This document summarizes the results of a survey of spinal cord stimulation procedures in Denmark between 2014-2015 from a national neuromodulation database. It found that the most common indications for spinal cord stimulation were radicular pain after spine surgery and peripheral nerve damage. The median patient age was 48.8 years old and symptom duration was 54.8 months. Most patients reported severe pain, with median 7-day pain averages of 7 out of 10 and worst pain of 9.8 out of 10. The most common implantable pulse generators were from Medtronic and St. Jude Medical and the most common leads were from Medtronic and St. Jude Medical.
Report consist of the literature survey of Spinal Cord Injuries. Design and implantation of the electrode with MEMS technology to implantable pulse generator with a rechargeable battery to cure the pain.
Cognitive Computing: Company presentation by Avner Halperin, Co-Founder & CEO of EarlySense at the NOAH Conference 2019 in Tel Aviv, Hangar 11, 10-11 April 2019.
Case Review #39: 55 year old male with Progressive ScoliosisRobert Pashman
A 55 year old male presented with Progressive Adult Idiopathic Scoliosis. While he was preparing for surgery, he lifted a heavy item, and had neck pain and pain going down his arm. The patient was found to have myeloradiculopathy and spinal cord effacement and required an Anterior Cervical Fusion prior to scoliosis surgery. The following year he had a posterior spinal fusion for Scoliosis.
Case Review #8: 62 year old female with cervical spinal stenosisRobert Pashman
62 year old female with neck pain and left arm weakness. On MRI, the patient was found to have spinal stenosis. Dr. Pashman treated the patient with an Anterior Cervical Discecomy and fusion C4-/7.
This is a Dean's Case Competition project in Som-Binghamton University. I did it with my team in Spring 2014 to present our the overall situation of Medtronic Inc.
Report consist of the literature survey of Spinal Cord Injuries. Design and implantation of the electrode with MEMS technology to implantable pulse generator with a rechargeable battery to cure the pain.
Cognitive Computing: Company presentation by Avner Halperin, Co-Founder & CEO of EarlySense at the NOAH Conference 2019 in Tel Aviv, Hangar 11, 10-11 April 2019.
Case Review #39: 55 year old male with Progressive ScoliosisRobert Pashman
A 55 year old male presented with Progressive Adult Idiopathic Scoliosis. While he was preparing for surgery, he lifted a heavy item, and had neck pain and pain going down his arm. The patient was found to have myeloradiculopathy and spinal cord effacement and required an Anterior Cervical Fusion prior to scoliosis surgery. The following year he had a posterior spinal fusion for Scoliosis.
Case Review #8: 62 year old female with cervical spinal stenosisRobert Pashman
62 year old female with neck pain and left arm weakness. On MRI, the patient was found to have spinal stenosis. Dr. Pashman treated the patient with an Anterior Cervical Discecomy and fusion C4-/7.
This is a Dean's Case Competition project in Som-Binghamton University. I did it with my team in Spring 2014 to present our the overall situation of Medtronic Inc.
COMPARISON AND EVALUATION DATA MINING TECHNIQUES IN THE DIAGNOSIS OF HEART DI...ijcsa
Heart disease is one of the biggest health problems in the world because of high mortality and morbidity
caused by the disease. The use of data mining on medical data brought valuable and effective life
achievements and can enhance medical knowledge to make necessary decisions. Data mining plays an
important role in the field of medical science to solve health problems and diagnose ailments in critical
conditions and in normal conditions. For this reason, in this paper, data mining techniques are used to
diagnose heart disease from a dataset that includes 200 samples from different patients. Techniques used to
diagnose heart disease include Bagging, AdaBoostM1, Random Forest, Naive Bayes, RBF Network, IBK,
and NNge that all the techniques used to diagnose heart disease use Weka tool. Then these techniques are
compared to determine which is more accurate in the diagnosis of heart disease that according to the
results, it was found that the RBF Network with the accuracy of 88.2% is the most accurate classification in
the diagnosis of heart disease.
Detection of heart pathology using deep learning methodsIJECEIAES
In the directions of modern medicine, a new area of processing and analysis of visual data is actively developing - a radio municipality - a computer technology that allows you to deeply analyze medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), chest radiography (CXR), electrocardiography and electrocardiography. This approach allows us to extract quantitative texture signs from signals and distinguish informative features to describe the heart's pathology, providing a personified approach to diagnosis and treatment. Cardiovascular diseases (SVD) are one of the main causes of death in the world, and early detection is crucial for timely intervention and improvement of results. This experiment aims to increase the accuracy of deep learning algorithms to determine cardiovascular diseases. To achieve the goal, the methods of deep learning were considered used to analyze cardiograms. To solve the tasks set in the work, 50 patients were used who are classified by three indicators,
13 anomalous, 24 nonbeat, and 1 healthy parameter, which is taken from the MIT-BIH Arrhythmia database.
Ilsi conference biomed presentation brain game change israel leadership in c...Howard Sterling
Summary:
Neuro-cognitive and degenerative (CNS) diseases, with Alzheimer’s leading, are among the most intractable and costly and distressing diseases. Without effective therapies with minimal side effects, these diseases will break the healthcare systems, patients and caregivers.
Current therapies are inadequate and so many standard pharmaceutical responses have failed in late stage trials.
Only the most innovative solutions will yield effective therapies.
Israel, with its history & culture of scientific innovative innovation, government support & early recognition of the challenges of CNS, is poised to be a leader in effective CNS therapies.
How can we make Israel’s leadership known to the world?
Brain game changer presentation -israeli leadership in cns ilsi iata biomed ...Howard Sterling
Neuro-cognitive and degenerative (CNS) diseases, with Alzheimer’s leading, are among the most intractable and costly and distressing diseases. Without effective therapies with minimal side effects, these diseases will break the healthcare systems, patients and caregivers.
Current therapies are inadequate and so many standard pharmaceutical responses have failed in late stage trials.
Only the most innovative solutions will yield effective therapies.
Israel, with its history & culture of scientific innovative innovation, Government support & early recognition of the challenges of CNS, is poised to be a leader in effective CNS therapies.
How can we make Israel’s leadership known to the world?
HEALTH PREDICTION ANALYSIS USING DATA MININGAshish Salve
Data mining techniques are used for a variety of applications. In healthcare industry, datamining plays an important
role in predicting diseases. For detecting a disease number of tests should be required from the patient. But using data
mining technique the number of tests can be reduced. This reduced test plays an important role in time and performance.
This report analyses data mining techniques which can be used for predicting different types of diseases. This report reviewed
the research papers which mainly concentrate on predicting various disease
ARTIFICIAL NEURAL NETWORKING.
FIRST STEP TO KNOWLEDGE IS TO KNOW THAT we are ignorant
Knowledge in medical field is characterized by uncertanity and vagueness
Historically as well as currently this fact remains a motivation for the development of medical decision support system are based on fuzzy logics
Greek philosopher visualized a basic model of brain function as early as 300 bc
Till date nervous system is not completely understood to human kind.
Statistical, Energy Values And Peak Analysis (SEP) Approach For Detection of ...IJMERJOURNAL
ABSTRACT: In this paper, a technique of statistical, Energy values and peak analysis (SEP) approach is used for detection of neurodegenerative diseases from the signal of force sensitive resistors. In this work within the time series Left Stride Interval, Right Stride Interval, Left Swing Interval, Right Swing Interval, Left Stance Interval, Right Stance Interval and Double support interval are obtained and apply the SEP method. In statistical analysis, energy, standard deviation, mean, variance, co-variance are calculated. Two approximations and two details of energy values are extracted from wavelet decomposition. Average peak interval and peak histogram are calculated using peak analysis. Support Vector Machine (SVM) and Random Forest are used as a classifier. Data sets which include a healthy control (HC), various types of Neuro degenerative Diseases: Parkinson’s Disease (PD), Huntington Disease (HD), Amyotrophic Lateral Sclerosis. For disease diagnostic Force Sensitive resistor signals are used for evaluation. The results show that the proposed technique can successfully detect the NDD pathologies. For NDD detection, the accuracy, the Sensitivity, the Specificity values are 97%, 97% and 97% using Random forest Classifier.
COMPARISON AND EVALUATION DATA MINING TECHNIQUES IN THE DIAGNOSIS OF HEART DI...ijcsa
Heart disease is one of the biggest health problems in the world because of high mortality and morbidity
caused by the disease. The use of data mining on medical data brought valuable and effective life
achievements and can enhance medical knowledge to make necessary decisions. Data mining plays an
important role in the field of medical science to solve health problems and diagnose ailments in critical
conditions and in normal conditions. For this reason, in this paper, data mining techniques are used to
diagnose heart disease from a dataset that includes 200 samples from different patients. Techniques used to
diagnose heart disease include Bagging, AdaBoostM1, Random Forest, Naive Bayes, RBF Network, IBK,
and NNge that all the techniques used to diagnose heart disease use Weka tool. Then these techniques are
compared to determine which is more accurate in the diagnosis of heart disease that according to the
results, it was found that the RBF Network with the accuracy of 88.2% is the most accurate classification in
the diagnosis of heart disease.
Detection of heart pathology using deep learning methodsIJECEIAES
In the directions of modern medicine, a new area of processing and analysis of visual data is actively developing - a radio municipality - a computer technology that allows you to deeply analyze medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), chest radiography (CXR), electrocardiography and electrocardiography. This approach allows us to extract quantitative texture signs from signals and distinguish informative features to describe the heart's pathology, providing a personified approach to diagnosis and treatment. Cardiovascular diseases (SVD) are one of the main causes of death in the world, and early detection is crucial for timely intervention and improvement of results. This experiment aims to increase the accuracy of deep learning algorithms to determine cardiovascular diseases. To achieve the goal, the methods of deep learning were considered used to analyze cardiograms. To solve the tasks set in the work, 50 patients were used who are classified by three indicators,
13 anomalous, 24 nonbeat, and 1 healthy parameter, which is taken from the MIT-BIH Arrhythmia database.
Ilsi conference biomed presentation brain game change israel leadership in c...Howard Sterling
Summary:
Neuro-cognitive and degenerative (CNS) diseases, with Alzheimer’s leading, are among the most intractable and costly and distressing diseases. Without effective therapies with minimal side effects, these diseases will break the healthcare systems, patients and caregivers.
Current therapies are inadequate and so many standard pharmaceutical responses have failed in late stage trials.
Only the most innovative solutions will yield effective therapies.
Israel, with its history & culture of scientific innovative innovation, government support & early recognition of the challenges of CNS, is poised to be a leader in effective CNS therapies.
How can we make Israel’s leadership known to the world?
Brain game changer presentation -israeli leadership in cns ilsi iata biomed ...Howard Sterling
Neuro-cognitive and degenerative (CNS) diseases, with Alzheimer’s leading, are among the most intractable and costly and distressing diseases. Without effective therapies with minimal side effects, these diseases will break the healthcare systems, patients and caregivers.
Current therapies are inadequate and so many standard pharmaceutical responses have failed in late stage trials.
Only the most innovative solutions will yield effective therapies.
Israel, with its history & culture of scientific innovative innovation, Government support & early recognition of the challenges of CNS, is poised to be a leader in effective CNS therapies.
How can we make Israel’s leadership known to the world?
HEALTH PREDICTION ANALYSIS USING DATA MININGAshish Salve
Data mining techniques are used for a variety of applications. In healthcare industry, datamining plays an important
role in predicting diseases. For detecting a disease number of tests should be required from the patient. But using data
mining technique the number of tests can be reduced. This reduced test plays an important role in time and performance.
This report analyses data mining techniques which can be used for predicting different types of diseases. This report reviewed
the research papers which mainly concentrate on predicting various disease
ARTIFICIAL NEURAL NETWORKING.
FIRST STEP TO KNOWLEDGE IS TO KNOW THAT we are ignorant
Knowledge in medical field is characterized by uncertanity and vagueness
Historically as well as currently this fact remains a motivation for the development of medical decision support system are based on fuzzy logics
Greek philosopher visualized a basic model of brain function as early as 300 bc
Till date nervous system is not completely understood to human kind.
Statistical, Energy Values And Peak Analysis (SEP) Approach For Detection of ...IJMERJOURNAL
ABSTRACT: In this paper, a technique of statistical, Energy values and peak analysis (SEP) approach is used for detection of neurodegenerative diseases from the signal of force sensitive resistors. In this work within the time series Left Stride Interval, Right Stride Interval, Left Swing Interval, Right Swing Interval, Left Stance Interval, Right Stance Interval and Double support interval are obtained and apply the SEP method. In statistical analysis, energy, standard deviation, mean, variance, co-variance are calculated. Two approximations and two details of energy values are extracted from wavelet decomposition. Average peak interval and peak histogram are calculated using peak analysis. Support Vector Machine (SVM) and Random Forest are used as a classifier. Data sets which include a healthy control (HC), various types of Neuro degenerative Diseases: Parkinson’s Disease (PD), Huntington Disease (HD), Amyotrophic Lateral Sclerosis. For disease diagnostic Force Sensitive resistor signals are used for evaluation. The results show that the proposed technique can successfully detect the NDD pathologies. For NDD detection, the accuracy, the Sensitivity, the Specificity values are 97%, 97% and 97% using Random forest Classifier.
Statistical, Energy Values And Peak Analysis (SEP) Approach For Detection of ...
f1000research-107467
1. Amputation, phantom pain
3
Amputation, stump pain
1
Angina pectoris
2
Back pain after spinal surgery
14
Back pain, NO previous spine
surgery
2
CRPS I
3
CRPS II
5
Medullar lesion, incomplete
1
Neuropathy, diabetic
3
Neuropathy, other
5
Peripheral nerve damage, plexus injury
1
Peripheral nerve damage
13
Radicular pain after spine
surgery
36
Radicular pain, NO previous
spine surgery
2
Unknown
13
PRIMARY INDICATIONS
Kaare Meier, MD PhD1,2,3, Christian Scherer, MD4,5, Christina Rosenlund, MD4, Helga A. Gulisano, MD6, Thomas P. Enggaard, MD PhD7,
Lisette M. Willumsen, MD8, Anne Lene H. Knudsen, RN1, Mattias Rasmusson, MSc3,9, Jens Christian Sørensen, MD PhD DMSc1,3
Reference:
Meier K. et al: The Aarhus Neuromodulation Database.
Neuromodulation. 2013 Nov-Dec;16(6):506-13.
A DANISH SURVEY OF SPINAL CORD STIMULATION BASELINE DATA:
FIRST RESULTS FROM A NATIONAL NEUROMODULATION DATABASE
1Dept. of Neurosurgery, 2Dept. of Anesthesiology, Aarhus University Hospital, 3Neurizon ApS, Aarhus, 4Dept. of Neurosurgery, 5Dept. of Anesthesiology, Odense University Hospital, Odense, 6Dept.
of Neurosurgery, Aalborg University Hospital, Aalborg, 7Multidisciplinary Pain Centre, 8Dept. of Neurosurgery, Rigshospitalet, Copenhagen, Denmark, 9Evibase LLC, Boston, MA, United States
WHY?
Evidence for the efficacy of spinal cord
stimulation (SCS) and dorsal root ganglion
stimulation (DRG) is accumulating thanks to an
increasing number of published data from
randomized controlled trials.
Much less is known about the application of SCS
in everyday clinical practice outside a controlled
study setting: Who gets implanted and on what
indications? What is the choice of implant? How
do the treatments perform?
WHAT?
Data on all patients receiving their first SCS or
DRG implant(s) between 1 January 2014 and 30
May 2015 in Denmark was retrieved from the
Neurizon Neuromodulation Database.
For this survey, only baseline patient data and
selected procedure data were analyzed.
The database is in routine use at all the four
centers performing SCS and DRG in Denmark.
HOW?
The Neurizon Neuromodulation Database is an
internet-based, generic, module-oriented,
publicly available database.
The numerous modules cover detailed patient
characteristics and core treatment parameters,
including procedure-related details and
complications.
It also features recording of key success
parameters for follow-up of the treatment such as
pain intensity, work status, and quality of life.
Conflict of interest:
Dr. Meier and Prof. Sørensen have received research support and lecture fees from
St. Jude Medical.
Dr. Meier, Prof. Sørensen, and Mr. Rasmusson are proprietors of Neurizon.
NEURIZON NEUROMODULATION DATABASE
Based mainly on drop-down menus, the Neurizon Neuromodulation Database is quick and easy to use, and it
covers all relevant parameters for full patient management and for continuous monitoring and research.
It is web-based, programmed using industry standards to ensure scalability and performance, and hosted on
a commercial server with full traffic encryption.
The Neurizon Neuromodulation Database is intended for international collaboration, and the Swiss
Neuromodulation Society recently joined the network.
Our other colleagues in the field of neuromodulation are invited to use the database in their own practice as
a free clinical tool. Independent mirrors of the database can be set up, keeping data local and confident.
For more information, please contact: neuro@kaare.org
Abstract ID: 2220737
International Neuromodulation Society, Montreal 2015
PATIENT CHARACTERISTICS
Boston Scientific
Precision Plus 2.0
5
Boston Scientific
Precision Spectra
1
Medtronic
PrimeAdvanced
12
Medtronic
PrimeAdvanced SS
21
St. Jude Medical Eon
13
St. Jude Medical Eon
Mini
8
St. Jude Medical EonC
12
Spinal Modulation Axium
6
IPGS
Boston Scientific Linear
Wide 3-4
6
Boston Scientific Linear
Wide 3-6
2
Medtronic Octad
stogard
7
Medtronic Octad sub-
compact
1
Medtronic Pisces Quad
compact
1
Medtronic Pisces Quad
plus
4
Medtronic Vectris SS
27
Medtronic other
2
St. Jude Medical Octrode
23
St. Jude Medical S8
Lamitrode
20
Spinal Modulation Axium
9
Unknown
2
LEADS
25% Median 75%
Patient
age (years)
40.9 48.8 55.3
n = 82
Symptom
duration (months)
34.7 54.8 87.3
n = 80
7-day pain
average (NRS)
6 7 8
n = 53
7-day worst
pain (NRS)
8 9.8 10
n = 54
Male
44
Female
38
Employed
10%
Flexijob / light duties
23%
Self-employed
2%
Student
2%
Sickness benefit
10%
Unemployment benefit 2%
Social security
8%
Disability pensioner
23%
Pensioner 18%
Other 2%
WORK STATUS, n = 51