Surgery – Diagnostic testing – Sensitivity to electric stimulus
Reexamination Certificate
2001-08-27
2003-04-15
Hindenburg, Max F. (Department: 3736)
Surgery
Diagnostic testing
Sensitivity to electric stimulus
C600S545000, C600S544000, C600S546000
Reexamination Certificate
active
06547746
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to a method and apparatus for quantifying the response thresholds of biological and nonbiological systems to stimuli. In particular, the present invention relates to the determination of response thresholds using Recurrence Quantitation Analysis and other mathematical techniques, for perceivable and nonperceivable stimuli (light, sound, temperature, pressure, aroma, chemical, biochemical, learning tasks, electric and magnetic fields, and so forth).
2. Discussion of Background
Biological systems—ranging from cells in culture media to laboratory animals to human beings—exhibit dynamically complex responses to stimuli. The classic approach to studying stimulus-response relationships has been to present the stimulus in a simplified experimental setting, with as few variables as possible, and record the subject's response. Various physiological parameters were also measured in order to provide an objective measure of the subject's response, including skin resistance and potential, blood pressure, respiration rate, electrocardiogram (ECG or EKG), electroencephalogram (EEG), electromyogram (EMG), etc. This approach was historically useful in determining thresholds for readily-perceivable stimuli such as light, sound, and pressure, as well as other stimuli that were specifically identifiable and recognizable as stimuli. However, the classic methodology fails when the stimulus is one that the subject does not perceive directly, or which does not lend itself to association with straightforward measurements of physiological parameters.
Recent developments in the study of physiological systems (including humans) draw on chaos theory and informational theory, suggesting that these are complex systems that exhibit equally complex dynamic, state-dependent behaviors. Unlike classic physiology, which implicitly assumed that physiological systems are both linear and homeostatic, the new paradigm acknowledges that the experimenter's underlying assumptions can affect both the design and the outcome of any experimental study. (For purposes of this specification, the term “homeostatic” refers to the tendency of a biological system to maintain internal constancy regardless of its surrounding environment. “Nonhomeostatic” is the reverse of homeostatic.) This approach has led to the development of new mathematical tools for the study of complex, nonlinear behaviors in biological systems.
Many different types of stimuli entail physiological changes that are straightforward to measure and analyze. For example, thresholds of perception for light, sound, and pressure are measured by standard, well-established techniques. Similarly, the effects of medications on blood pressure, blood chemistry, heart rate, etc. can be measured with readily-available instrumentation, and can be analyzed using familiar statistical techniques. The difficulty arises in measuring the effects of stimuli that elicit nonlinear, nonhomeostatic responses. Many environmental parameters are believed to elicit such nonlinear responses, including but not necessarily limited to electric and magnetic fields, light, and sound.
Various approaches to the study of stimulus effects have been developed. By way of example, Metz, et al. (U.S. Pat. No. 5,051,209) measures the effects of external stimuli on the brain using positron emission topography (PET). Stimuli include psychoactive compounds, drugs, and sensory-perceivable environmental factors (temperature, noise, vibration, light). The method includes the following steps: while controlling behavioral influences on the subject's brain via a “behavioral clamp,” (1) measuring cerebral metabolism with a positron emission tomography (PET) scan in the absence of external treatment; (2) administering an external treatment to the subject, (3) measuring cerebral metabolism after the treatment, and (4) determining any differences between the cerebral metabolism in steps (1) and (3). The PET image sets are standardized so the data from different subjects, and from the same subject at different times, can be compared to determine which (if any) brain areas show differences between the treatment conditions.
Electroencephalographic (EEG) measurements are frequently used to study responses to various stimuli. By way of example, Levin (U.S. Pat. No. 5,860,936) provides a differential geometric method and an apparatus for measuring an observer's perception of dynamically evolving visual and auditory stimuli. The apparatus includes a stimulus output device for presenting stimuli to the observer, and a stimulus manipulation device that permits the observer to modify the presented stimuli by selecting related stimuli from a database. The method is based on the concepts of “reference stimuli” and “reference transformations”: an evolving stimulus is described in terms of an initial reference state and of reference transformations (for example, movement in a certain distance for a certain direction, change in color, etc. The observer is asked to identify which small transformation of a first stimulus is perceived to be equivalent to a small transformation of a second stimulus. The observer's perceptions of a number of such transformations are used to calculate an affine connection on the stimulus manifold, which encodes how that particular observer perceives evolving stimuli as sequences of reference transformations. Differences between observers characterize differences between their individual perceptions, and can be used to “translate” sets of stimuli between observers).
Maynard (U.S. Pat. No. 5,816,247) uses neural networks to analyze EEG data with an apparatus that includes circuitry for receiving, amplifying and processing EEG signals, a computer for statistical processing of the signals, a neural network with a training mode and a classifying mode, a display for displaying the output classifying values in n-dimensional form, and a memory for storing the data. The method includes the following steps: (1) obtaining sets of training data from a plurality of patients; (2) determining categories for classifying the sets; (3) defining an n-dimensional space in which the determined categories are represented as distinct coordinates; (4) training a neural network with n outputs using the sets as input data and the defined categories as target outputs; and (5) applying a set of EEG data from a patient to the neural network to derive a position in the n-space for the purpose of assessing a patient category.
Nadel (U.S. Pat. No. 5,788,648) shows an EEG apparatus for exploring a subject's response to quantifiable external stimuli (oral, visual, tactile, acoustic, and/or olfactory, and combinations thereof). The apparatus includes sensing apparatus for sensing brainwave signals, stimulating apparatus for generating the stimuli, and processing apparatus for receiving and processing the signals to compute a correlation quotient of the signals and the stimuli. Data analysis is based on Fourier transforms.
Urbach, et al. (U.S. Pat. No. 5,282,475) disclose an apparatus and method for objective determination of auditory thresholds for intelligible speech. The apparatus includes a microprocessor, a digital-to-analog converter and a signal amplifier for presenting a randomly-selected speech stimulus to a human subject, a multichannel EEG amplifier for monitoring the physiological response of the subject, and a CRT display. The stimulus is presented to the subject through earphones while monitoring the EEG, and recorded data are corrected for eye movement artifacts.
Rosenfeld (U.S. Pat. No. 5,137,027) provides a method for using event-related potentials (P300 brain wave amplitude and/or latency) to evaluate whether or not a subject has previously performed a given act. Subjects are exposed to two successive groups of perceivable stimuli, each group designed according to a specified protocol. The following parameters are computed and compared for the two stimulus groups: (1) the prestimulus EEG potential for a f
Hindenburg Max F.
Natnithithadha Navin
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