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Symptomatic LLC. Executive Summary
Symptomatic LLC is an early stage company that is developing an interactive mental
health App for the internet of things. This App focuses on Bipolar Disease, but could be applied
to other mental health diseases including Depression and even healthy minded users (without a
mental disease). This App augments the role of patient, thus creating tools to analyze their
conditions and practice self-reliance to prevent episode’s from becoming irreversible. This
platform approach will allow us to monitor a patient’s wellbeing within a “smart environment”
and recommends therapies to help the patient maintain balance and wellbeing.
The goal is to create a smart environment using a smart phone, smart watch/fitness
tracker, smart house. This will be used throughout the patient’s routine (using a personal coach
via App). This platform is needed as a mechanism that implements pattern recognition, machine
learning, artificial intelligence throughout their routine. This provides countless insights to the
patient and even a personalized marketing scheme based on the patient’s personalized data
incorporated into the “internet of things” or IOT via pattern recognition and Machine learning.
Countless patterns via pattern recognition, will provide similar measures that pertain to previous
data sets. Thus the patient is accurately identified as a specific pattern(s)… which include
Symptoms, physiology, smart phone sensor behavior, behavior recognition, smart house,
medication regimen, therapy, consumer behavior.
The goal of all of this is to passively and accurately detect repeat patterns. With no effort
provided by the patient/user, the pattern recognition runs by itself and throughout the day
captures re-occur data point that reveal previous conditions correlating to a pervious pattern,
throughout a day, or several repeat patterns throughout a week or even months. The pattern
recognition consists of 250+ variables throughout the day… multiple times a day, throughout
many episodes/years. Thus the personalized patterns will reveal numerous data and that can be
used for analysis, episode prevention, IOT personalized marketing and 40+ measurements I’ve
made for pattern recognition alone, that will iteratively factor back into pattern recognition.
Many of these measurements are highly relevant and new to clinical psychiatry. Every patient
experiences Bipolar in their own unique way. Everyone has different combinations and severity
of symptoms, physiology, behavior, routine, emotions, all of which are personalized to their
disease. Therefore pattern recognition is able to unique gather data on specific patient’s
throughout their cycle and measure their disease in a personalized manner. Thus, revealing the
patient’s “mental health”. One business model works to create a platform of “internet of things”
for data that is given to advertisers, in order to personalize advertisers to the patients. These
advertisement’s will be targeted towards healthy living, which in result will promote mental
health.
The product is at Phase one - stage 1 stage of development cycle, which is appropriate for
the technology, because this sensor technology and the “Internet of Things” is just beginning to
be used in improving healthcare. We will introduce the platform in separate phases starting with
this Phase One, is 100+ pattern recognition (including the smart phone, smart watch, smart
house). As sensor technology advances, we will implement Phase Two by adding a smart house
and Phase three will include a field study with bipolar patient’s. My teammate has a 5,000
patient practice and we will be using his patient’s for the field study or clinical trial.
The intellectual merit is evident in that psychiatry has long held interest in physiology as
a marker of diagnosis or as an aid to diagnosis of certain mental health diseases including
bipolar. We hypothesize that we have selected key physiological signals including Autonomic
Nervous system dysfunction (HRV), Sleep patterns, and chronic physiological stress (Galvanic
Skin Response), Activity, Social Behavior, self-administered rating scale (of the given disease)
that can be used synergistically as an aid in the diagnosis and treatment of this disease. The
potential for the proposed activity to advance knowledge and understanding within its own field
is evident because it will provide an ongoing database of valuable clinical data that can be used
to further refine the process and diagnosis of mental health diseases. The broader impact is that if
my invention is successful as an early warning tool for bipolar patients the same technology can
then be applied to other mental health conditions including Depression. and people without
mental diseases, who are still concerned about mental health and healthy living. Simply by
modifying the variables most mental health diseases are applicable to the method.
Our team:
Grant Sier-Founder
Michael Kent, PhD-Chief Scientist
Dr. Charles Denby-West Bay Psychiatrics -Chief Psychiatrist
John Ring-Programming
Cory Fonger-Programming
Dr. Pamalea Shervanick-Psychiatrist
Dr. Ken Korr-Chief Cardiologist
Patrick Sier-CFO
Technical Advisors
Dr. Joseph Seradowski, PhD, PE, MBA-owner Autosoft Systems
Dr. Gary Robinson, PhD-CEO-PhaseDesign Research
Diane Cook-PhD-Director CASAS Smart Home Project -Center for Advanced Studies in Adaptive
Systems-Washington State University