IL284635A - Neuromonitoring data analysis apparatuses and methods - Google Patents
Neuromonitoring data analysis apparatuses and methodsInfo
- Publication number
- IL284635A IL284635A IL284635A IL28463521A IL284635A IL 284635 A IL284635 A IL 284635A IL 284635 A IL284635 A IL 284635A IL 28463521 A IL28463521 A IL 28463521A IL 284635 A IL284635 A IL 284635A
- Authority
- IL
- Israel
- Prior art keywords
- neuromonitoring
- data
- analysis apparatus
- data analysis
- injury
- Prior art date
Links
- 238000007405 data analysis Methods 0.000 title claims 22
- 238000000034 method Methods 0.000 title 1
- 230000001537 neural effect Effects 0.000 claims 21
- 208000027418 Wounds and injury Diseases 0.000 claims 15
- 230000006378 damage Effects 0.000 claims 15
- 208000014674 injury Diseases 0.000 claims 15
- 238000010801 machine learning Methods 0.000 claims 12
- 230000002547 anomalous effect Effects 0.000 claims 9
- 230000000763 evoking effect Effects 0.000 claims 7
- 230000004044 response Effects 0.000 claims 7
- 238000004458 analytical method Methods 0.000 claims 5
- 230000003238 somatosensory effect Effects 0.000 claims 4
- 206010002091 Anaesthesia Diseases 0.000 claims 3
- 230000037005 anaesthesia Effects 0.000 claims 3
- 230000007257 malfunction Effects 0.000 claims 2
- 210000000653 nervous system Anatomy 0.000 claims 2
- 230000037361 pathway Effects 0.000 claims 2
- 230000011514 reflex Effects 0.000 claims 2
- 230000009885 systemic effect Effects 0.000 claims 2
- 208000028389 Nerve injury Diseases 0.000 claims 1
- 230000036772 blood pressure Effects 0.000 claims 1
- 230000007613 environmental effect Effects 0.000 claims 1
- 230000001095 motoneuron effect Effects 0.000 claims 1
- 230000008764 nerve damage Effects 0.000 claims 1
- 230000007383 nerve stimulation Effects 0.000 claims 1
- 210000000578 peripheral nerve Anatomy 0.000 claims 1
- 230000001953 sensory effect Effects 0.000 claims 1
- 230000002269 spontaneous effect Effects 0.000 claims 1
- 238000001356 surgical procedure Methods 0.000 claims 1
Classifications
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
- A61B5/4029—Detecting, measuring or recording for evaluating the nervous system for evaluating the peripheral nervous systems
- A61B5/4041—Evaluating nerves condition
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
- A61B5/377—Electroencephalography [EEG] using evoked responses
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
- A61B5/377—Electroencephalography [EEG] using evoked responses
- A61B5/383—Somatosensory stimuli, e.g. electric stimulation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/389—Electromyography [EMG]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Veterinary Medicine (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Public Health (AREA)
- Psychiatry (AREA)
- Neurology (AREA)
- Psychology (AREA)
- Physiology (AREA)
- Neurosurgery (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Signal Processing (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Claims (21)
1.P10785-IL | CLEAN 284635/ 34
2.CLAIMS What is claimed is: 1. A neuromonitoring data analysis apparatus configured to monitor a subject’s nervous system, the apparatus comprising: at least one processor; and at least one memory configured to store data and software code portions executable by the at least one processor to cause to perform: applying a machine learning model; receiving patient data comprising: data that are descriptive of a plurality of physical stimuli applied to at least two neural structures of the mammalian subject’s nervous system; and sensor data descriptive of a plurality of neurophysiological response signals generated in the at least two neural structures in response to the applying of the plurality of physical stimuli; and identifying, using the machine learning model, based on the sensor data descriptive of the plurality of neurophysiological response signals, an anomalous event that is indicative of injury of at least one of the at least two neural structures; wherein the identifying comprises: analyzing data descriptive of a plurality of distinct signals to take into consideration the collective contribution of the plurality of distinct signals for distinguishing between: a first category of an anomalous event relating to injury of at least one of the at least two neural structures; and a second category of an anomalous event not relating to injury of at least one of the at least two neural structures. 2. The neuromonitoring data analysis apparatus of claim 1, further configured to provide a first output relating to the identified event.
3. The neuromonitoring data analysis apparatus of any one of the preceding claims, wherein, by taking into consideration the plurality of neurophysiological response signals generated in the at least two neural structures and, optionally, the data descriptive of the applied physical stimuli, a false-positive rate of anomalous events identified as relating to injury of a neural structure is reduced, compared to a false-positive rate obtained if each response signal was analyzed individually.
4. The neuromonitoring data analysis apparatus of any one of the preceding claims, wherein, by taking into consideration the plurality of neurophysiological response signals generated in the at least two neural structures, and, optionally, data descriptive of the applied physical stimuli a false-negative rate of anomalous events identified as relating to injury of a neural structure is reduced, compared to a false-negative rate obtained if each response signal was analyzed individually.
5. The neuromonitoring data analysis apparatus of any one of the claims 2 to 4, wherein the first output includes information about a probability that the detected anomalous event relates injury of the at least one neural structure.
6. The neuromonitoring data analysis apparatus of any one of the preceding claims, configured to provide a second output descriptive of an anomalous event of the second category. P10785-IL | CLEAN 284635/ 35
7. The neuromonitoring data analysis apparatus of claim 6, wherein the second output descriptive of the anomalous event of the second category includes information as to whether the second anomalous event is caused by one of the following: a sensor misconfiguration; a signal artifact, a systemic physiological factor, system malfunction, environmental factor, or any combination of the aforesaid.
8. The neuromonitoring data analysis apparatus of claim 7, wherein the systemic physiological factor includes one or more of the following: patient anesthesia; blood pressure; patient position; patient posture; or any combination of the aforesaid.
9. The neuromonitoring data analysis apparatus of any one of the preceding claims, wherein the plurality of physical stimuli relate to one of the following: an evoked potential; a reflex; a spontaneous potential, or any combination of the above.
10. The neuromonitoring data analysis apparatus of any one of the claims 6 to 9, further configured such that in the event it is determined that the detected anomaly does not relate to injury of the at least one neural structure, the apparatus provides the second output including information about the detected anomaly.
11. The neuromonitoring data analysis apparatus of any one of the preceding claims, wherein the injury of the at least one neural structure is the result of physical engagement with tissue region including the at least one neural structure.
12. The neuromonitoring data analysis apparatus of any one of the preceding claims, including a classifier for classifying a neural functional state of the at least one neural structure into one of the following categories: “NORMAL”, “DROP”, “DISAPPEAR”.
13. The neuromonitoring data analysis apparatus of any one of the preceding claims, configured to simultaneously subject the at least two neural structures to the physical stimuli.
14. The neuromonitoring data analysis apparatus of any one of the preceding claims, wherein the memory is configured to receive patient data further comprising one of the following: clinical patient data; demographic patient data; anesthesia data; physiological patient data; surgical data; baseline motor evoked potential signal data; baseline EMG signals; baseline EEG signals; baseline somatosensory evoked potential signal data; reflexes; or any combination thereof.
15. The neuromonitoring data analysis apparatus of any one of the claims 2 to 14, wherein the first output includes information characterizing a pathway injury as relating to one of the following: P10785-IL | CLEAN 284635/ 36 motor insult including motoric injury impact location; somatosensory insult, including sensory impact location; cord pathway injury severity, including complete or incomplete injury; or any combination thereof.
16. The neuromonitoring data analysis apparatus of any one of the preceding claims, configured to characterize injury of the at least one neural structure as relating to one of the following: Myotome injury; nerve injury severity, including complete or incomplete injury.
17. The neuromonitoring data analysis apparatus of any one of the preceding claims, further configured to provide: an operational recommendation output comprising one of the following: evoke additional motor evoked potential; evoke additional somatosensory evoked potential; change stimulus intensity of the additional motor evoked potential; change stimulus intensity of the additional somatosensory evoked potential; update recording parameters; check for neuromonitoring system malfunction; check impedance; check anesthesia parameters; to perform peripheral nerve stimulation; check physiological parameters; check patient position; hold surgical procedure; electrode positioning; patient positioning; or any combination of the aforesaid.
18. The neuromonitoring data analysis apparatus of claim 17, wherein the operational recommendation output depends on the identified anomaly.
19. The neuromonitoring data analysis apparatus of any one of the preceding claims, wherein the machine learning model includes hierarchically arranged machine learning submodels, and wherein a first level of machine learning submodels of the hierarchically arranged machine learning submodels is configured to analyze signals of a plurality of channels pertaining to a signal modality to produce a plurality of respective channel-wise analysis outputs.
20. The neuromonitoring data analysis apparatus of claim 19, wherein a second level of machine learning submodules of the hierarchically arranged machine learning submodels is configured to receive the plurality of channel-wise analysis outputs; and wherein the second level of machine learning submodules is configured to analyze the plurality of received channel-wise analysis outputs of the signal modality to provide an analysis output descriptive of the modality.
21. The neuromonitoring data analysis apparatus of claim 20, wherein a third level of machine learning submodules of the hierarchically arranged machine learning submodels receives the analysis output descriptive of the modality; and wherein the third level of machine learning submodules is configured to analyze the output received from the second submodule to produce an output descriptive of a clinical interpretation of the received patient data.
Priority Applications (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| IL284635A IL284635B2 (en) | 2021-07-05 | 2021-07-05 | A neuromonitoring data analysis apparatus |
| EP22837133.2A EP4366607A1 (en) | 2021-07-05 | 2022-07-05 | Neuromonitoring data analysis apparatuses and methods |
| PCT/IB2022/056217 WO2023281399A1 (en) | 2021-07-05 | 2022-07-05 | Neuromonitoring data analysis apparatuses and methods |
| JP2023580969A JP2024526274A (en) | 2021-07-05 | 2022-07-05 | Neuromonitoring data analysis apparatus and method |
| US18/403,768 US20240225519A9 (en) | 2021-07-05 | 2024-01-04 | Neuromonitoring data analysis apparatuses and methods |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| IL284635A IL284635B2 (en) | 2021-07-05 | 2021-07-05 | A neuromonitoring data analysis apparatus |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| IL284635A true IL284635A (en) | 2023-02-01 |
| IL284635B1 IL284635B1 (en) | 2023-10-01 |
| IL284635B2 IL284635B2 (en) | 2024-02-01 |
Family
ID=86691813
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| IL284635A IL284635B2 (en) | 2021-07-05 | 2021-07-05 | A neuromonitoring data analysis apparatus |
Country Status (1)
| Country | Link |
|---|---|
| IL (1) | IL284635B2 (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090048531A1 (en) * | 2005-06-03 | 2009-02-19 | Mcginnis William C | Dermatomal somatosensory evoked potential (dssep) apparatus for real time nerve root function diagnosis in surgical and clinical situations |
| US9566015B2 (en) * | 2009-01-30 | 2017-02-14 | Medtronic Xomed, Inc. | Nerve monitoring during electrosurgery |
| US9949651B2 (en) * | 2011-11-01 | 2018-04-24 | DePuy Synthes Products, Inc. | Intraoperative neurophysiological monitoring system |
| US20180122506A1 (en) * | 2015-03-26 | 2018-05-03 | Surgical Safety Technologies Inc. | Operating room black-box device, system, method and computer readable medium for event and error prediction |
| US10098585B2 (en) * | 2013-03-15 | 2018-10-16 | Cadwell Laboratories, Inc. | Neuromonitoring systems and methods |
| US20190038169A1 (en) * | 2017-08-03 | 2019-02-07 | Neuromonitoring Associates, Inc. | Systems for intraoperative neurophysiological monitoring |
| WO2019207510A1 (en) * | 2018-04-26 | 2019-10-31 | Mindmaze Holding Sa | Multi-sensor based hmi/ai-based system for diagnosis and therapeutic treatment of patients with neurological disease |
| US20200352468A1 (en) * | 2008-10-15 | 2020-11-12 | Nuvasive, Inc. | Neurophysiologic Monitoring System and Related Methods |
| US20210093228A1 (en) * | 2019-09-27 | 2021-04-01 | DePuy Synthes Products, Inc. | Intraoperative neural monitoring system and method |
-
2021
- 2021-07-05 IL IL284635A patent/IL284635B2/en unknown
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090048531A1 (en) * | 2005-06-03 | 2009-02-19 | Mcginnis William C | Dermatomal somatosensory evoked potential (dssep) apparatus for real time nerve root function diagnosis in surgical and clinical situations |
| US20200352468A1 (en) * | 2008-10-15 | 2020-11-12 | Nuvasive, Inc. | Neurophysiologic Monitoring System and Related Methods |
| US9566015B2 (en) * | 2009-01-30 | 2017-02-14 | Medtronic Xomed, Inc. | Nerve monitoring during electrosurgery |
| US9949651B2 (en) * | 2011-11-01 | 2018-04-24 | DePuy Synthes Products, Inc. | Intraoperative neurophysiological monitoring system |
| US10098585B2 (en) * | 2013-03-15 | 2018-10-16 | Cadwell Laboratories, Inc. | Neuromonitoring systems and methods |
| US20180122506A1 (en) * | 2015-03-26 | 2018-05-03 | Surgical Safety Technologies Inc. | Operating room black-box device, system, method and computer readable medium for event and error prediction |
| US20190038169A1 (en) * | 2017-08-03 | 2019-02-07 | Neuromonitoring Associates, Inc. | Systems for intraoperative neurophysiological monitoring |
| WO2019207510A1 (en) * | 2018-04-26 | 2019-10-31 | Mindmaze Holding Sa | Multi-sensor based hmi/ai-based system for diagnosis and therapeutic treatment of patients with neurological disease |
| US20210093228A1 (en) * | 2019-09-27 | 2021-04-01 | DePuy Synthes Products, Inc. | Intraoperative neural monitoring system and method |
Non-Patent Citations (3)
| Title |
|---|
| LEE, CECILIA S., AND AARON Y. LEE., CLINICAL APPLICATIONS OF CONTINUAL LEARNING MACHINE LEARNING., 31 December 2020 (2020-12-31) * |
| QIAO, NIDAN, ET AL., DEEP LEARNING FOR AUTOMATICALLY VISUAL EVOKED POTENTIAL CLASSIFICATION DURING SURGICAL DECOMPRESSION OF SELLAR REGION TUMORS., 20 November 2019 (2019-11-20) * |
| ZHA, XUEFAN, ET AL., A DEEP LEARNING MODEL FOR AUTOMATED CLASSIFICATION OF INTRAOPERATIVE CONTINUOUS EMG., 30 December 2020 (2020-12-30) * |
Also Published As
| Publication number | Publication date |
|---|---|
| IL284635B1 (en) | 2023-10-01 |
| IL284635B2 (en) | 2024-02-01 |
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