Sunday, December 6, 2015
RE: Patents Report
Excellent patent list! If you can focus on the proposed idea, narrow down patent search in that specific area, and implement/test your ideas, you might be able to file a patent.
Monday, November 30, 2015
Patents Report
GROUP 4, SARAH AND BRIAN
Electromagnetic signals of different frequencies are
simultaneously transmitted to the brain of the subject in which the signals
interfere with one another to yield a waveform which is modulated by the
subject's brain waves.
patent name:
Apparatus and method for remotely monitoring and altering brain waves
US3951134 A
US Class:
600/544 600/407
Owner name:
Dorne & Margolin Inc.
Various embodiments of the present invention create a novel
system for rating an event in a media based on the strength of the emotions
viewers feel towards the event. The viewer's responses to the media can be
measured and calculated via physiological sensors.
Patent Name:
Method and system for using coherence of biological responses as a measure of
performance of a media
US8230457 B2
US Class:
725/10, 725/9, 382/118
Owner Name:
EMSENSE CORPORATION, CALIFORNIA
this patent is on an electrode headset to collect brain
acitivity.
Patent Name:
Electrode Headset
USD565735 S1
US Class:
D24/187
Owner Name:
Emotiv Systems Pty Ltd.
this invloves a brainwave measuring device with a processsor
that also generates an output.
Patent Name:
Integrated Sensor Headset
US20090253996
A1
US Class:
600/544
Owner Name:
EMSENSE CORPORATION, CALIFORNIA
This patent sounds like a classification method. description
includes words like “identifying plurality of brain signals” and “extracting
identifying features”.
patent name:
Brain-computer interface anonymizer
US 20140228701 A1
US class: 600/544
Owner name:
UNIVERSITY OF WASHINGTON THROUGH ITS CENTER FOR CO
this patent was not yet granted but is really interesting.
through real time monitoring of brain signals, it tries to determine and graph
creativity. it also tries to pinpoint the moment of insight, by presenting data
to the subject and watching for excitement in brain signals. (...For example,
research has demonstrated that some EEG frequencies of particular channels can
differentiate between "insight" or "creativity", and
"analysis" or "non-creative'" brain states leading to
problem solutions…) this relates to our project, because it classifies signals
and tries to identify a desirable result.
patent name:
METHOD AND SYSTEM FOR REAL-TIME INSIGHT DETECTION USING EEG SIGNALS
US 20150216468 A1
US class: 600/544
applicant: KONICA
MINOLTA LABORATORY
this invention tries to analyze brain signals and thus
determine and predict sleep patterns. it analyzes differences between deep and
shallow sleep based on brainwave activity.
patent name:
METHOD AND SOFTWARE TO DETERMINE PROBABILITY OF SLEEP/WAKE STATES AND QUALITY
OF SLEEP AND WAKEFULNESS FROM AN ELECTROENCEPHALOGRAM
US 20150238103 A1
US class:
600/544 600/301
applicant: YRT
LIMITED
this is similiar to the above. its a sleep stage detection
system. sleep stage is detected based on frequency of certain brain bands etc.
in this case the system is then used in treating certain sleep disorders (cuz
various parts of the treatment have to be done through various stages.)
patent name: SLEEP
STAGE DETECTION
US 20150265207 A1
US class:
600/301 600/544
applicant:
Medtronic, Inc.
this patent might relate most closely to what were doing.
the patent is on a specific algorithm
pattern in classification. the patent referneces the decision tree
algorithm mainly. by refiltering the classified results after everything with
another decision tree and only then extracting desirable results the data gets
refined much better and the correct percentage inceases by .09%.
patent name: method for selecting features of EEG signals
based on decision tree
US 20150269336 A1
US class:
702/189 600/544
applicant: Beijing
University of Technology
This provides methods of decoding speech from brain activity
data. Aspects of the methods include receiving brain speech activity data from
a subject, and processing the brain speech activity data to output speech
feature data. Also provided are devices and systems for practicing the subject
methods.
patent name:
METHODS OF DECODING SPEECH FROM BRAIN ACTIVITY DATA AND DEVICES FOR PRACTICING
THE SAME
US 20150297106 A1
US class:
600/383 600/378 600/544
applicant: The
Regents of the University of California
basically its pretty similar to ours in that it invloves a
recording signals, training, classifying, interpreting, and output bci. the
gist: music will be played to the subject and through analyzing brain signals,
researchers will classify the emotion invoked. the system will then establish a
database of music associated with each emotion. then, when the eeg scans
seperately detect the user a certain emotion, it may recomend appropriate
music.
patent name:
SYSTEM AND METHOD FOR ASSOCIATING MUSIC WITH BRAIN-STATE DATA
US 20150297109 A1
US class:
600/28 600/544
applicant:
INTERAXON INC.
pretty simple - its just a real time signal mapping system.
it also includes certain filters etc to map cerian desirable features (like for
ex: if u wanna map frequency)
patent name:
Real-time Cortical Mapping
US 20150313497 A1
US class: 600/544
applicant: The
Regents of the University of California
this is a wearable glasses kinda sensor that measures and
classifies brainwaves. once it determines that the person is eating (through
brain activity) it then proceeds to measure calories through any of several
ways (for ex, it has a built in camera to take photos of the food and record
it).
patent name:
Willpower Glasses (TM) -- A Wearable Food Consumption Monitor
US 20150313539 A1
US class: 600/544
applicant: Connor;
Robert A.
this method, in very few words, is a method to squeeze out
noise from brain signals. several examples are given for usage, including an
output based example where treatment for mental illness can be incorporated.
patent name:
METHOD FOR PROCESSING BRAINWAVE SIGNALS
US 20150327813 A1
US class:
600/383 600/300 600/409
600/473 600/544 600/509
applicant: Fu; Chi
Yung
A system capable of detecting a brain signal and stores it.
The user is shown a sequence of images, and the system detects the user’s brain
signals as he views them. Through analysis, the system associates user
intentions with the user’s brain signals.
patent name: Brain
signal-based instant search
US 20150250401 A1
US Class: 600/544
applicant: Tveit;
Amund
Method for identifying patient’s neurological/ mental
status. The method includes: measuring a brainwave signal containing noise,
denoising the signal, to acquire a clean brainwave signal, and and then
matching that obtained signal with a database of brainwave signals for
neurological and mental conditions.
patent name:
APPARATUS FOR TREATING A PATIENT
US 20150257700 A1
US Class: 600/544
; 345/156; 600/13; 600/15; 604/501; 604/503; 607/103; 607/98
applicant: Fu; Chi
Yung
Method in which EEG data relating to a plurality of subjects
diagnosed with ADHD is obtained, and for each of the plurality of subjects, at
least one feature from the EEG data relating to that subject; formulating a
prediction model by performing regression analysis and using that to for an
ADHD assessment.
patent name:
METHOD FOR ASSESSING THE TREATMENT OF ATTENTION-DEFICIT/HYPERACTIVITY DISORDER
US 20150073294 A1
US Class: 600/544
applicant: AGENCY
FOR SCIENCE, TECHNOLOGY RESEARCH; NATIONAL UNIVERSITY OF SINGAPORE; INSTITUTE
OF MENTAL HEALTH
A brain signal management system comprised of a controlling
module configured to transform a first signal which indicates a state of a
brain in a time reversal order and generate a second signal based on the
transformed first signal, and a stimulating module configured to send the
generated second signal to the brain or another brain.
patent name: BRAIN
SIGNAL MANAGEMENT SYSTEM AND BRAIN SIGNAL MANAGEMENT METHOD USING THE SAME
US 20150031980 A1
US Class: 600/410
; 600/300; 600/437; 600/473; 600/544
applicant: YBRAIN
INC.
Cloud server that contains a communication unit
communicatively connected with a wireless network to receive
electroencephalography information of a user; and a electroencephalography
information processing unit configured to analyze a mental state of the user
from the received electroencephalography information.
patent name: CLOUD
SERVER FOR PROCESSING ELECTROENCEPHALOGRAPHY INFORMATION, AND APPARATUS FOR
PROCESSING ELECTROENCEPHALOGRAPHY INFORMATION BASED ON CLOUD SERVER
US 20150126892 A1
US Class: 600/545
; 600/544
applicant:ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE
A variety of methods for cerebral diagnosis, including one
that is a signal conditioning module to condition signal data; a signal
analysis module to determine signal features and cerebral network features; and
a condition classification module to determine a cerebral condition of the
subject.
patent name:
METHODS AND SYSTEMS FOR BRAIN FUNCTION ANALYSIS
US 20150088024 A1
US Class:600/544
applicant:
University of Florida Research Foundation, Inc.
The above patents can be classified into a few categories.
1- patents on methods and algorithms to classify, map, and
optimize brainwave data
(5, 9, 12, 14, 18)
3- patents on measuring brain activity to determine emotion,
sleep stage, etc
(2, 6, 7, 8, 11, 15)
4- patents on devices to collect brain data and generate an
output
(1, 3, 4, 10, 13, 19)
5- patents to measure brain activity and utilize it
medically
(16, 17, 20)
→
We have concluded that we can do more research and progress on optimization and
utilization. As witnessed in the decision tree patent, piling algorithms
results in less noise and more accurate results. We can think of ways to
optimize our algorithm tree so as to isolate the most accurate data. We can
then patent it in reference to a specific field, as seen above. For ex: if we
determine that a certain frequency band holds the most potential for accurate
results for our specific experiment, and we then compile a pattern of
classification methods to thin down the data to the desired results, we can
patent that specific pattern on that certain frequency in relation to the
field.
Saturday, November 7, 2015
Some Resource from Last Year
I just dug out some old resource from last year. They might give you some insight to what STEM
students have came across last year.
Video resource:
http://videolectures.net/bbci09_blankertz_muller_mlasp/
Problems they have encountered:
Problems:
Classifier XML file:
https://drive.google.com/a/erhsnyc.net/file/d/0B4er4OWY8aPMSFF1R05ZMXBXd2M/view?usp=sharing
students have came across last year.Video resource:
http://videolectures.net/bbci09_blankertz_muller_mlasp/
Problems they have encountered:
Questions: How do we perform linear discriminant analysis (LDA) on
filtered alpha and beta waves to produce a coefficient necessary for
proper data collection?
-Unable to
determine the proper utilization of the <Identity> function.
<Identity> function is required when using a (.ov) file but not
with a (.csv) file stimulation, which required input and output
assignments, are only integrated into the (.ov) file.
-Unclear about the function of <Feature Aggregator>
-Parameters
for the <Classifier Trainer> are not determined because of
limited knowledge on the processing and organization of data
Ex. What are the functions
Classifier Trainer(
"Multiclass Strategy"
"Train Trigger"
"K-Fold Cross Validation Test"
"Class Label"
)
What We have:
Filtered Data
Some knowledge on LDA
Displaying Data
Creation of .ov and .csv files
Essentially,
how do we configure <Classifier Trainer> settings to get proper
coefficients. Is there a method to verify the accuracy of out data and
of the coefficients.
https://drive.google.com/a/erhsnyc.net/file/d/0B4er4OWY8aPMSFF1R05ZMXBXd2M/view?usp=sharing
Saturday, October 31, 2015
Progress Report 3
This past week was a short one, primarily because we missed STEM class on Tuesday due to the College English field trip. On Thursday, we continued to explore and follow the OpenVIBE sample scenario tutorials and proceeded to create them using the OpenVIBE Designer application. In particular, completed 'Designer Tutorial 4: Window Manager' (http://openvibe.inria.fr/designer-tutorial-4/). We followed the tutorial and ended up creating a series of displays and topographic maps:
Next week, we plan to wrap up the OpenVIBE simple scenario tutorials and use our newly founded navigational skills to create our scenarios. We will look to Andre's and Ryan's scenarios from last year to guide us through the process. In addition, we hope to figure out a way to connect the NeuroSky Mindwave headset to Openvibe on the Windows computer, as we will need our brain data in the future. Lastly, we will continue to update our Gantt Chart on the basis of changes to our plans.
Sunday, October 25, 2015
progress report 2
Since
the past progress report we have not made much progress on our issue connecting
the neurosky headset to a windows computer. Apparently, windows obnoxiously
keeps rejecting the neurosky driver and installing their own, which then won’t
succesfully connect. Although we have worked with the neurosky drive and looked
for help on several online forums, we could not find a solution.
Our
project is multi-faceted, though. We have learned that instead of sitting on
that problem and halting the rest of our work until we find a solution, we can
focus on a different aspect of our research. We have done so by directing our
attention towards OpenVibe.
Using
one of the computers the last year’s OpenVibe group used, we explored the
OpenVibe platform as per our past research. We utilized the tutorials on
OpenVibe’s website and created our own few scenarios, using the given boxes.
The scenarios are not of heavy importance; they were just meant as exercises,
and taught us valuable OpenVibe navigation skills.
Next
week, we will continue with more OpenVibe tutorials to familiarize ourselves
with OpenVibe as authors. In addition, we will be utilizing last year’s
recorded EEG data in our scenarios, until we can successfully connect the
Neurosky headset.
We
have added a goal to our Gantt chart: we want, with the help of the OpenVibe
tutorials, build a functioning scenario with several boxes, maybe even
something pre-recorded like the handball game.
Tuesday, October 20, 2015
Tuesday, September 29, 2015
Friday, September 25, 2015
Sunday, September 20, 2015
Resource from Last Year
- Team Progress Report Blog: http://advstem2.blogspot.com/
- Project Resource including Gantt Chart: http://stem14-15.blogspot.com/2015/02/project-resource-biofeedback-games.html
RE: Initial Planning & Coordination
Project Description & Merits
Describe the project in your own words and list the
possible contribution your project can have to advance the field of STEM or
solve societal problems.
- Our project is concerned with interpreting brain signals using OpenViBE, which is an open source platform dedicated to designing, testing, and using brain-computer interfaces.
- Our project can be used in various ways. The technology of interpreting brainwaves and using them to control devices has far-reaching implications, especially for disabled people. Through OpenVIBE, we hope to design a BCI that may perhaps one day be used for convenience.
Group/Team Communication
Who will be involved in your project (team) and
relevant projects (group)? How to communicate effectively with each other? What
are the tools for project collaboration?
- Team - Brian Wong and Sarah Landau
- Groups - groups 4, 5, and 6
- The key to effective collaboration is communication. Updating each other on progress or complications will definitely make things smoother going ahead.
- How to communicate with other teams (5 & 6)? Have you set up some mechanism (chat group, Google doc, or Git Hub)?
- Since you are going to develop analysis and classification algorithms for team 5 & 6, you should understand their topics and tune your research directions accordingly. Of course, at the very beginning, you can start following something in the tutorials (maybe not directly related to their topics) for learning purpose. Once you set up the whole analysis, classification, and online testing mechanism, you can then modify it to adapt to their needs.
Prior Work/Resource Inventory
Go to the Project Resource website to
review the current resource and prior work. Update the page.
- Have you conduct your extensive literature survey?
Technology Analysis
Identify the scientific and technical
knowledge/skills involved in your project.
- Familiarization with the OpenVIBE platform
- Familiarization with the Neurosky Headseat (and Emotiv Insight headset)
- Should be in more details such as the flow chart of the signal processing and feature extraction, the classification algorithms (such as SVM and LDA), online testing, OpenVibe library, subject testing method/process, etc..
Competence
Identify skill sets, technical competence in your
group, and list the missing ones which need to be acquired.
- Sarah needs to polish up on physics
- Brian needs to familiarize himself with the OpenVIBE library
- You forgot to list what competence you already have.
·
Safety
Identify any safety issues regarding the build, use,
store, and dispose of materials and tools
- Nothing really to worry about.
Equipment, materials & budget
List the key materials and equipment required for
your project. Identify the key items needed to be purchased and their prices.
- Windows computer
- Nuerosky headset (and Emotiv Insight headset)
- Do you think you can share the headsets with them or you may need one for your team?
Schedule
What are the goals/milestones/plans of your project
in the next week? What are the task assignments for each team member?
- We will both sit down and compare our notes on the summer assignments. We will also review the assignments and try to operate the OpenViBE with the headset together.
Saturday, September 12, 2015
Initial Planning & Coordination
·
Project Description & Merits
Describe the project in your
own words and list the possible contribution your project can have to advance
the field of STEM or solve societal problems.
- Our project is concerned with interpreting brain signals using OpenViBE, which is an open source platform dedicated to designing, testing, and using brain-computer interfaces.
- Our project can be used in various ways. The technology of interpreting brainwaves and using them to control devices has far-reaching implications, especially for disabled people. Through OpenVIBE, we hope to design a BCI that may perhaps one day be used for convenience.
·
Group/Team Communication
Who will be involved in your
project (team) and relevant projects (group)? How to communicate effectively
with each other? What are the tools for project collaboration?
- Team - Brian Wong and Sarah Landau
- Groups - groups 4, 5, and 6
- The key to effective collaboration is communication. Updating each other on progress or complications will definitely make things smoother going ahead.
· Prior
Work/Resource Inventory
Go to the Project
Resource website to review the current resource and prior work. Update
the page.
·
Technology Analysis
Identify the scientific and
technical knowledge/skills involved in your project.
- Familiarization with the OpenVIBE platform
- Familiarization with the Neurosky Headseat
·
Competence
Identify skill sets,
technical competence in your group, and list the missing ones which need to be
acquired.
- Sarah needs to polish up on physics
- Brian needs to familiarize himself with the OpenVIBE library
·
Safety
Identify any safety issues
regarding the build, use, store, and dispose of materials and tools
- Nothing really to worry about.
·
Equipment, materials & budget
List the key materials and
equipment required for your project. Identify the key items needed to be
purchased and their prices.
- Windows computer
- Nuerosky headset
·
Schedule
What are the
goals/milestones/plans of your project in the next week? What are the task
assignments for each team member?
- We will both sit down and compare our notes on the summer assignments. We will also review the assignments and try to operate the OpenViBE with the headset together.
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