White Paper 13 March 2013

Innoception Technologies LLC is pioneering an Integrative Health platform for untethered

measurement of health parameters for an online, cloud-based format. This platform combines

off-the-shelf and proprietary technologies from a recently successful crowdsourcing effort to

produce a reliable, consistent process that quantizes wellness. This collaboration brings the most

progressive available technologies together on a platform that will allow the customer to track

his/her health in a dynamic and accurate online way.

It has been surmised for some time that there is an optimum range of physiological functioning

that will allow health providers unprecedented accuracy in assigning customers to wellness

profiles across demographic and diagnostic groups. Our approach to capturing this

neurophysiological state takes into account the diversity of the human species, reflecting the

genomic adaptability that explains our success on this planet. Revealing physiological baseline

information in a dynamic context goes beyond the understanding of traditional medicine in

regards to disease management to a predictive one that emphasizes the importance of returning

the individual to his/her optimum physiological baseline. Operating within their unique

parameters will make possible their most efficient use of medical interventions and allow quick

rehabilitation and recovery from health challenges of all kinds. This approach will also reveal

new information about global wellness issues like immune system functioning and recovery,

since the immune system’s optimum functioning is the true key to lifelong wellness. This paper

presents an overview of the collaborative roles that will allow this approach to Integrative Health

and wellness to succeed and give a concise and integrative view of the true promise of

personalized health.

This paper discusses the format for this ongoing enquiry along with the market forces which

affect the adoption of a new approach to health that emphasizes wellness. A unique collaboration

among several existing businesses and their proprietary technologies will allow this effort to

proceed. Also, the location at the University of Utah will give access to critical resources for

genomic enquiry and data management that exist nowhere else. Innoception Technologies LLC is

a Medical Technology startup licensed at the University of Utah Technology Commercialization

Office. We are unique in having a broad support base across five major departments at the U/U.

We have two specific patents licensed to us that offer us impressive market advantages. One is a

process patent for concurrent measurement of biosignals during a therapeutic or medical

intervention. Another is a unparalleled approach to ‘big data,’ “NDV” or n-dimensional

visualization developed by the head of our science advisory board and former head of Computer

Science at the U/U, Robert Johnson PhD. Analysis of biosignals with their orthogonal fields adds

to the specificity and sensitivity of accurate diagnostic formulations. Individuals within our team

have been measuring patterns made by the brain/body’s physiological subsystems since 2005.

We have rediscovered the nonlinear nature of biological systems, where system output is not a

straight line function of its input. Nonlinear systems are both stable and flexible as they go about

task performance. We have chosen three physiological signals that fluctuate orthogonally to each

other, allowing us to define a “corridor of normal”, age and sex specific, for each biosignal,

where individual clinical conditions fall outside this corridor in characteristic ways.

On a small scale, many studies have shown the utility of applying multivariate analysis and data

mining techniques to medical data. Innoception’s approach will be unique for examining the

collective effect of many parameters for relevance to health disorders. Multiparameter analysis

(MPA) techniques include vector fusion, Shannon information analyses and other topological

data mining approaches. These are expected to indicate how specific groups of bio-signal

parameters collectively enhance or diminish correlation patterns with specific neurophysiological

states associated with anxiety disorders, for example. Development of effective MPA methods,

using archived data when possible, will be the focus during the first year. Standard statistical

approaches in medical research are generally too limited to appreciate the physiological diversity

that determines lifelong wellness. The challenges of capturing optimum human functioning are

also the challenges of ‘big data’ and in the future, HIPAA-related concerns for data capture and

maintenance will not only focus on patient protection but also the ability to maintain the Value of

Information (VOI). As a part of healthcare reform, many health stakeholders are grappling at

present with the portability of information across HIEs (Health Information Exchanges) where

most traditional health entities are for the first time addressing core empirical issues in terms of

how meaningful health data is captured and maintained in the context of personalized healthcare

and the integration of dissimilar data sources. The proposed collaboration will result in a ‘best

practices’ model since biophysiological data will be analyzed across a spectrum of integrative

health interventions which evidence the greatest therapeutic benefit in these conditions. Then

healthy information will lead to a greater variety of choices for the healthcare consumer and

allow a collaborative approach to health. Biopsychosocial phenomenon and social factors

dynamically interact and affect the individual’s ability to adapt. The most promising therapies for

traumatically induced biophysiological conditions are often integrative and holistic approaches to

symptom management.

I. Traumatic experience, disability and Health Events:

The heart receives neural stimulation from both the sympathetic and parasympathetic ANS

components. Blood pressure regulation is one of the most important ANS functions.

Baroreceptor cells in the heart and blood vessels sense pressure and send afferent signals to the

brain where components of the ANS that control heart rate and vascular tonus via sympathetic,

and to a lesser extent parasympathetic, activity. This is a dedicated feedback control system to

maintain blood pressure within proper limits by adjusting heart rate and cardiac output in

response to environmental and emotional influences. Thus heart rate is recognized as a basic

measure of ANS function. Other factors affecting cardiac regulation include respiration,

thermoregulation, and humoral regulation, whose ANS influences also reflect neurophysiological

status is subtle ways.

The cardiovascular bio-signal parameters briefly described below reflect various aspects of ANS

activity; they will be studied using multiparameter analysis for relevancy as potential individual

or clustered markers for anxiety disorders.

Blood Pressure

Heart Rate (HR) High resting heart rate is also associated with increased risks of adverse

outcomes for coronary artery disease (CAD).

Heart Rate Variability (HRV) is an important parameter for reflecting ANS status.

Physiologically, a significant increase in HF/LF power, followed by a sharp decrease is cited as a

predictor of paroxysmal atrial fibrillation (PAF), and low HRV reflects poor cardiac health.

Complicating issues include HRV reflection of both sympathetic and parasympathetic activity,

and significant HRV differences are commonly found between individuals.

P-wave dispersion and variability have been the focus of several recent research studies. The Q-

T interval A technique using root-mean square values across multiple ECG leads has been used at

the University of Utah to obtain reliable Q-T intervals for research projects. QT dispersion may

be associated with increased risks of arrhythmic events and syncope, and it may predict sudden

cardiac death in variety of disease states such as acute myocardial infarction and hypertrophic

cardiomyopathy.

Respiratory Sinus Arrhythmia (RSA) is related to the HF peak in the HRV spectrum and it

primarily indicates parasympathetic ANS activation

Baroreflex sensitivity (BRS) associates reduced parasympathetic function with PTSD in males,

but a recent study found contrary gender effects in BRS among smokers.

Vagal tone is a positive indicator of stress and is considered important parameters for

characterizing anxiety disorders.

The characteristics of these bio-signals will be studied and classified quantitatively as potential

contributors for developing multiparameter bio-signal marker patterns for neurophysiological

conditions and states such as anxiety disorders.

1.- ECG

2.- Diastolic Blood Pressure (DBP)

3.- Systolic Blood Pressure (SBP)

4.- Glucose Test (GT)

5 .- Average glucose for the past 8 weeks test (H1A1c Test)

6.- Type of medication used.

7.- High Density Lipoprotein (HDL)

8.- Low Density Lipoprotein (LDL)

9.- Weight (WT)

10,- Fast Plasma Glucose test

11.- Body mass Index (BMI)

We will be seeking to additionally develop new areas where the analysis methods and data

mining approaches we possess offer great promise. For example, In 2000, according to the World

Health organization (WHO), at least 171 million people or 2.8% of the population suffered from

diabetes. The number is increasing rapidly, and by 2030, the number will double. Type 2 diabetes

is more common in the Western world, where urbanization and lifestyle changes have increased

the prevalence of the illness, and an environmental (dietary) affect is implied. Type 2 affects up

to 95% of the US diabetes population. 18.6% of those above 60 have diabetes, from the National

Health and Nutrition Examination Survey. In particular, the system we propose specifically

predicts the diabetes variables of a patient for the next scheduled doctor’s visit. Alarming values

in these predictions can trigger automatic warnings to the medical professional allowing for

scheduling more frequent visits, which allows the medical professional to timely intervene. To

predict the future diabetes variables from past data, we propose to use artificial intelligence and

machine learning techniques. Our algorithms will be trained on the existing rich set of patient

data in the Utah diabetes database. Various AI and ML techniques are candidates to be adapted to

successfully achieve this goal. One approach would be to view the patient as a dynamical

system, whose dynamics equations (governing the evolution of its state over time) are unknown.

Various AI and ML techniques exist to learn these dynamics equations from past data. Given

such a dynamics model, it can readily be used to predict the patient’s state into the future, and it

is able to provide a measure of (un)certainty about its prediction. Another class of techniques

builds on Artificial neural networks (ANN), which is a powerful empirical pattern-recognition

and mapping tool for different data, including approximation of complex nonlinear relationships,

as well as different outcomes that characterize individualized epidemiological trajectories. In

personalized healthcare, these trajectories are revealed as epigenetic influences accompanied by

discrete medical indicators. Instead of imposing an a priori model on the data, ANN learns input

and output relationships directly from the data. The flexibility of the ANN models has led to

successful application in population pharmacokinetic and pharmacodynamic data analysis.

Standard medical information and local clinical studies will be related to one or more

conventional psychiatric scale metrics such as the Hamilton Anxiety Scale, Hamilton Depression

Scale, Positive and Negative Syndrome Scale, Clinician-administered PTSD Scale, Mississippi

Scale for Combat-Related PTSD, and Watson's criteria for PTSD in the veteran arms of the

studies. This provides well documented classification references for each bio-signal record.

Local clinical studies are planned for the second year to verify MPA results. Laboratory serum

assays will be collected to determine the levels of stress markers such as cytokines and

chemokines to further verify the results through multiparameter analysis techniques. Lastly, since

the ECG inherently reflects many aspects of the heart’s physical status, it is possible that in the

process of mining neurological information from ECG parameters, Innoception may also

uncover new marker patterns for certain cardiovascular conditions. This possibility is considered

a secondary facet of the proposed research project, and relevant discoveries in the cardiovascular

areas will be documented for further investigation. It should be observed that A-Fib and other

chronic heart conditions may have a higher incidence in veteran populations than in the general

population. Innoception will develop and employ multiparameter analysis techniques in a

structured investigation of complex bio-signal parametric relationships associated with anxiety

disorders in the ECG bio-signal. As progress is made in discovering collective ECG parameter

correlations to anxiety traits, additional bio-signal parameters from other bio-signals, such as

blood pressure, and skin conductance will be included in the study to develop a multi-modal

approach for objective neurological state analysis.

II. Collaborators

Drs Ed Fila and Regina Drueding (co-founders) have been pioneers and successful entrepreneurs in CVD

prevention and CIMT development. They, in prior entities, developed the CIMT software that received

FDA approval, sold to an ultrasound manufacturer, and established several CIMT outsourcing companies

that today are the primary industry players. Dr. Fila has also been intimately involved in researching

cancer prevention (including researching facilities or practitioners getting exceptional results), treating

depression, getting metals out of the body, reducing effects of radiation, etc. (all major drivers of CVD),

A seasoned corporate executive, Fortune 500 consultant and entrepreneur, Bruce Collett will lead the

effort to establish cardiovascular measurement with this technology. Two other founders contribute

engineering, QC, project management, IT systems, marketing and business skills.

Tomasz Petelenz PhD and Robert Tuckett PhD will guide the bioengineering aspects of the project, both

with extensive experience in the assessment and measurement of relevant physiological parameters that

relate to health and wellness.

Proprietary technologies that will be utilized include biochemical analysis of the breath, developed by

Royce Johnson PhD, and the use of blood markers to quantize the neurological level of

functioning/injury developed by Banyan Pharma. We feature the combination of these new technologies

that we consider critical to the capture of a meaningful and accurate dynamic measurement of

physiological baseline and will actively collaborate with them in utilizing these proprietary technologies

on the Innoception platform.

Breath analysis for health diagnosis and management: The principle long-term target for EZKnowz™ is

for health diagnosis and health management, through breath or odor analysis. We all know that the

“elephant in the room” is the extremely high cost of healthcare and that current proposed solutions are

not adequate. In search of fresh approaches, it worth noting that the computer technology industry is

one of the few industries where the cost becomes lower year after year, driven by Moore’s Law, where

computer power doubles every 18 months. Creative coupling of this digital power offers a chance to rein

in the spiraling cost of healthcare. The question is: What is the optimal way of implementation of

computing power and internet communication in the healthcare industry?

One great possibility of healthcare cost reduction is to find a solution to “the fact that much time and

money is spent on patients visiting their doctors or a clinic and too little attention is afforded to

preventive care”. Improvements in preventive diagnostics will help reduce hospital admission costs and

allow patients to be cared for at home, for longer. The biggest issue is keeping patients out of hospitals.

Simple diagnostic devices are needed that operate at the personal level and that can universally monitor

the health status of individuals in a home environment in real time. These diagnostic devices should be

able to digitize the collected information and use the internet to transfer data and communicate with the

doctor’s offices. Powerful consumer gadgets already exist that are simple to use and consistent with the

existing PCs infrastructure, whether this is smart phone, IPad, a notebook, etc. Our vision is to emulate

the IT/PC revolution by empowering the individuals with digital, personal, real time monitoring devices

for the purpose of preventive care and facilitating early diagnostics. why we cannot communicate with

doctors without face to face meetings, and there is no reason that preventive care should not have

excellent remote medical coverage. We and many others believe that there is a huge business

opportunity here!

For example, one study has identified as many as 3,481 components in human breath. Already

correlations between increases in specific components (markers) with physiological sources and

conditions have been identified (lung cancer, influenza, tuberculosis, etc.). Advantages are:

Non-invasive (painless),

Sample is easy acquire,

Information rich,

Digital information available immediately,

Low-cost and easy to administer.

Patented claims to protect these concepts and the first issued claims are published in “Analysis of Gases”

(Issued European Patent EP 1 976 431 B1).

Use of biomarkers in neurological functioning/injury. Although there are a number of

biochemical markers that have been investigated in TBI, our discussion will include the most

current and widely studied ones. The most extensively studied among these are glial protein S-

100 beta(β) 45-55, neuron-specific enolase (NSE)56-63, and myelin basic protein (MBP)41, 59,

64-66 Although some of these published studies suggest that these biomarkers correlate with

degree of injury; conflicting results exist (3-11). S100β is the major low affinity calcium binding

protein in astrocytes (3) and it is considered a marker of astrocyte injury or death. It can also be

found in non-neural cells such as adipocytes, chondrocytes, and melanoma cells (12). Elevated

serum levels have been associated with increased incidence of post concussive syndrome and

impaired cognition (13,14). Other studies have reported that serum levels of S-100β are

associated with MRI abnormalities and with neuropsychological examination disturbances after

mild TBI (15,16). A number of studies have found significant correlations between elevated

serum levels of S-100β and CT abnormalities (17-19). It has been suggested that adding the

measurement of S-100B concentration to clinical decision tools for mild TBI patients could

potentially reduce the number of CT scans by 30%.84 Other investigators have failed to detect

associations between S-100β with CT abnormalities (3,20-22). The vast majority of these clinical

studies have employed ELISA to measure levels of S100B. Although S-100β continues to be

actively investigated and remains promising as an adjunctive marker, its utility as a biochemical

diagnostic remains controversial. Some studies have observed high serum S-100β levels in

trauma patients without head injuries suggesting that it lacks CNS specificity and is released

from peripheral tissues (23-25).

Neuron specific enolase is one of the five isozymes of the gycolytic enzyme enolase found in

central and peripheral neurons and it has been shown be elevated following cell injury (26). It

has a molecular weight of 78 kDa and a biological half-life of 48 hours (27). This protein is

passively released into the extracellular space only under pathological conditions during cell

destruction.

Most studies employed an enzyme immunoassay for NSE detection. Many of these studies either

contained inadequate control groups or concluded that serum NSE had limited utility as a marker

of neuronal damage. Early levels of NSE and MBP concentrations have been correlated with

outcome in children, particularly those under 4 years of age(1,2,28,29). A limitation of NSE is

the occurrence of false positive results in the setting of hemolysis (30).

A supposedly cleaved form of tau, c-tau, has also been investigated as a potential biomarker of

CNS injury. Tau is preferentially localized in the axon and tau lesions are apparently related to

axonal disruption (31,32). CSF levels of c-tau were significantly elevated in TBI patients

compared to control patients and these levels correlated with clinical outcome (33,34). Though

levels of c-tau were also elevated in plasma from patients with severe TBI, there was no

correlation between plasma levels and clinical outcome. A major limitation of all of these

biomarkers is the lack of specificity for defining neuropathological cascades.

Using the same proteomic Western blot technique, levels of spectrin breakdown products

(SBDP’s) have been reported in CSF from adults with severe TBI and they have shown a

significant relationship with severity of injury and clinical outcome (35-40). Following a TBI the

axonally enriched cytoskeletal protein -II-spectrin is proteolyzed by calpain and caspase-3 to

signature breakdown products (SBDPs). Calpain and caspase-3 mediated SBDP levels in CSF

have shown to be significantly increased in TBI patients at several time points after injury,

compared to control subjects. The time course of calpain mediated SBDP150 and SBDP145

(markers of necrosis) differs from that of caspase-3 mediated SBDP120 (marker of apoptosis). A

promising candidate biomarker for TBI currently under investigation is Ubiquitin Cterminal

Hydrolase-L1 (UCH-L1). UCH-L1 was previously used as a histological marker for neurons due

to its high abundance and specific expression in neurons (41). This protein is involved in the

addition and removal of ubiquitin from proteins that are destined for metabolism (42). It has an

important role in the removal of excessive, oxidized or misfolded proteins during both normal

and pathological conditions in neurons (43). In initial studies, UCH-L1 was identified as a

protein with a two-fold increase in abundance in the injured cortex 48 hours after controlled

cortical impact in a rat model of TBI (44). Subsequently, a

UCH-L1 sandwich enzyme-linked immunosorbent assay quantitatively showed that CSF and

serum UCH-L1 levels in rats were significantly elevated as early as 2 hours following both

traumatic and ischemic injury (45). Clinical studies in humans with severe TBI confirmed, using

ELISA analysis, that the UCH-L1 protein was significantly elevated in human CSF44 (46), and

was detectable very early after injury and remained significantly elevated for 168 hours post-

injury. Further studies in severe TBI patients have revealed a very good correlation between CSF

and serum levels. Most recently, UCH-L1 was detected in the serum of mild and moderate TBI

(MMTBI) patients within an hour of injury. Serum levels of UCH-L1 discriminated MMTBI

patients from uninjured and non-head injured trauma controls and were also able to distinguish

mild TBI (concussion patients) from these controls. Most notable was that levels were

significantly higher in those with intracranial lesions on CT than those without lesions. Glial

Fibrillary Acidic Protein (GFAP) is a monomeric intermediate protein found in astroglial

skeleton that was first isolated by Eng et al. in 1971. GFAP is found in white and gray brain

matter and is strongly upregulated during astrogliosis. Current evidence indicates that serum

GFAP might be a useful marker for various types of brain damage from neurodegenerative

disorders (47,48) and stroke to severe traumatic brain injury (49-53).

Clinical researchers have developed methodological standards for developing clinical decision

tools in order to ensure the validity of study results (54,55). As TBI biomarker research

transitions from the bench to the bedside there are a number of important methodological issues

that researchers will have to consider as they design their clinical protocols. Since TBI

biomarkers are being designed for clinical management, the outcome or diagnosis being

examined will need to be clearly defined and clinically important. In order to ensure external

validity and the generalizability of the results, study patients will have to be selected without bias

and represent a wide spectrum of clinical and demographic characteristics. When interpreting the

data, clinical variables that potentially affect outcome will require careful consideration in the

analysis. Biochemical markers could help with clinical decision making by elucidating injury

severity, injury mechanism(s), and monitoring progression of injury. Temporal profiles of

changes in biomarkers could guide timing of diagnosis and treatment. Biomarkers could have a

role in management decisions regarding patients at high risk of repeated injury. Accurate

identification of these patients could facilitate development of guidelines for return to duty, work

or sports activities and also provide opportunities for counseling of patients suffering from these

deficits. Repeated mild TBI occurring within a short period (i.e. hours, days, or weeks) can be

catastrophic or fatal, a phenomenon termed ‘second impact syndrome.’

Acute CT or MRI abnormalities are not usually found after these injuries, but levels of some

neurotransmitters remain elevated, and a hypermetabolic state may persist in the brain for several

days after the initial injury.

Biomarkers could serve as prognostic indicators by providing information for patients and their

families about the expected course of recovery. It opens the door to the initiation of early

therapies. Identifying at-risk patients with less apparent TBI or differentiating injury pathology in

those with more severe intracranial processes would be tremendously valuable in the

management of these patients. For example, in a patient with a normal CT scan or MRI, a

biomarker that could predict worsening neurological status or long-term disability would have

great clinical utility.

There have been a large number of clinical trials studying potential therapies for traumatic brain

injury (TBI) that have resulted in negative findings. Biomarkers measurable in blood would have

important applications in clinical research of these injuries. Biomarkers could provide clinical

trial outcome measures that are cost-effective and more readily available than conventional

neurological assessments, thereby significantly reducing the risks and costs of human clinical

trials. Biomarkers that represent highly sensitive and specific indicators of disease pathways

have been used as substitutes for outcomes in clinical trials when evidence indicates that they

predict clinical risk or benefit.

Lack of quickly accessible pathophysiologic information during the post-injury course has made

pharmacologic intervention problematic. Biomarkers could provide more timely information on

disease progression and the effects of interventions such as drugs and surgery. Biomarker

measurements could potentially relate the effects of interventions on molecular and cellular

pathways to clinical responses. In doing so, biomarkers would provide an avenue for researchers

and clinicians to gain a mechanistic understanding of the differences in clinical response that

may be influenced by uncontrolled variables.

Intoxicated, unconscious, sedated, or polytraumatized patients suspected of having a TBI pose a

particular challenge to emergency and trauma physicians. Biomarkers could expedite the

evaluation of such patients by providing information on the degree of brain injury prior to

neuroimaging. Biomarkers in this setting could also help determine the need for early

neurosurgical consultation or transfer to facilities with neurosurgical capabilities. There are

potential military applications as well. Serum biomarkers could help diagnose and/or triage brain

injured military servicemen and women. TBI is a leading cause of combat casualty with an

estimated 15-20% of all injuries sustained in 20th century conflicts being to the head (57-58).

America's armed forces are sustaining attacks by rocket-propelled grenades, improvised

explosive devices, and land mines almost daily in the recent conflicts in Iraq and

Afghanistan.145 It has been suggested that over 50% of injuries sustained in combat are the

result of such explosive munitions including bombs, grenades, land mines, missiles, and

mortar/artillery shells. Neuroimaging techniques to diagnose brain injury acutely and other

monitoring tools that assess secondary insults are not immediately available in combat zones and

such casualties have to be evacuated. Triage and management of brain injured soldiers could be

significantly improved if first responders had a quick and simple means of objectively assessing

severity of brain injury and of

monitoring secondary insults.

There is a unique opportunity to use the insight offered by biochemical markers to shed light on

the complexities of the injury process. Accordingly, certain markers could be used as indicators

of damage to a particular cell type or cellular process or may be indicative of a particular type of

injury. Neuroanatomically, that could include evidence of, say, primary axonal damage versus

glial damage. With such heterogeneity the solution may not lie with a single biomarker but more

with a complementary panel of markers that may prove useful in distinguishing different

pathoanatomic processes of injury.

III. Development of Healthbooks™

In the business model using software as a service (SaaS), users are provided access to application

software and databases. The cloud providers manage the infrastructure and platforms on which the

applications run. SaaS is sometimes referred to as “on-demand software” and is usually priced on a pay-

per-use basis. SaaS providers generally price applications using a subscription fee.

• Proponents claim that the SaaS allows a business the potential to reduce IT operational

costs by outsourcing hardware and software maintenance and support to the cloud

provider. This enables the business to reallocate IT operations costs away from

hardware/software spending and personnel expenses, towards meeting other IT goals. In

addition, with applications hosted centrally, updates can be released without the need for

users to install new software. One drawback of SaaS is that the users' data are stored on

the cloud provider’s server. As a result, there could be unauthorized access to the data.

End users access cloud-based applications through a web browser or a light-weight

desktop or

mobile app while the business software and user's data are stored on servers at a remote location.

Proponents claim that cloud computing allows enterprises to get their applications up and running

faster, with improved manageability and less maintenance, and enables IT to more rapidly adjust

resources to meet fluctuating and unpredictable business demand.

In the most basic cloud-service model, providers of IaaS offer computers - physical or (more often)

virtual machines - and other resources. (A hypervisor, such as Xen or KVM, runs the virtual machines as

guests. Pools of hypervisors within the cloud operational support-system can support large numbers of

virtual machines and the ability to scale services up and down according to customers' varying

requirements.) IaaS clouds often offer additional resources such as images in a virtual-machine image-

library, raw (block) and file-based storage, firewalls, load balancers, IP addresses, virtual local area

networks (VLANs), and software bundles. IaaS-cloud providers supply these resources on-demand from

their large pools installed in data centers. For wide-area connectivity, customers can use either the

Internet or carrier clouds (dedicated virtual private networks).

Cloud computing relies on sharing of resources to achieve coherence and economies of scale similar to a

utility (like the electricity grid) over a network. At the foundation of cloud computing is the broader

concept of converged infrastructure and shared services.

The underlying concept of cloud computing dates back to the 1950s, when large-scale mainframe

became available in academia and corporations, accessible via thin clients / terminal computers. To make

more efficient use of costly mainframes, a practice evolved that allowed multiple users to share both the

physical access to the computer from multiple terminals as well as to share the CPU time. This

eliminated periods of inactivity on the mainframe and allowed for a greater return on the investment.

The practice of sharing CPU time on a mainframe became known in the industry as time-sharing.

In the 1990s, telecommunications companies, who previously offered primarily dedicated point-to-point

data circuits, began offering virtual private network (VPN) services with comparable quality of service

but at a much lower cost. By switching traffic to balance utilization as they saw fit, they were able to

utilize their overall network bandwidth more effectively. The cloud symbol was used to denote the

demarcation point between that which was the responsibility of the provider and that which was the

responsibility of the users. Cloud computing extends this boundary to cover servers as well as the

network infrastructure. As computers became more prevalent, scientists and technologists explored

ways to make large-scale computing power available to more users through time sharing, experimenting

with algorithms to provide the optimal use of the infrastructure, platform and applications with

prioritized access to the CPU and efficiency for the end users.

Gathering data is a fairly easy task, understanding it is the problem. Big data presents a

challenge in that the value of information (VOI) becomes a key consideration- allowing the

meaning of medical data to the patient will be considered a HIPAA violation in the furue. Today

we rely heavily on digital data streams to analyze everything from the timing microwave ovens

to listening to music from an iPhone. One characteristic of digital data is that is very mundane –

it is very much like Morse code. At least in Morse code there was a long sound and a short

sound. maybe even some rhythm Some very adept in Morse code could understand the various

clicks as a language. Digital data would not be very practical without a computer. - imagine

reading this document in Morse code! Fortunately, modern fast computers exist to eliminate that

boredom..

Let's look at our objective: Provide a improved quality of life through a few simple, unobtrusive

devices that provide a constant stream of digital data concerns our current health status. One,

unusual, benefit of constant health monitoring is now we will now what is right. If you are

flying North and you have a cross wind to the West it is obvious – to correct - one needs to fly a

little bit East. The key is a constant data stream that is routinely interpreted for all aspects of

health – those that are bad, those that are good and all those in between. Collected data is then

normalized for each individual that can be compared to the general populace instead of the other

way around. Once a data stream is collected it can then be easily transformed to be easily

understood much like this document had be transformed from Morse code. HIPAA compliance

requires that the architecture of the system be designed for failure- not just the interruption of the

data-architecture but the loss of connections that are essential to preserve the meaning of the

data.

Failure to decouple the links between the applications and the sources of data, especially when

they are likely to be so numerous, would be catastrophic. Applications must not be designed to

expect data, especially transient data, but the application and the device must be expected to

intercommunicate—but to execute completely independent of each other. A last example to

consider is the accelerating pace of business itself. Back-office systems have been designed and

built for years to run with extremely high performance and throughput. These back-office

systems have been measured by transactions per second, and response times to the submission of

an individual piece of work. As teams move to accessing and even running these solutions

outside the enterprise, they continue to expect the reliability and the speed of response seen

within the enter-prise domain. To try to achieve this will require substantial evaluation of how to

implement this connectivity to try to balance these requests. When it comes to responding to

requests, delays of even a second or more may lead to users to believe that there is be a problem,

and a negative perception can lead to rapid dissatisfaction with the solution.

The growth of cloud computing has created a change in this picture. Cloud is not a single thing, but

in fact can be used to describe the more-dynamic allocation and use of in-house IT resources, or

cloud can mean the use as needed of publically available IT resources on a usage-based model.

Or cloud could be any combination of these—and even other—deployment types. Business

leaders are likely to be considering which of their IT systems, and which of their applications,

are suitable for deployment in the cloud—whatever cloud might mean to them. Perhaps this

might be for cost-saving reasons, or it might be for more flexible deployment in response to a

growth in usage, or it might simply be the fastest way to get something done. Whatever the

reason, applications will need to become ever more agnostic about their runtime environment,

and the connections they have to the rest of the enterprise. They will need to be loosely

connected, but reliably and securely connected, enabling business teams to make decisions on

deployment completely independent of the application architecture itself.

Applications and the business IT infrastructure itself needs to be robust enough, and must

perform fast enough, to consume and take action on all the data and all the events, in a timely

manner. Other data can be held and processed to extract the remaining value. Indeed, the

applications and infrastructure must be both high-performing and “smart.” Applications and

infrastructure must not only be able to recognize the data that was previously important, but must

change to be able to identify and act upon some of the rest of the Big Data, creating the new

business opportunities that Big Data represents, even while Big Data creates new challenges to

the IT infrastructure—the systems, the applications and the connections between them.

One final way to move data between applications is to use a dedicated middleware layer for enterprise

messaging. This is a similar approach to the embedded JMS messaging mentioned above, but avoids the

limitations of being Java only, and of only connecting to other instances running in the same application

server environment. The enterprise messaging approach also avoids some of the limitations of HTTP,

since you are able to use more loosely coupled requests, including both time- independence and

transactional integrity. And although it is different from a file transfer solution, enterprise messaging can

be used to enhance, replace or update an existing or a new file transfer-based approach without

application disruption. As discussed above, many business leaders use applications coded in Java,

running in an application server. Part of the Java standard is JMS—providing a messaging service as a

part of the programming model. Using JMS is therefore a natural way for such applications to move data

into an application and out of an application, and many application servers include a JMS provider to

“listen” for JMS requests and execute them. However, this will only work if both the sending application

and the receiving application are running a common JMS provider. Although JMS is a standard API, the

wire format is not standard, so different JMS providers cannot exchange messages

IV. Our corporate advantages for the researcher include:

• Alignment of Integrative Health with disciplines that focus on human stress/resilience

makes alignment with that community a high priority biosignal analysis for those

involved in the development of these new technologies

• Submission of grants through TCO (Technology Commercialization Office) avoids high

administrative charges for grants submitted through OSP (Office of Sponsored Projects)

by various University Departments

• Innoception will aggressively approach funding sources that are not available to most

Academic or Medical projects

• Innoception creates a protected place for those involved in development and fielding of

measurement technologies to fully mature their intellectual property, whether device, or

curriculum focused, provides an accelerated path to market

• Ongoing work in biosignal technology development has overlooked the complex adaptive

system. We offer unique technological resources to enable the investigation of this

potentially fruitful area of enquiry

• Principles associated with Innoception have an established track record of years of

involvement in the Integrative and Academic community with stable networks in

Business and Allied Technologies

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Addendum: Common correlation with physiological symptoms and disease states.

Pain Fatigue Mood Digest SleepUnderhydration P P P PFood sensitivities P P P P PJoint subluxations P P Radiculopathies P P Myelopathy P P P P PViscerosomatic reflex P Infectious malaise P P P Arthritides P

Low bone densitiy P P Hypovitaminosis D P P P PCalcium deficiency P P P PIron deficiency P PMagnesium deficiency P P PTyrosine deficiciency P P P PFatty acid deficiency P PZinc deficiency P Hypoadrenia P P P PHyperadrenia P P P PAAT deficiency P P Poor posture P P Parasite infection P P P PNon-restorative sleep P P P Metal toxicity P P Candidiasis P P P Dysbiosis P Dysglycemia P P PHyponatremia P P Anemia P Hypothyroid P P P PFunctional acidosis P P Foreign energies P Zeta virus P Pancreatic insufficiency P H. pylori infection P Hypochlorhydria P Prolapsed colon P Hiatal hernia P Rib torque P Medication side-effects P P PRetless legs PMeridian dysfunction PLight & sound dysruption PPoor stress management P P P P P