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Commit 732d0ec2 authored by Avinash Baskaran's avatar Avinash Baskaran
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adding work from Tuesday

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......@@ -1404,6 +1404,8 @@ function compute_current_TRIP(TRIP_min,TRIP_max, samples)
}
}
// net Pressure-Volume Work:
// integral under P*V curve
function PressureVolumeWork(samples, a,z) {
......@@ -1416,8 +1418,7 @@ function compute_current_TRIP(TRIP_min,TRIP_max, samples)
// I'll use qadrilateral approximation.
// We'll form each quadrilateral between two samples.
var ms = flows[j+1].ms - flows[j].ms;
var netWorkDone = ((flows[j+1].val*pressures[j+1].val) - (flows[j].val*pressures[j+1].val ))/2) * CONVERT_PIRDS_TO_SLM;
var TotalWorkDone =
var ht = (((flows[j+1].val*pressures[j+1].val) + (flows[j].val*pressures[j+1].val ))/2) * CONVERT_PIRDS_TO_SLM;
// Flow in standard liters per minute,
// divide by 60000 to get liters/s
pressureVolume_prod += ms * ht/60000;
......@@ -1429,50 +1430,23 @@ function compute_current_TRIP(TRIP_min,TRIP_max, samples)
return pressureVolume_prod/1033
}
function testWork(samples){ // breaths give us inspiration transition points
var flows = samples.filter(s => s.event == 'M' && s.type == 'F');
var first_time = flows[0].ms;
var last_time = flows[flows.length - 1].ms;
var duration = last_time - first_time;
console.log(flows);
const vm = 10;
var transitions = compute_transitions(vm,flows);
var breaths = compute_breaths_based_without_negative_flow(transitions,flows);
console.log(breaths);
}
// A simple computation of a moving window trace
// computing [A + -B], where A is volume to left
// of sample int time window t, and B is volume to right
// t is in milliseconds
function computeMovingWindowTrace(samples,t,v) {
var flows = samples.filter(s => s.event == 'M' && s.type == 'F');
var first_time = flows[0].ms;
var last_time = flows[flows.length - 1].ms;
var duration = last_time - first_time;
// Here is an idea...
// We define you to be in one of three states:
// Inspiring, expiring, or neither.
// Every transition between these states is logged.
// Having two inspirations between an expiration is
// weird but could happen.
// We record transitions.
// When the time series crossed a fixed threshold
// or zero, it causes a transition. If you are inspiring,
// you have to cross zero to transition to neither,
// and you start expiring when you cross the treshold.
// This is measured in standard liters per minute.
const vm = 10; // previously used 4
// We will model this as a list of transitions.
// A breath is any number of inspirations followed by
// any number of expirations. (I+)(E+)
var transitions = compute_transitions(vm,flows);
// Now that we have transitions, we can apply a
// diferrent algorithm to try to define "breaths".
// Because a breath is defined as an inspiration
// and then an expiration, we will define a breath
// as from the first inspiration, until there has
// been one expiration, until the next inspiration.
var breaths = [];
var expiring = false;
// This should be in liters...
function integrateSamples(a,z) {
function integrateSamples(a,z,flows) {
// -1 for quadilateral approximation
var vol = 0;
for(var j = a; j < z-1; j++) {
......@@ -1493,16 +1467,34 @@ function computeMovingWindowTrace(samples,t,v) {
return vol/(60*1000);
}
function compute_breaths_based_on_exhalations(transitions) {
// This is based only on inhalations, and
// is therefore functional when there is a check valve
// in place. Such a system will rarely
// have negative flows, and we must mark
// the beginning of a breath from a transition to a "1"
// state from any other state.
// This algorithm is simple: A breath begins on a trasition
// to 1 from a not 1 state. This algorithm is susceptible
// to "stutter" near the boundary point, but if necessary
// a digital filter would sove that; we have not yet found
// that level of sophistication needed.
// We still want to track zeros, but now must strack them
// as a falling signal.
function compute_breaths_based_without_negative_flow(transitions,flows) {
var beg = 0;
var zero = 0;
var last = 0;
var voli = 0;
var vole = 0;
var breaths = [];
var expiring = true;
for(var i = 0; i < transitions.length; i++) {
// We're looking for the end of the inhalation here!!
if (((i -1) >= 0) && transitions[i-1].state == 1 && (transitions[i].state == 0 || transitions[i].state == -1 )) {
if (((i -1) >= 0) && transitions[i-1].state == 1 &&
(transitions[i].state == 0 || transitions[i].state == -1 )) {
zero = i;
}
if (expiring && transitions[i].state == 1) {
......@@ -1517,43 +1509,70 @@ function computeMovingWindowTrace(samples,t,v) {
);
beg = i;
expiring = false;
vole = integrateSamples(last,transitions[i].sample);
vole = integrateSamples(last,transitions[i].sample,flows);
last = transitions[i].sample;
}
if (!expiring && transitions[i].state == -1) {
if (!expiring && ((transitions[i].state == -1) || (transitions[i].state == 0))) {
expiring = true;
voli = integrateSamples(last,transitions[i].sample);
voli = integrateSamples(last,transitions[i].sample,flows);
last = transitions[i].sample;
}
}
return breaths;
}
// This is based only on inhalations, and
// is therefore functional when there is a check valve
// in place. Such a system will rarely
// have negative flows, and we must mark
// the beginning of a breath from a transition to a "1"
// state from any other state.
// This algorithm is simple: A breath begins on a trasition
// to 1 from a not 1 state. This algorithm is susceptible
// to "stutter" near the boundary point, but if necessary
// a digital filter would sove that; we have not yet found
// that level of sophistication needed.
// We still want to track zeros, but now must strack them
// as a falling signal.
function compute_breaths_based_without_negative_flow(transitions) {
// A simple computation of a moving window trace
// computing [A + -B], where A is volume to left
// of sample int time window t, and B is volume to right
// t is in milliseconds
function computeMovingWindowTrace(samples,t,v) {
var flows = samples.filter(s => s.event == 'M' && s.type == 'F');
var first_time = flows[0].ms;
var last_time = flows[flows.length - 1].ms;
var duration = last_time - first_time;
// Here is an idea...
// We define you to be in one of three states:
// Inspiring, expiring, or neither.
// Every transition between these states is logged.
// Having two inspirations between an expiration is
// weird but could happen.
// We record transitions.
// When the time series crossed a fixed threshold
// or zero, it causes a transition. If you are inspiring,
// you have to cross zero to transition to neither,
// and you start expiring when you cross the treshold.
// This is measured in standard liters per minute.
const vm = 10; // previously used 4
// We will model this as a list of transitions.
// A breath is any number of inspirations followed by
// any number of expirations. (I+)(E+)
var transitions = compute_transitions(vm,flows);
// Now that we have transitions, we can apply a
// diferrent algorithm to try to define "breaths".
// Because a breath is defined as an inspiration
// and then an expiration, we will define a breath
// as from the first inspiration, until there has
// been one expiration, until the next inspiration.
var breaths = [];
var expiring = false;
function compute_breaths_based_on_exhalations(transitions) {
var beg = 0;
var zero = 0;
var last = 0;
var voli = 0;
var vole = 0;
var breaths = [];
var expiring = true;
for(var i = 0; i < transitions.length; i++) {
// We're looking for the end of the inhalation here!!
if (((i -1) >= 0) && transitions[i-1].state == 1 &&
(transitions[i].state == 0 || transitions[i].state == -1 )) {
if (((i -1) >= 0) && transitions[i-1].state == 1 && (transitions[i].state == 0 || transitions[i].state == -1 )) {
zero = i;
}
if (expiring && transitions[i].state == 1) {
......@@ -1568,20 +1587,18 @@ function computeMovingWindowTrace(samples,t,v) {
);
beg = i;
expiring = false;
vole = integrateSamples(last,transitions[i].sample);
vole = integrateSamples(last,transitions[i].sample,flows);
last = transitions[i].sample;
}
if (!expiring && ((transitions[i].state == -1) || (transitions[i].state == 0))) {
if (!expiring && transitions[i].state == -1) {
expiring = true;
voli = integrateSamples(last,transitions[i].sample);
voli = integrateSamples(last,transitions[i].sample,flows);
last = transitions[i].sample;
}
}
return breaths;
}
breaths = compute_breaths_based_without_negative_flow(transitions);
breaths = compute_breaths_based_without_negative_flow(transitions,flows);
return [transitions,breaths];
}
......
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