Diagnostic method and apparatus for brain injury based on EMG frequency power spectra analysis
First Claim
1. A method for testing a subject for a brain condition comprising at least one of mild traumatic brain injury (mTBI), Alzheimer'"'"'s disease, Parkinson'"'"'s disease, and chronic traumatic encephalopathy using a portable device, the method comprising:
- acquiring, by a processor, electromyogram (EMG) signals of the subject from a detection area of the body using an EMG sensor device operatively coupled to a portable base unit, wherein the detection area of the body includes an area of muscles that are active while the subject is engaging in a physical task and the EMG signals are acquired while the subject engages in the physical task, the physical task comprising at least one of a walking gait cycle and a balance test;
processing, by the processor, the acquired EMG signals using the processor of the base unit and software to transform the EMG signals into EMG power spectra data, wherein the EMG power spectra data is characterized by a frequency spread, and determining quantitative features of the EMG power spectra data using at least one of linear and non-linear algorithms, wherein determining quantitative features comprises determining at least a ratio of a first energy value and a second energy value where the first energy value is obtained from a first frequency range in the EMG power spectra data and the second energy value is obtained from a second frequency range in the EMG power spectra data, wherein each of the first frequency range and the second frequency range comprises at least one of;
(a) approximately 30 Hz, (b) approximately 35 Hz to 70 Hz, (c) approximately 74 Hz to 75 Hz, (d) approximately 79 Hz to 80 Hz (e) approximately 93 Hz to 95 Hz, (f) approximately 60 Hz to 150 Hz, and (g) approximately 160 Hz to 320 Hz, and wherein the first frequency range is different than the second frequency range;
comparing, by the processor, the subject'"'"'s EMG power spectra data and the determined quantitative features against those in at least one database;
determining, by the processor, when the subject has at least one of mild traumatic brain injury (mTBI), Alzheimer'"'"'s disease, Parkinson'"'"'s disease and chronic traumatic encephalopathy based on the comparisons;
generating, by the processor, diagnostic information based on the comparison and determination, wherein the diagnostic information comprises at least one of the presence, location, and severity of a brain injury and the quantitative features of the subject; and
displaying, on an interactive screen, at least one of the diagnostic information and the quantitative features.
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Abstract
A method and a device for diagnosing brain injury (e.g. concussion) based on analysis of electromyogram (EMG) signals and presence of neurological modulation impairment of motor activity are described. The method consists of recording specific EMG signals under defined conditions, processing the acquired EMG signals, extracting the relevant information, and making diagnosis of brain injury and disorders that are associated with brain pathology. Specifically, the steps and device involved in the method include placing an EMG electrode set on the subject'"'"'s body area, acquiring EMG signals from a subject'"'"'s muscle(s) undergoing contraction, processing the acquired EMG signals using a signal processing algorithm that includes Fourier transformation. The resulting EMG data with a frequency domain (frequency power spectra) are then analyzed in comparison with databases stored in the device and used to determine anomaly of diagnostic value in the EMG power spectra from subjects. A diagnosis can be made based the altered EMG frequency power spectra that reflect the neurological modulation impairment of motor neurons. The diagnostic value, determination, management suggestions are displayed on the device.
9 Citations
26 Claims
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1. A method for testing a subject for a brain condition comprising at least one of mild traumatic brain injury (mTBI), Alzheimer'"'"'s disease, Parkinson'"'"'s disease, and chronic traumatic encephalopathy using a portable device, the method comprising:
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acquiring, by a processor, electromyogram (EMG) signals of the subject from a detection area of the body using an EMG sensor device operatively coupled to a portable base unit, wherein the detection area of the body includes an area of muscles that are active while the subject is engaging in a physical task and the EMG signals are acquired while the subject engages in the physical task, the physical task comprising at least one of a walking gait cycle and a balance test; processing, by the processor, the acquired EMG signals using the processor of the base unit and software to transform the EMG signals into EMG power spectra data, wherein the EMG power spectra data is characterized by a frequency spread, and determining quantitative features of the EMG power spectra data using at least one of linear and non-linear algorithms, wherein determining quantitative features comprises determining at least a ratio of a first energy value and a second energy value where the first energy value is obtained from a first frequency range in the EMG power spectra data and the second energy value is obtained from a second frequency range in the EMG power spectra data, wherein each of the first frequency range and the second frequency range comprises at least one of;
(a) approximately 30 Hz, (b) approximately 35 Hz to 70 Hz, (c) approximately 74 Hz to 75 Hz, (d) approximately 79 Hz to 80 Hz (e) approximately 93 Hz to 95 Hz, (f) approximately 60 Hz to 150 Hz, and (g) approximately 160 Hz to 320 Hz, and wherein the first frequency range is different than the second frequency range;comparing, by the processor, the subject'"'"'s EMG power spectra data and the determined quantitative features against those in at least one database; determining, by the processor, when the subject has at least one of mild traumatic brain injury (mTBI), Alzheimer'"'"'s disease, Parkinson'"'"'s disease and chronic traumatic encephalopathy based on the comparisons; generating, by the processor, diagnostic information based on the comparison and determination, wherein the diagnostic information comprises at least one of the presence, location, and severity of a brain injury and the quantitative features of the subject; and displaying, on an interactive screen, at least one of the diagnostic information and the quantitative features. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 24)
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16. A portable device for diagnosing at least one of mild traumatic brain injury (mTBI), Alzheimer'"'"'s disease, Parkinson'"'"'s disease, and chronic traumatic encephalopathy in a subject, wherein the portable device comprises:
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an electromyogram (EMG) signal sensor device for acquiring EMG signals from a detection area of the body of the subject, wherein the detection area of the body includes an area of muscles that are active while the subject is engaging in a physical task and the EMG signals are acquired while the subject engages in the physical task, the physical task comprising at least one of a walking gait cycle and a balance test; a portable base unit operatively coupled to the EMG signal sensor device comprising; a memory unit comprising; software having instructions for performing the assessment of neuromuscular control of the subject; at least one database; and a processor coupled to the memory unit, the processor being configured to; process the acquired EMG signals to transform the EMG signals into a EMG power spectra data, wherein the EMG power spectra data is characterized by a frequency spread; determine quantitative features from the EMG power spectra data, wherein determining quantitative features of the EMG power spectra data comprises determining at least a ratio of a first energy value and a second energy value where the first energy value is obtained from a first frequency range in the EMG power spectra data and the second energy value is obtained from a second frequency range in the EMG power spectra data, wherein each of the first frequency range and the second frequency range comprises at least one of;
(a) approximately 30 Hz, (b) approximately 35 Hz to 70 Hz, (c) approximately 74 Hz to 75 Hz, (d) approximately 79 Hz to 80 Hz, (e) approximately 93 Hz to 95 Hz, (f) approximately 60 Hz to 150 Hz and (g) approximately 160 Hz to 320 Hz, and wherein the first frequency range is different than the second frequency range;compare the subject'"'"'s EMG power spectra data and the determined quantitative features with EMG power spectra data and quantitative features from the at least one database; determine when the subject has at least one of mild traumatic brain injury (mTBI), Alzheimer'"'"'s disease, Parkinson'"'"'s disease, and chronic traumatic encephalopathy based on the comparison; generate diagnostic information based on the comparison and determination, wherein the diagnostic information comprises at least one of the presence, location and severity of the brain injury and the quantitative features of the subject; and an interactive screen that is configured to display at least one of the diagnostic information and the quantitative features. - View Dependent Claims (17, 18, 19, 20, 21, 22, 25)
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23. A non-transitory computer readable medium comprising a plurality of instructions that are executable on a processor of a portable device for adapting the portable device to implement a method for diagnosing at least one of mild traumatic brain injury (mTBI), Alzheimer'"'"'s disease, Parkinson'"'"'s disease, and chronic traumatic encephalopathy in a subject, wherein the method comprises:
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acquiring electromyogram (EMG) signals of the subject from a detection area of the body using an EMG sensor device operatively coupled to a portable base unit, wherein the detection area of the body includes an area of muscles that are active while the subject is engaging in a physical task and the EMG signals are acquired while the subject engages in the physical task, the physical task comprising at least one of a walking gait cycle and a balance test; processing the acquired EMG signals using the processor of the base unit and software to transform the EMG signals into EMG power spectra data, wherein the EMG power spectra data is characterized by a frequency spread, and determining quantitative features from the transformed EMG signals using at least one of linear and non-linear algorithms, wherein determining quantitative features comprises determining at least a ratio of a first energy value and a second energy value where the first energy value is obtained from a first frequency range in the EMG power spectra data and the second energy value is obtained from a second frequency range in the EMG power spectra data, wherein each of the first frequency range and the second frequency range comprises at least one of;
(a) approximately 30 Hz, (b) approximately 35 Hz to 70 Hz, (c) approximately 74 Hz to 75 Hz, (d) approximately 79 Hz to 80 Hz (e) approximately 93 Hz to 95 Hz, (f) approximately 60 Hz to 150 Hz, and (g) approximately 160 Hz to 320 Hz, and wherein the first frequency range is different than the second frequency range;comparing the subject'"'"'s EMG power spectra data and the determined quantitative features against those in at least one database; determining if the subject has at least one of mild traumatic brain injury (mTBI), Alzheimer'"'"'s disease, Parkinson'"'"'s disease, and chronic traumatic encephalopathy based on the comparison; generating diagnostic information based on the comparison and determination, wherein the diagnostic information comprises at least one of the presence, location and severity of the brain injury and the quantitative features of the subject; and displaying, on an interactive screen, at least one of the diagnostic information and the quantitative features. - View Dependent Claims (26)
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Specification