U.S. patent application number 14/921115 was filed with the patent office on 2016-02-11 for system and method to provide career counseling and management using biofeedback.
The applicant listed for this patent is INTERNATIONAL BUSINESS MACHINES CORPORATION. Invention is credited to Christian Eggenberger, Peter K. Malkin, Jeffrey W. Mersereau, Andreas J. Schindler.
Application Number | 20160042658 14/921115 |
Document ID | / |
Family ID | 43465768 |
Filed Date | 2016-02-11 |
United States Patent
Application |
20160042658 |
Kind Code |
A1 |
Eggenberger; Christian ; et
al. |
February 11, 2016 |
SYSTEM AND METHOD TO PROVIDE CAREER COUNSELING AND MANAGEMENT USING
BIOFEEDBACK
Abstract
An apparatus and method for measuring a person's biometric data
as well as associated data and for using that data to determine the
person's talents and well-being state, as well as predicting an
optimal career path for the person. Biometric data is measured
using a sensor, a memory configured to store the biometric signals,
a database configured to store and retrieve profiles, and a
processor configured to compare biometric data as well as
associated data with anonymous profiles stored in the database and
create a profile for the person.
Inventors: |
Eggenberger; Christian;
(Zurich, SZ) ; Malkin; Peter K.; (Hawthorne,
NY) ; Schindler; Andreas J.; (Zurich, SZ) ;
Mersereau; Jeffrey W.; (Bakersfield, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
INTERNATIONAL BUSINESS MACHINES CORPORATION |
ARMONK |
NY |
US |
|
|
Family ID: |
43465768 |
Appl. No.: |
14/921115 |
Filed: |
October 23, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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12504238 |
Jul 16, 2009 |
9179847 |
|
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14921115 |
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Current U.S.
Class: |
702/19 ;
434/219 |
Current CPC
Class: |
A61B 5/167 20130101;
A61B 5/024 20130101; A61B 5/165 20130101; G09B 5/02 20130101; G06Q
10/105 20130101; G09B 19/00 20130101; A61B 5/02405 20130101; G06Q
30/02 20130101 |
International
Class: |
G09B 19/00 20060101
G09B019/00; G06Q 10/10 20060101 G06Q010/10; G09B 5/02 20060101
G09B005/02 |
Claims
1. A system for creating biometric profiles comprising: a sensor
configured to measure a person's biometric signals; and a processor
configured to process the biometric signals to produce a life fire
graph, the life fire graph comprising a heat map that correlates an
intensity of change in the biometric signals at different
frequencies at different points in time, further configured to
compare the life fire graph to a plurality of stored biometric
profiles, and further configured to evaluate at least one
personality characteristic of the person based on correlations with
the plurality of stored profiles.
2. The system of claim 1, wherein the measured biometric data
includes Heart Rate Variability data.
3. The system of claim 1, wherein the measured biometric data
includes skin conductivity.
4. The system of claim 1, wherein the measured biometric data
includes brainwaves.
5. The system of claim 1, wherein the measured biometric data
includes blood sugar levels.
6. The system of claim 1, further comprising a database that
includes a knowledge management system where at least one of
competency, associated well-being state, and an associated
performance rating of a plurality of users are stored.
7. The system of claim 1, wherein the processor includes an alert
mechanism which is triggered when a mismatch occurs between a given
person's biometric data and a job role.
8. The system of claim 1, wherein the sensor and processor are
contained within a single, self-contained device that is small
enough to be worn under a user's clothing.
9. The system of claim 1, wherein the processor is further
configured to process the biometric signals using a Fourier
transform.
10. A method for determining an optimal job for a given user
comprising: processing a user's biometric signals to produce a life
fire graph, said life fire graph comprising a heat map that
correlates an intensity of change in the biometric signals at
different frequencies at different points in time; and correlating
the user's life fire graph with a plurality of known life fire
graphs using a processor to determine job roles with a high
probability of good performance and health for the user.
11. The method of claim 10, wherein the biometric data includes
Heart Rate Variability information.
12. The method of claim 10, wherein the characteristic traits
include at least one competency.
13. The method of claim 10, wherein the characteristic traits
include the given user's well-being state.
14. The method of claim 13, wherein the information to determine
the characteristic traits and the matching job role are retrieved
from a knowledge management system where the characteristic traits
and the associated performance rating of a significant number of
users are stored.
15. The method of claim 14 wherein a competency includes
information about personal characteristics such as motives, traits,
self-image, social role, and information about the skills and
knowledge of a user.
16. A computer readable storage medium comprising a computer
readable program for determining an optimal job for a given user,
wherein the computer readable program when executed on a computer
causes the computer to perform the steps of: processing a user's
biometric signals to produce a life fire graph, said life fire
graph comprising a heat map that correlates an intensity of change
in the biometric signals at different frequencies at different
points in time; and correlating the user's life fire graph with a
plurality of known life fire graphs using a processor to determine
job roles with a high probability of good performance and health
for the user.
Description
BACKGROUND
[0001] 1. Technical Field
[0002] The present invention relates to biofeedback methods and
devices, and more particularly to systems and methods for career
consulting and management using biometric information such as heart
rate variability data.
[0003] 2. Description of the Related Art
[0004] Currently, career-based consulting and management is based
on either a given employee's performance ratings (e.g., measured by
client satisfaction surveys, 360.degree. peer or manager surveys),
or on the results of questionnaires or interviews answered by the
given employee. Both of these fundamental source types have their
limitations. Job performance results can be highly influenced by
elements such as interpersonal relationships between the given
employee and others, e.g., their manager, or job location. Answers
to questionnaires or interviews are limited in that the given
answers are in one extreme either wholly true (perhaps due to a
given employee's modesty), or at the other extreme greatly
exaggerated (if the interviewee is trying to inflate his or her
capabilities and/or accomplishments). The process of interviewing
employees can also be costly and time consuming, and bears the risk
that only part of all potential talents are discovered and
monitored.
SUMMARY
[0005] A system for creating biometric profiles includes a sensor
configured to measure a person's biometric signals. A memory is
configured to store the measured biometric signals. A database
stores and retrieves biometric profiles. A processor compares
biometric data stored in the memory to biometric profiles stored in
the database and creates a biometric profile for the person.
[0006] A method for determining an optimal job for a given user
includes measuring biometric data of a given user. The biometric
data is then used to determine characteristic traits of the given
user. The user is then matched to a job role based upon the
determined characteristic traits.
[0007] These and other features and advantages will become apparent
from the following detailed description of illustrative embodiments
thereof, which is to be read in connection with the accompanying
drawings.
BRIEF DESCRIPTION OF DRAWINGS
[0008] The disclosure will provide details in the following
description of preferred embodiments with reference to the
following figures wherein:
[0009] FIG. 1 is a block diagram of a method for matching a person
to a job role based upon their competencies in accordance with an
illustrative embodiment.
[0010] FIG. 2 is a graph depicting an example of a recorded
heartbeat.
[0011] FIG. 3a is a graph plotting time versus frequency as an
example of heart rate variability data characterizing
achievement.
[0012] FIG. 3b is a graph plotting time versus frequency as an
example of heart rate variability data characterizing will.
[0013] FIG. 3c is a graph plotting time versus frequency as an
example of heart rate variability data characterizing
intuition.
[0014] FIG. 3d is a graph plotting time versus frequency as an
example of heart rate variability data characterizing change.
[0015] FIG. 3e is a graph plotting time versus frequency as an
example of heart rate variability data characterizing
innovation.
[0016] FIG. 4 is a block/flow diagram illustrating a system which
generates a heart rate variability profile in accordance with an
illustrative embodiment.
[0017] FIG. 5 is a block diagram of a method for determining a
career path in which a person will perform well and maintain an
optimal well-being in accordance with an illustrative
embodiment.
[0018] FIG. 6 is a block diagram of the steps required to build a
set of biometric profiles.
[0019] FIG. 7 is a block diagram of a method for providing ongoing
career counseling to a user.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0020] A person's bio-feedback is a good indicator of who a person
is and how that person is feeling. Bio-feedback can indicate not
only the person's physical well-being, but also their emotional
well-being state and their talents. The present principles are
directed to a system and method which measures a person's biometric
data and builds a profile for that person representing the person's
talents and well-being state. The profile may also include
associated data, such as the person's competencies and traits. It
compares the measured profile to other profiles corresponding to a
plurality of previously measured people, and provides indications
as to what sort of roles the person would be best suited to.
[0021] As will be appreciated by one skilled in the art, aspects of
the present invention may be embodied as a system, method or
computer program product. Accordingly, aspects of the present
invention may take the form of an entirely hardware embodiment, an
entirely software embodiment (including firmware, resident
software, micro-code, etc.) or an embodiment combining software and
hardware aspects that may all generally be referred to herein as a
"circuit," "module" or "system." Furthermore, aspects of the
present invention may take the form of a computer program product
embodied in one or more computer readable medium(s) having computer
readable program code embodied thereon.
[0022] Any combination of one or more computer readable medium(s)
may be utilized. The computer readable medium may be a computer
readable signal medium or a computer readable storage medium. A
computer readable storage medium may be, for example, but not
limited to, an electronic, magnetic, optical, electromagnetic,
infrared, or semiconductor system, apparatus, or device, or any
suitable combination of the foregoing. More specific examples (a
non-exhaustive list) of the computer readable storage medium would
include the following: an electrical connection having one or more
wires, a portable computer diskette, a hard disk, a random access
memory (RAM), a read-only memory (ROM), an erasable programmable
read-only memory (EPROM or Flash memory), an optical fiber, a
portable compact disc read-only memory (CD-ROM), an optical storage
device, a magnetic storage device, or any suitable combination of
the foregoing. In the context of this document, a computer readable
storage medium may be any tangible medium that can contain, or
store a program for use by or in connection with an instruction
execution system, apparatus, or device.
[0023] A computer readable signal medium may include a propagated
data signal with computer readable program code embodied therein,
for example, in baseband or as part of a carrier wave. Such a
propagated signal may take any of a variety of forms, including,
but not limited to, electromagnetic, optical, or any suitable
combination thereof. A computer readable signal medium may be any
computer readable medium that is not a computer readable storage
medium and that can communicate, propagate, or transport a program
for use by or in connection with an instruction execution system,
apparatus, or device.
[0024] Program code embodied on a computer readable medium may be
transmitted using any appropriate medium, including but not limited
to wireless, wireline, optical fiber cable, RF, etc., or any
suitable combination of the foregoing.
[0025] Computer program code for carrying out operations for
aspects of the present invention may be written in any combination
of one or more programming languages, including an object oriented
programming language such as Java, Smalltalk, C++ or the like and
conventional procedural programming languages, such as the "C"
programming language or similar programming languages. The program
code may execute entirely on the user's computer, partly on the
user's computer, as a stand-alone software package, partly on the
user's computer and partly on a remote computer or entirely on the
remote computer or server. In the latter scenario, the remote
computer may be connected to the user's computer through any type
of network, including a local area network (LAN) or a wide area
network (WAN), or the connection may be made to an external
computer (for example, through the Internet using an Internet
Service Provider).
[0026] Aspects of the present invention are described below with
reference to flowchart illustrations and/or block diagrams of
methods, apparatus (systems) and computer program products
according to embodiments of the invention. It will be understood
that each block of the flowchart illustrations and/or block
diagrams, and combinations of blocks in the flowchart illustrations
and/or block diagrams, can be implemented by computer program
instructions. These computer program instructions may be provided
to a processor of a general purpose computer, special purpose
computer, or other programmable data processing apparatus to
produce a machine, such that the instructions, which execute via
the processor of the computer or other programmable data processing
apparatus, create means for implementing the functions/acts
specified in the flowchart and/or block diagram block or
blocks.
[0027] These computer program instructions may also be stored in a
computer readable medium that can direct a computer, other
programmable data processing apparatus, or other devices to
function in a particular manner, such that the instructions stored
in the computer readable medium produce an article of manufacture
including instructions which implement the function/act specified
in the flowchart and/or block diagram block or blocks.
[0028] The computer program instructions may also be loaded onto a
computer, other programmable data processing apparatus, or other
devices to cause a series of operational steps to be performed on
the computer, other programmable apparatus or other devices to
produce a computer implemented process such that the instructions
which execute on the computer or other programmable apparatus
provide processes for implementing the functions/acts specified in
the flowchart and/or block diagram block or blocks.
[0029] A data processing system suitable for storing and/or
executing program code may include at least one processor coupled
directly or indirectly to memory elements through a system bus. The
memory elements can include local memory employed during actual
execution of the program code, bulk storage, and cache memories
which provide temporary storage of at least some program code to
reduce the number of times code is retrieved from bulk storage
during execution. Input/output or I/O devices (including but not
limited to keyboards, displays, pointing devices, etc.) may be
coupled to the system either directly or through intervening I/O
controllers.
[0030] Network adapters may also be coupled to the system to enable
the data processing system to become coupled to other data
processing systems or remote printers or storage devices through
intervening private or public networks. Modems, cable modem and
Ethernet cards are just a few of the currently available types of
network adapters.
[0031] Certain biometric signals have been shown to be an indicator
not only of the person's physical well-being, but also an indicator
of the person's emotional well-being, as well as more abstract
personality traits, such as, e.g., capacity for achievement,
innovation, and intuition. The way a person's biometric signals
change over a period of time provides an indication as to the
condition and potential of that person. After measuring the
person's biometric data over the course of a period of time and
analyzing the data with mathematical transform suited to the type
of signal, the resulting data can be compared to a database of
other people's previously accumulated biometric data profiles to
determine the person's attributes. These accumulated profiles have
associated with them the known traits, competencies, and well-being
states of their respective users.
[0032] The information gleaned from the biometric data analysis can
then be used to counsel the person with regard to, for example,
career path and well-being activities.
[0033] Referring now in detail to the figures in which like
numerals represent the same or similar elements and initially to
FIG. 1, an exemplary method for matching a person to a job role
based on their competencies is illustratively depicted. In block
102, raw biometric data is collected for the person over a period
of time. It is contemplated that this data can include any of a
number of different forms of biometric data (e.g., skin
conductivity, brainwaves, blood sugar levels, or other signals from
the sympathetic or parasympathetic nervous systems) but for the
sake of simplicity only heart rate variability is described
herein.
[0034] At block 104, the raw biometric data is processed to form a
biometric profile. Block 106 compares the biometric profile to a
database of known biometric profiles. Block 108 uses correlations
between the measured biometric profile and the stored biometric
profiles to determine the competencies of the person. Block 110
uses correlations between the measured biometric profile and the
stored biometric profiles to determine the person's physical
well-being. A person's internal state, their health, and their
talents are made manifest by their body's reactions. For example,
the body reacts naturally to stress, and it produces different
responses depending on a person's ability to handle stressful
situations. By measuring the person's autonomic responses, it is
possible to gain significant insight into that person.
[0035] Taking the person's competencies and well-being into
account, block 112 matches the person to the best available job
role. As an example, using this method, one could detect that the
person is highly negatively stressed and give him/her a relaxing
job role or a positive stress producing job role which will give
him/her an opportunity to recover. If a person is exceptionally
talented, he/she may receive job roles which allow him/her make
best use of his or her talents. This makes it possible to help the
person reach his or her potential while staying healthy and
productive. It is contemplated that these traits and others might
be accounted for in a person's profile.
[0036] One example of biometric data that can be used for this
purpose is Heart Rate Variability ("HRV"). HRV is a measurement of
how the timing between heartbeats changes over time. A heartbeat
graph 200 is illustratively shown in FIG. 2. The time between
individual beats 204 is called the RR interval 202. "RR interval"
is defined as the time between two "R waves" of an ECG. HRV is
calculated by collecting data on the heartbeat 200 for a period of
time (for example, 24 hours, although other periods are
contemplated) and measuring each RR interval with a high sampling
resolution (for example, 4,000 to 5,000 Hz). Calculating the
standard deviation of the RR intervals over a given period of time
yields a measurement of HRV: a low standard deviation indicates a
low HRV, while a high standard deviation indicates a high HRV.
[0037] By performing a Fourier transform (or other mathematical
transform) on the collected heartbeat data, one can produce a graph
called a "life fire." FIGS. 3a-e are examples of different life
fires. The horizontal axis represents time, while the vertical axis
represents the frequencies at which the RR interval 102 is changing
at that point in time. Darker colors represent larger amounts of
change at those frequencies.
[0038] HRV information can then be correlated with the person's
well-being state, as it is indicative of stress and sickness. HRV
measurements can also be correlated with various personal traits.
FIGS. 3a-e represent HRV measurements that, according to one model
for interpretation, characterize people with high achievement (FIG.
3a), will (FIG. 3b), intuition (FIG. 3c), change (FIG. 3d), and
innovation (FIG. 3e). In each of the figures, the dotted areas with
thick lines represent frequencies which manifest the strongest, the
areas with angled lines show medium frequencies, and the solid
white areas are frequencies which manifest weakly. For example,
according to this exemplary model, measuring a strong HRV response
in the range 0.15 Hz to 0.4 Hz is an indication of having the
talent "intuition," while a strong HRV response in the range 0.0033
Hz to 0.04 Hz is indicative of "achievement." Other ranges and
combinations of ranges characterize other talents. These talents
are intended to be purely exemplary, as another model may interpret
the data as characterizing different traits, while still embodying
the present principles. The result of using such a model is that
concrete determinations may be made automatically by measuring
HRV.
[0039] Referring to FIG. 4, an embodiment of a system/method 400
designed to measure a person's biometric data and correlate that
data with the person's personal traits is illustratively shown. A
biometric monitor 401, in one embodiment, for example, a heart rate
monitor, tracks the person's biometric signals over a period of
time. The raw biometric data 402 is then stored in a memory 404.
After the data has been collected, a processor 406 analyzes the
biometric data stored in memory 404. In the case of HRV, this means
performing a transform of the data, e.g. a Fourier transform. The
processor 406 then compares the analyzed biometric data 408 to
biometric profiles 412 stored in a database 410. These biometric
profiles 412 correspond to various known character and physical and
emotional traits. The processor 406 builds a profile 414 for the
biometric data 408 which describes the character and physical and
emotional traits most likely possessed by the person.
[0040] The system just described can be used to perform the methods
in accordance with the present principles. Referring to FIG. 5, a
method for determining the optimal career path for a person is
illustratively shown. Blocks 502 and 504 collect and analyze the
raw biometric data, as in FIG. 1. Block 506 compares the biometric
data with known biometric profiles. Block 508 matches the biometric
data to people who have performed well in their careers, and block
510 suggests a career path for the person that will optimize their
performance and well-being. For example, if a person has a profile
similar to the profiles of successful managers and leaders, block
510 might involve determining that the person would be best suited
for a career path that will lead to management. As another example,
if a person's profile shows a high degree of adaptability, block
510 might involve determining that the person would be best suited
for a high-paced role with quickly-changing conditions.
[0041] Referring to FIG. 6, preliminary steps needed to make use of
the methods of the present system/method are illustratively shown.
Block 602 collects biometric data for a plurality of people. Block
604 then builds biometric profiles for the people "by hand," using
a person's known traits, competencies, and well-beings states.
Block 606 stores the profiles in a "knowledge management system."
Once the biometric data and the associated data have been collected
and the profiles have been created, the profiles should have no
connection to the identity of the people they represent to protect
the privacy of the people who make up the stored profiles. Once a
plurality of profiles have been stored, block 608 uses the present
principles to build new profiles from input biometric data, using
correlations between the input data and the stored profiles.
[0042] Referring to FIG. 7, a method for providing responsive
guidance to a user is illustratively shown. Block 702 generates
suggested career paths, competencies, and a well-being state for
the user as shown, for example, in FIG. 5. In block 704, an advisor
can then make a recommendation to the person regarding appropriate
tasks, open positions, well-being and learning activities, and what
measures he or she has to make short-term, mid-term, and long-term
advancements on the suggested career paths. These recommendations
are geared to be advisory, so that the person can make his or her
own choices regarding his or her career path. Although the advisor
may be a human, it is also contemplated that an automated system
may fill that role.
[0043] For example, consider a person applying for a job. The
person is just now entering the workforce and has little idea of
what roles or career paths he or she would be best suited for. The
person is provided with a biometric sensor which monitors their
biometric data for several hours. During this time the person
performs a standardized set of activities or keeps a logbook of
activities performed. The sensor stores the biometric information
using a memory device, or transmits the data to a database or
computer. The data is retrieved and analyzed using one or more of
the techniques listed above. Conclusions are drawn based upon the
comparisons as to whether the person is well-suited for the job.
This provides benefits to the person, because he or she will not
end up in a job that is significantly above or below his or her
ability, and it provides benefits to the employer, because the
employer can streamline the hiring process.
[0044] Another example is a person who has been in the workforce
for some time, but who, due to changed circumstances or the simple
passage of time, has realized that he or she is no longer
interested or well-suited to his or her job role. The person may
then speak to a career counselor who makes use of the present
system and methods to make recommendations. This can lead the
person to pursue a new career path that he or she will be more
successful at, and will find more fulfilling.
[0045] In block 706, the person may continue to obtain periodic
measurements of their biometric data as well as the associated
data. Block 708 shows that these subsequent measurements will allow
the advisor to build a history and track the person's advancement
along the proposed career path. Such monitoring also makes it
possible to note any abnormalities with regard to the person's job
performance and health (i.e., when the person is neither successful
in his or her job role, nor healthy). If an abnormality is detected
in block 710, the advisor makes suggestions regarding changes that
the person can make to get back on track, or suggestions regarding
a new career path that will better suit the user's current
characteristic traits and well-being state.
[0046] The flowchart and block diagrams in the Figures illustrate
the architecture, functionality, and operation of possible
implementations of systems, methods and computer program products
according to various embodiments of the present invention. In this
regard, each block in the flowchart or block diagrams may represent
a module, segment, or portion of code, which comprises one or more
executable instructions for implementing the specified logical
function(s). It should also be noted that, in some alternative
implementations, the functions noted in the block may occur out of
the order noted in the figures. For example, two blocks shown in
succession may, in fact, be executed substantially concurrently, or
the blocks may sometimes be executed in the reverse order,
depending upon the functionality involved. It will also be noted
that each block of the block diagrams and/or flowchart
illustration, and combinations of blocks in the block diagrams
and/or flowchart illustration, can be implemented by special
purpose hardware-based systems that perform the specified functions
or acts, or combinations of special purpose hardware and computer
instructions.
[0047] Having described preferred embodiments of a system and
method (which are intended to be illustrative and not limiting), it
is noted that modifications and variations can be made by persons
skilled in the art in light of the above teachings. It is therefore
to be understood that changes may be made in the particular
embodiments disclosed which are within the scope and spirit of the
invention as outlined by the appended claims. Having thus described
aspects of the invention, with the details and particularity
required by the patent laws, what is claimed and desired protected
by Letters Patent is set forth in the appended claims.
* * * * *