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title: Architecture | ||
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title: Privacy & security | ||
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## Core Concepts | ||
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![Under Construction](../images/underconstruction.svg) | ||
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**Cosinor analysis** uses the [least squares method](../../glossary#least-squares) to fit a sine wave to a time series. Cosinor analysis is often used in the analysis of biologic time series that demonstrate predictible rhythms. This method can be used with an unequally spaced time series. | ||
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The Phoenix Biorhythms Platform applies cosinor analysis to a patient's blood pressure and heart rate measurements taken over a defined period, such as 1 day, 2 days, or 7 days. The analysis compares the blood pressure and heart rate profile to healthy peers of the same gender and age group. | ||
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The first objective of cosinor analysis is to measure the [MESOR](../../glossary#mesor) of the patient's blood pressure and to detect [MESOR-hypertension](../../glossary#mesor-hypertension). MESOR is a circadian rhythm-adjusted mean. MESOR-hypertension is an elevation of the blood pressure MESOR as validated statistically against the person's own MESOR at another time and/or against a peer reference standard. | ||
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The second objective of cosinor analysis is to detect [vascular variability anomalies (VVAs)](../../glossary#vascular-variability-anomaly), which are mathematically defined anomalies in the [circadian](../../glossary#circadian) phase, [amplitude](../../glossary#amplitude) and MESOR, of blood pressure and heart rate. | ||
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!!! bug | ||
Simplify the definitions of _CHAT_, _ecphasia_, and _ecfrequentia_, which come across as wordy jargon. Lean on physiology concepts rather than statistics. Use a follow-on section for each VVA to get into statistical details. | ||
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| VVA | Definition | | ||
| --- | ---------- | | ||
| Circadian hyper-amplitude-tension (CHAT) | :material-bug:{: style="color: red;" } An elevation of the 24-hour amplitude of blood pressure above the upper 95% prediction limit of clinically healthy peers matched by gender and age | | ||
| Ecphasia | :material-bug:{: style="color: red;" } Odd circadian blood pressure timing. A deviation of the 24-hour acrophase above the 90% prediction limits of clinically healthy peers matched by gender and age | | ||
| Ecfrequentia<br>(frequency desynchronization) | :material-bug:{: style="color: red;" } Altered period of the circadian rhythm, by cosine fitting. A statistically significant deviation of the period from 24 hours, assessed by the nonoverlap of 24 hours by the 95% [confidence interval](../../glossary#confidence-interval) of the period assessed by nonlinear least squares | | ||
| Excessive pulse pressure | The problem of too large a difference between [diastolic](../../glossary#diastolic-blood-pressure) and [systolic blood pressure](../../glossary#systolic-blood-pressure) (between when the heart contracts and relaxes, respectively) | | ||
| Excessive pulse pressure product | The combined effect of [heart rate](../../glossary#heart-rate) and [pulse pressure](../../glossary#pulse-pressure), as either or both increase | | ||
| Deficient heart rate variability (DHRV) | The problem of heart rate that does not vary enough, as indicated by the [standard deviation](../../glossary#standard-deviation) and when measured over a seven-day period | | ||
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MESOR-hypertension indicates a risk of stroke. The VVAs represent independent, additive risks of adverse cardiovascular events. Together, a patient with four of the conditions has a nearly 100% risk of stroke within six years. [^physiology] | ||
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The cosinor analysis produces a **Sphygmochron^™^** — a report that provides an inferential statistical basis for diagnosising blood pressure disorders, by comparing the subject's blood pressure and heart rate profile with that of a clinically healthy peers. | ||
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[^cdc]: Centers for Disease Control and Prevention. "High Blood Pressure Symptoms and Causes". Website, reviewed 18 May 2021. [https://www.cdc.gov/bloodpressure/about.htm](https://www.cdc.gov/bloodpressure/about.htm){: target="_blank" }. | ||
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[^rhythmometry]: Cornelissen, Germaine. “Cosinor-based rhythmometry.” _Theoretical biology & medical modelling_ vol. 11 16. 11 Apr. 2014, doi:10.1186/1742-4682-11-16. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3991883/pdf/1742-4682-11-16.pdf](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3991883/pdf/1742-4682-11-16.pdf){: target="_blank" }. | ||
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[^physiology]: Franz Halberg, Deborah Powell, Kuniaki Otsuka, Yoshihiko Watanabe, Larry A. Beaty, Paul Rosch, Jerzy Czaplicki, Dewayne Hillman, Othild Schwartzkopff, and Germaine Cornelissen. "Diagnosing vascular variability anomalies, not only MESOR-hypertension". _American Journal of Physiology-Heart and Circulatory Physiology_ 2013 305:3, H279-H294. [https://journals.physiology.org/doi/full/10.1152/ajpheart.00212.2013](https://journals.physiology.org/doi/full/10.1152/ajpheart.00212.2013){: target="_blank" }. |
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![Coming Soon](../images/coming-soon-construction.png) | ||
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**Cumulative sum (CUSUM) analysis** is a statistical method, borrowed from the discipline of manufacturing quality control[^cusum], for detecting a signal that has drifted beyond a target mean and standard deviation. CUSUM can be used to detect unstable motion or small changes in mean, such as linear trends. | ||
The CUSUM detects the time at which changes in a metric such as SBP MESOR became statistically significant. The Halberg Chronobiology Center developed a “self-starting CUSUM” that eliminates the need to specify a “target value” to be met. | ||
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[^cusum]: Wikipedia. "CUSUM". Website, accessed 14 March 2024. [https://en.wikipedia.org/wiki/CUSUM](https://en.wikipedia.org/wiki/CUSUM){: target="_blank" }. |
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![Under Construction](../images/underconstruction.svg) | ||
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<span id="dg_correctness">Correctness</span> | ||
: This design correctly matches the given requirements. | ||
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<span id="dg_feasibility">Feasibility</span> | ||
: This design can be implemented and tested with the planned amount of time and effort. | ||
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<span id="dg_understandability">Understandability</span> | ||
: Developers can understand this design and correctly implement it. | ||
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<span id="dg_guidance">Implementation phase guidance</span> | ||
: This design divides the implementation into components or aspects that can correspond to reasonable implementation tasks. | ||
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<span id="dg_modularity">Modularity</span> | ||
: Concerns are clearly separated so that the impact of most design changes would be limited to only one or a few modules. | ||
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<span id="dg_extensibility">Extensibility</span> | ||
: New [features](#feature) or components can be easily added later. | ||
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<span id="dg_testability">Testability</span> | ||
: It is easy to test components of this design independently, and information is available to help diagnose defects. | ||
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<span id="dg_efficency">Efficiency</span> | ||
: The design enables the system to perform functions with an acceptable amount of time, storage space, bandwidth, and other resources. | ||
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<span id="dg_easy_integration">Ease of integration</span> | ||
: The components will work together. | ||
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<span id="dg_cap_match">Capacity matching</span> | ||
: The architecture deploys components onto machines that provide needed resources with reasonable total expense. | ||
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<span id="dg_expressiveness">Expressiveness</span> | ||
: It allows for storage of all valid values and relationships | ||
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<span id="dg_easy_access">Ease of access</span> | ||
: Application code to access stored data is simple | ||
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<span id="dg_data_reliability">Reliability</span> | ||
: Stored data cannot easily be corrupted by defective code, concurrent access, or unexpected process termination | ||
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<span id="dg_data_capacity">Data capacity</span> | ||
: The system can store the amount of data needed. | ||
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<span id="dg_data_security">Data security</span> | ||
: Protection of sensitive user and corporate data from unauthorized access or modification | ||
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<span id="dg_data_performance">Performance</span> | ||
: Data can be accessed quickly | ||
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<span id="dg_data_interop">Interoperability</span> | ||
: The database or data files can be accessed and updated by other applications | ||
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<span id="dg_no_intrusion">Intrusion prevention</span> | ||
: Prevent, e.g., hackers opening a command shell on our server. | ||
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<span id="dg_no_abuse">Abuse prevention</span> | ||
: Prevention of abuse (e.g., using our system to send spam). | ||
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<span id="dg_auditability">Auditability</span> | ||
: All changes can be accounted for later. | ||
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<span id="dg_use_understand">Understandability and learnability</span> | ||
: Users can reasonably be expected to understand the UI at first sight. Users will be able to discover additional [features](#feature)without aid from other users or documentation, and they will be able to recall what they have learned. | ||
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<span id="dg_use_efficiency">Task support and efficiency</span> | ||
: The UI is well matched to the users' tasks and it can be used with a reasonable number of clicks and keystrokes. | ||
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<span id="dg_use_safety">Safety</span> | ||
: Users are not likely to accidentally produce an undesired result (e.g., delete data, or send a half-finished email). | ||
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<span id="dg_use_consistency">Consistency and familiarity</span> | ||
: Users can apply their knowledge of similar UIs or UI standards to this system. |
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