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Add requirements overview. Reduce glossary to a single file. Stub des…
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…ign goals. Stub qa goals.
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3 changes: 0 additions & 3 deletions docs/architecture/index.md
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---
title: Architecture
---

![Under Construction][def]

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---
title: Privacy & security
---

## Core Concepts

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![Under Construction](../images/underconstruction.svg)

**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.

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.

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.

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.

!!! 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.

| 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&nbsp;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 |

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]

The cosinor analysis produces a **Sphygmochron^&trade;^** &mdash; 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.

[^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" }.

[^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" }.

[^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" }.
6 changes: 6 additions & 0 deletions docs/requirements/cusum.md
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![Coming Soon](../images/coming-soon-construction.png)

**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.

[^cusum]: Wikipedia. "CUSUM". Website, accessed 14 March 2024. [https://en.wikipedia.org/wiki/CUSUM](https://en.wikipedia.org/wiki/CUSUM){: target="_blank" }.
73 changes: 73 additions & 0 deletions docs/requirements/design-goals.md
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![Under Construction](../images/underconstruction.svg)

<span id="dg_correctness">Correctness</span>
: This design correctly matches the given requirements.

<span id="dg_feasibility">Feasibility</span>
: This design can be implemented and tested with the planned amount of time and effort.

<span id="dg_understandability">Understandability</span>
: Developers can understand this design and correctly implement it.

<span id="dg_guidance">Implementation phase guidance</span>
: This design divides the implementation into components or aspects that can correspond to reasonable implementation tasks.

<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.

<span id="dg_extensibility">Extensibility</span>
: New [features](#feature) or components can be easily added later.

<span id="dg_testability">Testability</span>
: It is easy to test components of this design independently, and information is available to help diagnose defects.

<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.

<span id="dg_easy_integration">Ease of integration</span>
: The components will work together.

<span id="dg_cap_match">Capacity matching</span>
: The architecture deploys components onto machines that provide needed resources with reasonable total expense.

<span id="dg_expressiveness">Expressiveness</span>
: It allows for storage of all valid values and relationships

<span id="dg_easy_access">Ease of access</span>
: Application code to access stored data is simple

<span id="dg_data_reliability">Reliability</span>
: Stored data cannot easily be corrupted by defective code, concurrent access, or unexpected process termination

<span id="dg_data_capacity">Data capacity</span>
: The system can store the amount of data needed.

<span id="dg_data_security">Data security</span>
: Protection of sensitive user and corporate data from unauthorized access or modification

<span id="dg_data_performance">Performance</span>
: Data can be accessed quickly

<span id="dg_data_interop">Interoperability</span>
: The database or data files can be accessed and updated by other applications

<span id="dg_no_intrusion">Intrusion prevention</span>
: Prevent, e.g., hackers opening a command shell on our server.

<span id="dg_no_abuse">Abuse prevention</span>
: Prevention of abuse (e.g., using our system to send spam).

<span id="dg_auditability">Auditability</span>
: All changes can be accounted for later.

<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.

<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.

<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).

<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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57 changes: 49 additions & 8 deletions docs/requirements/index.md
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---
title: Requirements
---
![Under Construction](../images/underconstruction.svg)

## Overview

**{{ config.site_name }}** underpin an emerging healthcare program that uses [chronobiologic](../glossary#chronobiology) techniques to prevent [strokes](../glossary#stroke) and other effects of cardiac disease.

The system uses blood pressure measurements taken approximately every 30 minutes, day and night, in ambulatory fashion. Ideally, seven days of data are available. This data is analyzed with **[cosinor:material-link:](cosinor.md)** and **[cumulative-sum:material-link:](cusum.md)** algorithms.

The results of an analysis is available directly to the patient, and when appropriate, to the patient’s healthcare provider. Analysis solutions are automated and easy to use.

The associated databases contain physiological data about large numbers of individuals over time, as well as physiological and psychological data on populations. The databases are available to chronophysiologists who create the reference sets needed by the analysis techniques, as well as to chronobiology researchers.

The solution is global in scope. Its capability is widely distributed and fronted by multi-linguage websites.

The solution employs a zero-trust security model, with defense in depth.

The solution treats privacy as paramount, giving the patient control over who has access to the patient's data.

The public-facing websites contain:

* The analysis tools
* Libraries of reference materials for different audiences (physician, general public, student)
* Lists of commercially-available ambulatory blood pressure monitors

!!! question "Proposal for and Concern About Social Networks"
The solution previously envisioned connections to popular social networking websites as means to motivate members of the general public to use the system and disseminate information that they find to be trustworthy and popular. The social networking mechanisms would be designed to allow the general public to collaborate and discover individualized treatments that are more effective than those that have passed one-size-fits-all style clinical trials, and would allow comparative analyses of individual and population based physiological and psychological data, starting with but not limited to their own blood pressure.

Links to social networks are problematic because they would open vulnerabilities to privacy and security.

## Context

!!! bug
The diagrams in this article are out-of-date but included as placeholders to organize the article.
The diagrams in this article are out-of-date but are included as placeholders to organize the article.

![Context Diagram](../images/context-diagram.png)

Inputs: blood pressure measurements taken approximately every 30 minutes, day and night, in ambulatory fashion.


## Actors

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| physician | a clinician<br><br>makes clinical decisions<br><br>diagnoses patient |
| nurse | a clinician<br><br>Deals directly with device<br><br>Manages interaction between device and patient<br><br>Responsible for data transfer<br><br>Creates report for physician<br><br>Creates report for patient |

## Context

![Context Diagram](../images/context-diagram.png)

## Use cases


The mechanism for detecting high risk of stroke and guiding treatment requires “continuous” blood pressure measurements; blood pressure measurements taken approximately every 30 minutes, day and night, in ambulatory fashion, are analyzed via cosinor and cumulative sum.

The analysis can be automated on, and dispensed from, a worldwide multi-lingual website. The results of the analysis are to be made available to the patient directly, and when appropriate, to the patient’s healthcare provider. The associated databases are useful to chronobiology researchers, as they contain physiological data on large numbers of individuals over time as well as physiological and psychological data on populations.

The chronobiological analyses to be used in the first version of the website are Sphygmochron™ reports (circadian rhythm analysis based on cosinor mathematics) and CUSUM reports (based on cumulative sum mathematics derived from the manufacturing “quality control” arena). The Sphygmochron detects six Vascular Variability Disorders (VVDs, persistent incorrect circadian rhythm characteristics in blood pressure or heart rate) that act as indicators of risk of stroke. VVDs are mathematically defined as anomalies in the circadian phase, amplitude, and MESOR (a time-adjusted average) of BP and HR time series, when compared to healthy peers of the same gender and age group. One VVD is a more precise definition of hypertension than that defined by the WHO, and others VVDs represent independent, additive indicators of stroke risk; an individual with MESOR hypertension, circadian hyper-amplitude tension, excessive pulse pressure, and deficient heart rate variability has a nearly 100% risk of stroke within six years.

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.

The website will provide the reports and data access mechanisms that meet appropriate security and privacy constraints. Standard search and relational-database query capability will be provided. The public-facing website will contain the analysis tools, libraries of reference materials for different audiences (physician, general public, student), lists of commercially-available cABPMs, and connections to popular social networking websites to motivate members of the general public to use the system and disseminate information that they find to be trustworthy and popular. The social networking mechanisms are designed to allow the general public to collaborate and discover individualized treatments that are more effective than those that have passed one-size-fits-all style clinical trials, and will allow comparative analyses of individual and population based physiological and psychological data, starting with but not limited to their own blood pressure.

## Required attributes

!!! bug
Reconcile the following with [Design goals:material-link:](design-goals.md) and [Quality goals:material-link:](quality-goals.md).

Inexpensive
: Free and open source software [^foss]

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1. System operators are custodians
1. Control belongs to the user


[^foss]: Wikipedia. "Free and open-source software". Website, accessed 8 March 2024. [https://en.wikipedia.org/wiki/Free_and_open-source_software](https://en.wikipedia.org/wiki/Free_and_open-source_software){: target="_blank" }.

[^threat]: Wikipedia. "Threat model". Website, accessed 8 March 2024. [https://en.wikipedia.org/wiki/Threat_model](https://en.wikipedia.org/wiki/Threat_model){: target="_blank" }.
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