investigation of Sounds Produced by Healthy and Diseased Human Muscular Contraction

Muscle sounds were recorded from the medial biceps of 37 subjects as they pressed against a stationary object. The recordings were analyzed with a digital computer for frequency content. 20 subjects had some form of neuromuscular disorder, while 17 had no known muscle impairment.

Cardiac output measurements. A review of current techniques and research

Cardiac output is the volume of blood ejected by the heart per unit time. It is a useful measurement in that it can be used to evaluate overall cardiac status in both critically ill patients and patients with suspected cardiovascular disease. An ideal cardiac output measurement system would have automated continuous output capability, be minimally invasive, accurate, fast, small, low cost and clinically adaptable. This paper presents a theoretical and practical description of the variety of clinical techniques in use today and lists their advantages and shortcomings with respect to the ideal system. Included are the Fick method, indicator dilution techniques, velocity measurements and transthoracic impedance and combined Doppler ultrasound as noninvasive techniques. In addition, several experimental methods are described along with their desirable features and possible constraints. These include intravascular heating/recording, thermistor tracking of cardiac output, ejection fraction measurements and magnetic susceptability plethysmography.

Integration of monitoring for intelligent alarms in anesthesia: Neural networks—Can they help?

Although there has been a decrease in the number of anesthesia-related critical incidents, there are still opportunities for further improvement. We discuss the potential of integrated monitoring and artificial neural networks as a means of vigilantly watching for patterns in multiple variables to detect incidents and reduce false alarms. We estimate that half the anesthesia-related events could be detected with integrated monitoring using only 5 variables. A review of research using artificial intelligence/expert systems indicates limited potential for success using these tools alone for integrated monitoring in the operating room. We present artificial neural networks as an approach that is more suited to the type of multivariable monitoring and pattern recognition required. Along with rule-based artificial intelligence, these now have the potential to help develop innovative monitoring in the operating room.

Alarms and anesthesia: challenges in design of intelligent systems for patient monitoring

The limitations of current anesthesia monitor alarm technology are first discussed. The challenges of applying technology to improve patient monitoring are then considered, with attention given to integrating stand-alone devices and functions that are part of the anesthesia workstation and to the standardization of anesthetic practices. Design strategies for intelligent alarms are addressed. The process of generating alarms is considered as compromising three distinct tasks: sensing, signal processing, and annunciation.<<ETX>>

Integrated monitoring can detect critical events and improve alarm accuracy.

A computer-based, integrated monitor system was designed and utilized to collect and interactively manage physiologic data (13 variables and 3 waveforms) from six routinely used operating room monitors. Various approaches were developed to reduce false alarms, classify waveforms, and recognize events. False alarms: false alarms in ECG heart rate detection were reduced from 37.3% to 2.6% (p = 0.005) of total alarms using multi-variable analysis and rate-of-change limits. Waveform classification: using artificial neural networks (ANN), CO2 waveforms were classified into (a) spontaneous, (b) mechanical, and (c) mechanical/with spontaneous breathing attempts. The system properly classified 47 of 71 spontaneous, 65 of 67 mechanical, and 37 of 44 mechanical breaths/with spontaneous breathing attempts. Another ANN was used for detection of elevated and depressed ST segments in the ECG signal. All ST segment elevations and depressions of 0.1 mV were correctly identified. Event recognition: an algorithm developed to identify endotracheal intubation correctly recognized 13 of 17 intubations. This resulted in a 42% reduction in low end-tidal-CO2 false alarms.

An integrated course in fundamental engineering and English composition using interactive and process learning methodologies

At the University of Arizona, the electrical and computer engineering faculty teamed up with English composition instructors and used process-oriented teaching strategies to teach a combined English/engineering course to freshmen. The six credit-hour course combined three credit hours of introductory engineering and three credit hours of English composition, both required courses in the curriculum. The combined course is a creative problem-solving class that emphasizes the use of critical reading, thinking, and writing as appropriate learning strategies for technical material. The authors found that the seminar/lecture/laboratory approach produced an increased awareness of learning processes and resulted in more collaborative learning and holistic thinking. >

Detection of false alarms using an integrated anesthesia monitor

A computer-based system was used to collect and analyze data from five routinely used operating room monitors in order to identify meaningful alarm conditions and reduce the number of false positive alarms. Several methods for reduction of false alarms were implemented (patient-dependent limits, multivariable analysis and rate of change). The system was tested using operating room data from 21 surgical cases. The integrated monitor was able to correctly identify 10 of 11 intubations. Recognition of intubation was used in detection of false end-tidal-CO/sub 2/ alarms, reducing them by 70%. False heart-rate alarms were reduced by 68% using multivariable analysis and rate-of-change limits.<<ETX>>

Evaluation of peripheral nerve stimulators and relationship to possible errors in assessing neuromuscular blockade

Voltage and current output characteristics were measured on six commercially available peripheral nerve stimulator devices. The results are evaluated as possible sources of variability in peripheral nerve stimulator function and neuromuscular blockade assessment. The authors found significant differences in output voltage waveform and in maximum current into a 470 ohm load (21.4 to 128 mA.). Output current decreased from 25 to 88% in the different devices, with a load impedance increase from 470 to 10,000 ohms. Due to the variability in peripheral nerve stimulation units and the decrease in current output at higher load impedance, less than supramaximal stimulation is possible with erroneous interpretation of neuromuscular blockade.

An Esophageal Multiprobe for Temperature, Electrocardiogram, and Heart and Lung Sounds Measurements

An esophageal multiprobe capable of continuous monitoring of body core temperature, heart and lung sounds, and ECG during surgery was constructed using tubing having integral conductive plastic strips. A temperature readout instrument was designed for compatibility with this device. Clinical testing indicates promise for the development of an inexpensive disposable device for use with patients under general anesthesia.

Investigation of a continuous heating/cooling technique for cardiac output measurement

Cardiac output is frequently measured to assess patient hemodynamic status in the operating room and intensive care unit. Current research for measuring cardiac output includes continuous sinusoidal heating and synchronous detection of thermal signals. This technique is limited by maximum heating element temperatures and background thermal noise. A continuous heating and cooling technique was investigated in vitro to determine if greater thermal signal magnitudes could be obtained. A fast responding thermistor was employed to measure consecutive ejected temperature plateaus in the thermal signal. A flow bath and mechanical ventricle were used to simulate the cardiovascular system. A thermoelectric module was used to apply heating and cooling energy to the flow stream. Trials encompassing a range of input power, input frequency, and flow rate were conducted. By alternating heating and cooling, thermal signal magnitude can be increased when compared to continuous heating alone. However, the increase was not sufficient to allow for recording in all patients over the expected normal range of cardiac output. Consecutive ejected temperature plateaus were also measured on the thermal signal and ejection fraction calculations were made.