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Breath Plot: COVID-19 Respiration Analysis Software
Copyright (C) 2020 Robert L. Read
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<title>Public Invention Respiration Analysis</title>
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<body>
<div class="container-fluid">
<div class="jumbotron">
<h1 class="display-4">VentMon Respiration Analysis</h1>
<p class="lead">This is a work in progress of <a href="https://www.pubinv.org">Public Invention</a>. It can be attached to a data server to produce
an interactive or static analysis of a respiration. It's primary purpose is to test pandemic ventilators, but it is free software meant to be reused for other purposes.
</p>
</div>
<div class="input-group mb-3">
<div class="input-group-prepend">
<span class="input-group-text" id="basic-addon3">PIRDS data server url:</span>
</div>
<input type="text" class="form-control" id="dserverurl" aria-describedby="basic-addon3">
<div class="input-group-append">
<a class="btn btn-outline-dark btn-sm" href="#" role="button" id="useofficial">Use Ventmon Data Lake: ventmon.coslabs.com</a>
</div>
</div>
<div class="input-group mb-3">
<div class="input-group-prepend">
<span class="input-group-text" id="basic-addon3">Trace ID:</span>
</div>
<input type="text" class="form-control" id="traceid" aria-describedby="basic-addon3">
</div>
<div class="input-group mb-3">
<div class="input-group-prepend">
<span class="input-group-text" for="samples_to_plot">Number of Samples (~10s per 15000 samples):</span>
</div>
<input type="text" class="form-control" id="samples_to_plot" aria-describedby="samples_to_plot">
</div>
<label for="livetoggle">Plot Live:</label>
<label class="switch">
<input type="checkbox" id="livetoggle" checked>
<span class="slider round"></span>
</label>
<div class="container-fluid">
<div class="row">
<div class="col-9">
<div id='PFGraph'><!-- Pressure and Flow Graph --></div>
<div id='EventsGraph'><!-- Events --></div>
</div>
<div class="col-3">
<div class="alert alert-danger" role="alert" id="main_alert">
Danger! Flow limits exceeded; volumes will be incorrect.
</div>
<div class="container" id="calcarea">
<div>
<label for="max">PIP (max): </label>
<div class="value_and_fences">
<div class="calcnum">
<label id="max"> </label>
</div>
<div class="vertical_alarms">
<div class="limit max">
<label for="max_h">H:</label>
<input class="fence" id="max_h" type='text'> </input>
</div>
<div class="limit min">
<label for="max_l">L:</label>
<input class="fence" id="max_l" type='text'> </input>
</div>
</div>
</div>
</div>
<div>
<label for="avg">P. Mean: </label>
<div class="value_and_fences">
<div class="calcnum">
<label id="avg"> </label>
</div>
<div class="vertical_alarms">
<div class="limit max">
<label for="avg_h">H:</label>
<input class="fence" id="avg_h" type='text'> </input>
</div>
<div class="limit min">
<label for="avg_l">L:</label>
<input class="fence" id="avg_l" type='text'> </input>
</div>
</div>
</div>
</div>
<div>
<label for="min">PEEP (min): </label>
<div class="value_and_fences">
<div class="calcnum">
<label id="min"> </label>
</div>
<div class="vertical_alarms">
<div class="limit max">
<label for="min_h">H:</label>
<input class="fence" id="min_h" type='text'> </input>
</div>
<div class="limit min">
<label for="min_l">L:</label>
<input class="fence" id="min_l" type='text'> </input>
</div>
</div>
</div>
</div>
<div>
<label for="mv">MVs (l/min): </label>
<div class="value_and_fences">
<div class="calcnum">
<label id="mv"> </label>
</div>
<div class="vertical_alarms">
<div class="limit max">
<label for="mv_h">H:</label>
<input class="fence" id="mv_h" type='text'> </input>
</div>
<div class="limit min">
<label for="mv_l">L:</label>
<input class="fence" id="mv_l" type='text'> </input>
</div>
</div>
</div>
</div>
<div>
<label for="bpm">RR: </label>
<div class="value_and_fences">
<div class="calcnum">
<label id="bpm"> </label>
</div>
<div class="vertical_alarms">
<div class="limit max">
<label for="bmp_h">H:</label>
<input class="fence" id="bpm_h" type='text'> </input>
</div>
<div class="limit min">
<label for="bpm_l">L:</label>
<input class="fence" id="bpm_l" type='text'> </input>
</div>
</div>
</div>
</div>
<div>
<label for="ier">I:E ratio: </label>
<div class="value_and_fences">
<div class="calcnum">
<label id="ier"> </label>
</div>
<div class="vertical_alarms">
<div class="limit max">
<label for="ier_h">H:</label>
<input class="fence" id="ier_h" type='text'> </input>
</div>
<div class="limit min">
<label for="ier_l">L:</label>
<input class="fence" id="ier_l" type='text'> </input>
</div>
</div>
</div>
</div>
<div>
<label for="tv">VTd (ml): </label>
<div class="value_and_fences">
<div class="calcnum">
<label id="tv"> </label>
</div>
<div class="vertical_alarms">
<div class="limit max">
<label for="tv_h">H:</label>
<input class="fence" id="tv_h" type='text'> </input>
</div>
<div class="limit min">
<label for="tv_l">L:</label>
<input class="fence" id="tv_l" type='text'> </input>
</div>
</div>
</div>
</div>
<div>
<label for="fio2">FiO2 Mean (%): </label>
<div class="value_and_fences">
<div class="calcnum">
<label id="fio2"> </label>
</div>
<div class="vertical_alarms">
<div class="limit max">
<label for="fio2_h">H:</label>
<input class="fence" id="fio2_h" type='text'> </input>
</div>
<div class="limit min">
<label for="fio2_l">L:</label>
<input class="fence" id="fio2_l" type='text'> </input>
</div>
</div>
</div>
<div>
<label for="taip">TAIP (ms): </label>
<div class="value_and_fences">
<div class="calcnum">
<label id="taip"> </label>
</div>
<div class="vertical_alarms">
<div class="limit max">
<label for="taip_h">H:</label>
<input class="fence" id="taip_h" type='text'> </input>
</div>
<div class="limit min">
<label for="taip_l">L:</label>
<input class="fence" id="taip_l" type='text'> </input>
</div>
</div>
</div>
</div>
<div>
<label for="taip">TRIP (ms): </label>
<div class="value_and_fences">
<div class="calcnum">
<label id="trip"> </label>
</div>
<div class="vertical_alarms">
<div class="limit max">
<label for="trip_h">H:</label>
<input class="fence" id="trip_h" type='text'> </input>
</div>
<div class="limit min">
<label for="trip_l">L:</label>
<input class="fence" id="trip_l" type='text'> </input>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div> <!-- end main area -->
</div>
<div>
Parameters:
<div>
<label for="tarip_h">TAIP/TRIP High Pressure (cm H2O):</label>
<input class="fence" id="tarip_h" type='text'> </input>
</div>
<div>
<label for="tarip_l">TAIP/TRIP Low Pressure (cm H2O):</label>
<input class="fence" id="tarip_l" type='text'> </input>
</div>
</div>
<div>
<button id="import">Import Trace</button>
<button id="export">Export Trace</button>
</div>
<div>
<textarea id="json_trace" rows="30" cols="80"></textarea>
</div>
<p>
This is a work in progress of <a href="https://www.pubinv.org">Public Invention</a>.
<p>
This is a tester tool for open-source ventilators.
It uses the <a href="https://github.com/PubInv/respiration-data-standard">PIRDS data format</a>.
<p>
The basic operation is receive data from web server specified in the URL above.
Probably for now that will be the VentMon Python web server that
listens on a serial port for the VentMon device or any other
device that streams PIRDS events.
</div>
</body>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
var TAIP_AND_TRIP_MIN = 2;
var TAIP_AND_TRIP_MAX = 8;
function getParameterByName(name, url) {
if (!url) url = window.location.href;
name = name.replace(/[\[\]]/g, '\\$&');
var regex = new RegExp('[?&]' + name + '(=([^&#]*)|&|#|$)'),
results = regex.exec(url);
if (!results) return null;
if (!results[2]) return '';
return decodeURIComponent(results[2].replace(/\+/g, ' '));
}
// These are defined in PIRDS.h as "constant" key words of special meaning...
var FLOW_LIMITS_EXCEEDED = false;
const FLOW_TOO_HIGH = "FLOW OUT OF RANGE HIGH";
const FLOW_TOO_LOW = "FLOW OUT OF RANGE LOW";
const VENTMON_DATA_LAKE = "http://ventmon.coslabs.com";
const queryString = window.location.search;
const urlParams = new URLSearchParams(queryString);
var TRACE_ID = urlParams.get('i')
var DSERVER_URL = window.location.protocol + "//" + window.location.host;
var NUM_TO_READ = 500;
var DATA_RETRIEVAL_PERIOD = 50;
var RESPIRATION_RATE_WINDOW_SECONDS = 20;
var intervalID = null;
// This sould be better as time, but is easier
// to do as number of samples.
var MAX_SAMPLES_TO_STORE_S = 32000;
var samples = [];
var INITS_ONLY = true;
// This is just to get the party started!
function init_samples() {
return [
{
"event": "M",
"type": "P",
"ms": 19673310,
"loc": "A",
"num": "0",
"val": 10111
},
{
"event": "M",
"type": "D",
"ms": 19673310,
"loc": "A",
"num": "0",
"val": 4
},
{
"event": "M",
"type": "F",
"ms": 19673310,
"loc": "A",
"num": "0",
"val": 0
},
{
"event": "M",
"type": "P",
"ms": 19673376,
"loc": "A",
"num": "0",
"val": 10111
},
{
"event": "M",
"type": "D",
"ms": 19673376,
"loc": "A",
"num": "0",
"val": 4
},
{
"event": "M",
"type": "F",
"ms": 19673376,
"loc": "A",
"num": "0",
"val": 0
},
{
"event": "M",
"type": "P",
"ms": 19673442,
"loc": "A",
"num": "0",
"val": 10110
},
{
"event": "M",
"type": "D",
"ms": 19673442,
"loc": "A",
"num": "0",
"val": 3
},
];
}
function unpack(rows, key) {
return rows.map(function(row) { return row[key]; });
}
const CONVERT_PIRDS_TO_SLM = 1/1000;
// we have now changed this, there will be flow and
// pressure in the same samples, and we should filter.
// TODO: I need to add maximal start and end
// samples to equalize all the plots.
function samplesToLine(samples) {
var flows = samples.filter(s => s.event == 'M' && s.type == 'F');
// These are slm/1000, or ml/minute...
// so we multiply by 1000 to get liters per minute
var flow_values = unpack(flows,"val").map(v => v * CONVERT_PIRDS_TO_SLM);
var fmillis = unpack(flows, 'ms');
// Convert to seconds...
var fmin = Math.min(...fmillis);
var fzeroed = fmillis.map(m =>(m-fmin)/1000.0);
var pressures = samples.filter(s => s.event == 'M' && s.type == 'D' && s.loc == 'A');
var pmillis = unpack(pressures, 'ms');
var pmin = Math.min(...pmillis);
var pzeroed = pmillis.map(m =>(m-pmin)/1000.0);
// the PIRDS standard is integral mm H2O, so we divide by 10
var delta_p = unpack(pressures, 'val').map(p => p / 10);
var diff_p = {type: "scatter", mode: "lines",
name: "pressure",
x: pzeroed,
y: delta_p,
line: {color: "#FF0000"}
};
var flow = {type: "scatter", mode: "lines",
name: "flow",
x: fzeroed,
y: flow_values,
xaxis: 'x2',
yaxis: 'y2',
fill: 'tozeroy',
line: {color: '#0000FF'}
};
var max_flow = flow_values.reduce(
function(a, b) {
return Math.max(Math.abs(a), Math.abs(b));
}
,0);
var scaled_flow = flow_values.map(f => 100.0 * (f / max_flow));
var flow_hollow = {type: "scatter", mode: "lines",
name: "flow ghost",
x: fzeroed,
// Convert to a percentage
y: scaled_flow,
line: {color: '#8888FF'}
};
return [diff_p,flow,flow_hollow];
}
function plot(samples, trans, breaths) {
var new_data = samplesToLine(samples);
var millis = unpack(samples, 'ms');
var min = Math.min(...millis);
var zeroed = millis.map(m =>(m-min)/1000.0);
{
var layout = {
title: 'VentMon Breath Analysis',
showlegend: false,
xaxis: {domain: [0.0,1.0]},
yaxis: {
title: 'Airway P(cm H2O)',
titlefont: {color: 'red'},
tickfont: {color: 'red'},
},
xaxis2: {domain: [0.0,1.0]},
yaxis2: {
title: 'Flow l/minute',
titlefont: {color: 'blue'},
tickfont: {color: 'blue'}
},
grid: {
rows: 2,
columns: 1,
pattern: 'independent',
roworder: 'top to bottom'}
}
var double_plot = [new_data[0],new_data[1]];
Plotly.newPlot('PFGraph', double_plot, layout);
}
// The Y-axis for the events will be percentage.
// This is somewhat abstract; each trace has
// a different meaning. In general it will be
// % as a function of some known value, which
// will be either a limit or a min or max.
{
var event_graph = [];
if (trans) {
// Transitions are simply scaled to 50%.
var tmillis = unpack(trans, 'ms');
var tzeroed = tmillis.map(m =>(m-min)/1000.0);
var tstates = unpack(trans, 'state');
var tstates_amped = tstates.map(m =>m*50);
var transPlot = {type: "scatter",
mode: "lines+markers",
name: "trans",
x: tzeroed,
y: tstates_amped,
line: {shape: 'hv',
color: 'dkGreen'},
};
// We add a hollow flow line to see in position..
event_graph.push(new_data[2]);
event_graph.push(transPlot);
}
if (breaths) {
var bmillis = unpack(breaths, 'ms');
var bzeroed = bmillis.map(m =>(m-min)/1000.0);
// I'm goint to a add start and end transition to make the plot
// come out right
var ys = breaths.map( b => 0);
var breathPlot = {type: "scatter", mode: "markers",
name: "Transitions",
x: bzeroed,
y: ys,
marker: { size: 8, color: "red",symbol: "diamond" },
textposition: 'bottom center',
text: bzeroed
};
event_graph.push(breathPlot);
// Now I attempt to extract volumes...
// Our breaths mark the END of a breath..
// so we want to draw the volumes that way.
const volume_ht_factor = 20;
var max_exh = unpack(breaths,'vol_e').reduce(
function(a, b) {
return Math.max(Math.abs(a), Math.abs(b));
}
,0);
var max_inh = unpack(breaths,'vol_i').reduce(
function(a, b) {
return Math.max(Math.abs(a), Math.abs(b));
}
,0);
var max_v = Math.max(max_inh,max_exh);
var exh_v = unpack(breaths, 'vol_e').map(e => 100 * e / max_v);
var t_exh_v = unpack(breaths, 'vol_e').map(e => Math.round(e*1000.0)+"ml exh");
var inh_v = unpack(breaths, 'vol_i').map(i => 100 * i / max_v);
var t_inh_v = unpack(breaths, 'vol_i').map(e => Math.round(e*1000.0)+"ml inh");
// now to graph properly, I must find the center of an inhalation.
// I have packed these into the breaths...
var inhale_centers = breaths.map(b => ((trans[b.trans_begin_inhale].ms + trans[b.trans_cross_zero].ms) - 2*min) / (2.0 * 1000.0));
var exhale_centers = breaths.map(b => ((trans[b.trans_cross_zero].ms + trans[b.trans_end_exhale].ms) - 2*min) / (2.0 * 1000.0));
var inhPlot = {type: "scatter", mode: "markers+text",
name: "Inh. ml",
textposition: 'bottom center',
x: inhale_centers,
y: inh_v,
text: t_inh_v,
marker: { size: 8,
color: 'black',
symbol: 'triangle-down'}
};
var exhPlot = {type: "scatter", mode: "markers+text",
name: "Exh. ml",
textposition: 'top center',
marker : {
sizer: 12,
color: 'green',
symbol: 'triangle-up' },
x: exhale_centers,
y: exh_v,
text: t_exh_v,
};
event_graph.push(inhPlot);
event_graph.push(exhPlot);
}
// Now I will attempt to add other markers, such as Humidity, Altitude, and other events,
// including possible warning events.
function gen_graph_measurement(samples, name, color, textposition, tp, lc, vf, tf) {
var selected = samples.filter(s => s.event == 'M' && s.type == tp && s.loc == lc);
return gen_graph(selected, name, color, textposition, vf, tf);
}
function gen_graph(selected,name,color, textposition, vf, tf) {
var millis = unpack(selected, 'ms');
var zeroed = millis.map(m =>(m-min)/1000.0);
var vs = selected.map(vf);
var vs_t = vs.map(tf);
var plot = {type: "scatter", mode: "markers+text",
name: name,
textposition: textposition,
x: zeroed,
y: vs,
text: vs_t,
marker: { size: 10, color: color }
};
return plot;
}
function gen_message_events(samples,name,color, textposition) {
var messages = samples.filter(s => s.event == 'E' && s.type == 'M');
// Now I want to filter our all flow error messages...
// There are two special ones, "FLOW OUT OF RANGE LOW" and
// "FLOW OUT OF RANGE HIGH"
// Basically, we will show only the first of these in a "run"
// This is rather difficult; we will instead just use 200 ms
// as a window.
const time_windwow_ms = 200;
var lows = [];
var highs = [];
var others = [];
for(var i = 0; i < messages.length; i++) {
var m = messages[i];
if (m.buff == FLOW_TOO_LOW) {
if ((lows.length == 0) || ((lows.length > 0) && (lows[lows.length-1].ms < (m.ms - 200))))
lows.push(m);
} else if (m.buff == FLOW_TOO_HIGH) {
if ((highs.length == 0) || ((highs.length > 0) && (highs[highs.length-1].ms < (m.ms - 200))))
highs.push(m);
} else {
others.push(m);
}
}
if (lows.length > 0 || highs.length > 0) {
set_flow_alert();
} else {
unset_flow_alert();
}
var lowsPlot = gen_graph(lows,"Low Range","blue",'top center',
(s => -90.0),
(v => "LOW"));
var highsPlot = gen_graph(highs,"High Range","red",'bottom center',
(s => 90.0),
(v => "HIGH"));
var othersPlot = gen_graph(others,"messages","Aqua",'top center',
(s => -75.0),
(v => v.buff));
return [lowsPlot,highsPlot,othersPlot];
}
{
var fio2AirwayPlot = gen_graph_measurement(samples,"FiO2 (%)","Black",'top center','O','A',
(s => s.val),
(v => "FiO2 (A): "+v.toFixed(1)+"%"));
event_graph.push(fio2AirwayPlot);
}
{
var humAirwayPlot = gen_graph_measurement(samples,"Hum (%)","Aqua",'top center','H','A',
(s => s.val/100.0),
(v => "H2O (A): "+v.toFixed(0)+"%"));
event_graph.push(humAirwayPlot);
}
{
var humAmbientPlot = gen_graph_measurement(samples,"Hum (%)","CornflowerBlue",'bottom center','H','B',
(s => -s.val/100.0),
(v => "H2O (B): "+(-v).toFixed(0)+"%"));
event_graph.push(humAmbientPlot);
}
{
var tempAirwayPlot = gen_graph_measurement(samples,"Temp A","red",'bottom center','T','A',
(s => s.val/100.0),
(v => "T (A): "+v.toFixed(1)+"C"));
event_graph.push(tempAirwayPlot);
}
{
var tempAmbientPlot = gen_graph_measurement(samples,"Temp B","orange",'top center','T','B',
(s => -s.val/100.0),
(v => "T (B): "+(-v).toFixed(1)+"C"));
event_graph.push(tempAmbientPlot);
}
// Altitude is really just a check that the system is working
{
var altAmbientPlot = gen_graph_measurement(samples,"Altitude","purple",'right','A','B',
(s => s.val/20.0),
(v => "Alt: "+(v*20.0).toFixed(0)+"m"));
event_graph.push(altAmbientPlot);
}
{
var [l,h,o] = gen_message_events(samples,"Message","red",'right');
event_graph.push(l);
event_graph.push(h);
event_graph.push(o);
}
// The BME680 sensor detects VOC gases. I don't think has any clinical value
// compared
// {
// var gasAirwayPlot = gen_graph_measurement(samples,"Gas A","yellow",'bottom center','G','A',
// (s => s.val/1000.0),
// (v => "G (A): "+(v*100).toFixed(1)+"Ohms"));
// event_graph.push(gasAirwayPlot);
// }
// {
// var gasAmbientPlot = gen_graph_measurement(samples,"Gas B","gold",'top center','G','B',
// (s => -s.val/1000.0),
// (v => "G (B): "+(-v*100).toFixed(1)+"Ohms"));
// event_graph.push(gasAmbientPlot);
// }
// I'm going to try putting the pressure
// in faintly to make the graphs match
var event_layout = {
title: 'Events',
showlegend: false,
xaxis: {domain: [0.0,1.0]},
yaxis: {
range: [-100.0, 100.0]
},
};
Plotly.newPlot('EventsGraph', event_graph,event_layout);
}
}
function set_flow_alert() {
$("#main_alert").show();
}
function unset_flow_alert() {
$("#main_alert").hide();
}
function check_alarms(limits,key,limit,val,f,ms) {
var alarms = [];
if (limits[key][limit] && (f(val,limits[key][limit]))) {
alarms.push({param: key,
limit: limit,
val: val,
ms: ms});
}
return alarms;
}
// Return, [min,avg,max] pressures (no smoothing)!
function compute_pressures(secs,samples) {
var pressures = samples.filter(s => s.event == 'M' && s.type == 'D' && s.loc == 'A');
if (pressures.length == 0) {
return [0,0,0,[]];
} else {
const recent_ms = pressures[pressures.length - 1].ms;
var cur_ms = recent_ms;
var cnt = 0.0;
var i = pressures.length - 1;
var cur_sample = pressures[i];
var min = Number.MAX_VALUE;
var max = Number.MIN_VALUE;
var sum = 0;
var alarms = [];
while((i >=0) && (pressures[i].ms > (cur_ms - secs*1000))) {
var p = pressures[i].val / 10.0; // this is now cm H2O
if (p < min ) {
min = p;
}
if (p > max) {
max = p;
}
sum += p;
cnt++;
alarms = alarms.concat(check_alarms(LIMITS,"max","h",p,(a,b) =>(a > b),pressures[i].ms));
alarms = alarms.concat(check_alarms(LIMITS,"max","l",p,(a,b) =>(a < b),pressures[i].ms));
i--;
}
return [min,sum/cnt,max,alarms];
}
}
function compute_fio2_mean(secs,samples) {
var oxygens = samples.filter(s => s.event == 'M' && s.type == 'O' && s.loc == 'A');
if (oxygens.length == 0) {
return null;
} else {
const recent_ms = oxygens[oxygens.length - 1].ms;
var cur_ms = recent_ms;
var cnt = 0.0;
var i = oxygens.length - 1;
var sum = 0;
var alarms = [];
while((i >=0) && (oxygens[i].ms > (cur_ms - secs*1000))) {
var oxy = oxygens[i].val; // oxygen concentration as a percentage
sum += oxy;
cnt++;
i--;
}
var fio2_avg = sum / cnt;
return fio2_avg;
}
}
function compute_respiration_rate(secs,samples,transitions,breaths) {
// In order to compute the number of breaths
// in the last s seconds, I compute those breaths
// whose time stamp is s seconds from the most recent sample
// We will compute respiration rate by counting breaths
// and dividing (cnt - 1) by time the first and last inhalation
var first_inhale_ms = -1;
var last_inhale_ms = -1;
if (breaths.length == 0) {
return [0,0,0,"NA"];
} else {
const recent_ms = samples[samples.length - 1].ms;
var cur_ms = recent_ms;
var cnt = 0.0;
var vol_i = 0.0;
var vol_e = 0.0;
var i = breaths.length - 1;
var time_inh = 0;
var time_exh = 0;
// fully completed inhalation volume does not include the
// most recent breath; we need it to be able to accurately
// divide by the inhlation_duration.
var vol_ci = 0.0;
while((i >=0) && (breaths[i].ms > (cur_ms - secs*1000))) {
cnt++;
vol_i += breaths[i].vol_i;
if (i < (breaths.length -1)) {
vol_ci += breaths[i].vol_i;
}
vol_e += breaths[i].vol_e;
const inh_ms = transitions[breaths[i].trans_begin_inhale].ms;
// note i is counting down in this loop...
if (last_inhale_ms < 0) last_inhale_ms = inh_ms;
first_inhale_ms = inh_ms;
const exh_ms = transitions[breaths[i].trans_end_exhale].ms;
const zero_ms = transitions[breaths[i].trans_cross_zero].ms;
time_inh += (zero_ms - inh_ms);
time_exh += (exh_ms - zero_ms);
i--;
}
if ((cnt > 1) && (first_inhale_ms != last_inhale_ms)) {
var inhalation_duration = last_inhale_ms - first_inhale_ms;
var inhalation_duration_min = inhalation_duration / (60.0 * 1000.0);
var rr = (cnt - 1) / inhalation_duration_min;
var duration_minutes = secs / 60.0;
// This is liters per minute. vol_ci is in liters.
// inhalation_duration is in ms.
var minute_volume = vol_ci / inhalation_duration_min;
var tidal_volume = 1000.0 * vol_i / cnt;
var EIratio = (time_inh == 0) ? null : time_exh / time_inh;
return [
rr,
tidal_volume,
minute_volume,
EIratio];
} else {
return [0,0,0,"NA"];
}
}
}
var LIMITS = {
max: { h: 40,
l: 0},
avg: { h: 30,
l: 0},
min: { h: 10,
l: -10},
mv: { h: 10,
l: 1},
bpm: { h: 40,
l: 5},
ier: { h: 4,
l: 0.25},
tv: { h: 1000,
l: 200},
fio2: { h: 100,
l: 20},
taip: { h: 100, // These are in ms
l: 0},
trip: { h: 100, // These are in ms
l: 0},
}
function load_ui_with_defaults(limits) {
var Lkeys = Object.keys(limits);
Lkeys.forEach((key,index) => {
["h","l"].forEach(limit => {
$("#"+key+"_"+limit).val(limits[key][limit]);
})
});
}
function set_rise_time_pressures()
{
$("#tarip_l").val(TAIP_AND_TRIP_MIN);
$('#tarip_l').change(function () {
TAIP_AND_TRIP_MIN = $("#tarip_l").val();
});
$("#tarip_h").val(TAIP_AND_TRIP_MAX);
$('#tarip_h').change(function () {
TAIP_AND_TRIP_MAX = $("#tarip_h").val();
});
}
function reflectAlarmsInGUI(alarms) {
var Lkeys = Object.keys(LIMITS);
Lkeys.forEach((key,index) => {
["h","l"].forEach(limit => {
var alarms_for_key = alarms.filter(s => s.param == key && s.limit == limit);
if (alarms_for_key.length > 0) {
$("#"+key).addClass("alarmred");
$("#"+key+"_"+limit).addClass("alarmred");
} else {
$("#"+key).removeClass("alarmred");
$("#"+key+"_"+limit).removeClass("alarmred");
}
})
});
}
function process(samples) {
const t = 200; // size of the window is 200ms
const v = 50; // min volume in ml
var [transitions,breaths] = computeMovingWindowTrace(samples,t,v);
plot(samples,transitions,breaths);
// How many seconds backwards should we look? Perhaps 20?
var [bpm,tv,mv,EIratio,fio2] = compute_respiration_rate(RESPIRATION_RATE_WINDOW_SECONDS,samples,transitions,breaths);
var alarms = [];
$("#bpm").text(bpm.toFixed(1));
$("#tv").text(tv.toFixed(0));
$("#mv").text((mv).toFixed(2));
if (EIratio == "NA") {
$("#ier").text("NA");
} else {
$("#ier").text((1.0 / EIratio).toFixed(1));
}
var final_ms = samples[samples.length -1].ms;
var b_ms = 0;
if (breaths.length > 0) {
b_ms = breaths[breaths.length -1].ms;
} else {
b_ms = final_ms;
}
function check_high_and_low(limits,key,v,ms) {
var al1 = check_alarms(limits,key,"h",v,(a,b) =>(a > b),ms);
var al2 = check_alarms(limits,key,"l",v,(a,b) =>(a < b),ms);
return al1.concat(al2);
}
alarms = alarms.concat(check_high_and_low(LIMITS,"bpm",bpm.toFixed(1),b_ms));
alarms = alarms.concat(check_high_and_low(LIMITS,"tv",tv.toFixed(0),b_ms));
alarms = alarms.concat(check_high_and_low(LIMITS,"mv",(mv).toFixed(2),b_ms));
alarms = alarms.concat(check_high_and_low(LIMITS,"ier",(1.0 / EIratio).toFixed(1),b_ms));
// These must be moved out; in fact,
// they must be made configurable!
var taip = compute_mean_TRIP_or_TAIP(
TAIP_AND_TRIP_MIN,
TAIP_AND_TRIP_MAX,
samples,
true);
if (taip != "NA") {
$("#taip").text(taip.toFixed(1));
alarms = alarms.concat(
check_high_and_low(LIMITS,"taip",taip,b_ms));
} else {
$("#taip").text("NA");
}
var trip = compute_mean_TRIP_or_TAIP(
TAIP_AND_TRIP_MIN,
TAIP_AND_TRIP_MAX,
samples,
false);
if (trip != "NA") {
$("#trip").text(trip.toFixed(1));
alarms = alarms.concat(
check_high_and_low(LIMITS,"trip",trip,b_ms));
} else {
$("#trip").text("NA");
}
var [min,avg,max,palarms] = compute_pressures(RESPIRATION_RATE_WINDOW_SECONDS,samples);
alarms = alarms.concat(palarms);
$("#min").text(min.toFixed(1));
$("#avg").text(avg.toFixed(1));
$("#max").text(max.toFixed(1));
var fio2 = compute_fio2_mean(RESPIRATION_RATE_WINDOW_SECONDS,samples);
if(fio2 == null){
$("#fio2").text("NA");
} else {
alarms = alarms.concat(check_high_and_low(LIMITS,"fio2",fio2.toFixed(1),b_ms));
$("#fio2").text(fio2.toFixed(1));
}
reflectAlarmsInGUI(alarms);
}
// WARNING: This is a hack...if the timestamp is negative,
// we treat it as a limited (beyond range of sensor) measurement.
// Our goal is to warn about this, but for now we will just
// ignore and correct.
function sanitize_samples(samples) {
samples.forEach(s =>
{
if (s.event == "M") {
if ("string" == (typeof s.ms))
s.ms = parseInt(s.ms);
if ("string" == (typeof s.val))
s.val = parseInt(s.val);
if ("string" == (typeof s.num))
s.num = parseInt(s.num);
if (s.ms < 0) {
s.ms = -s.ms;
} else if (s.event == "E") {
}
}
});
return samples;
}
function retrieveAndPlot(){
var trace_piece = (TRACE_ID) ? "/" + TRACE_ID : "";
DSERVER_URL = $("#dserverurl").val();
var url = DSERVER_URL + trace_piece + "/json?n="+ NUM_TO_READ;
$.ajax({url: url,
success: function(cur_sam){
// WARNING: This is a hack...if the timestamp is negative,
// we treat it as a limited (beyond range of sensor) measurement.
// Our goal is to warn about this, but for now we will just
// ignore and correct.
if (cur_sam && cur_sam.length == 0) {
console.log("no samples; potential misconfiguration!");
} else {
cur_sam = sanitize_samples(cur_sam);
if (INITS_ONLY) {
samples = cur_sam;
INITS_ONLY = false;
} else {
var discard = Math.max(0,
samples.length + cur_sam.length - MAX_SAMPLES_TO_STORE_S);
samples = samples.slice(discard);
}
samples = samples.concat(cur_sam);
// We are not guaranteeed to get samples in order
// we sort them....
samples = samples.sort((a,b) => a.ms - b.ms);
process(samples);
}
},
error: function(xhr, ajaxOptions, thrownError) {
console.log("Error!" + xhr.status);
console.log(thrownError);
// clearInterval(intervalID);
stop_interval_timer();
$("#livetoggle").prop("checked",false);
}
});
}
function compute_transitions(vm,flows) {
var transitions = [];
var state = 0; // Let 1 mean inspiration, -1 mean expiration, 0 neither
for(var i = 0; i < flows.length; i++) {
var f = flows[i].val * CONVERT_PIRDS_TO_SLM;
// var ms = flows[i].ms-first_time;
var ms = flows[i].ms;
if (state == 0) {
if (f > vm) {
state = 1;
transitions.push({ state: 1, sample: i, ms: ms})
} else if (f < -vm) {
state = -1;
transitions.push({ state: -1, sample: i, ms: ms})
}
} else if (state == 1) {
if (f < -vm) {
state = -1;
transitions.push({ state: -1, sample: i, ms: ms})
} else if (f < vm) {
state = 0;
transitions.push({ state: 0, sample: i, ms: ms})
}
} else if (state == -1) {
if (f > vm) {
state = 1;
transitions.push({ state: 1, sample: i, ms: ms})
} else if (f > 0) {
state = 0;
transitions.push({ state: 0, sample: i, ms: ms})
}
}
}
return transitions;
}
// produces a set of rising signals, time in ms of the leading edge of the rise and the trailing edge of the rise
// an array of 2-tuple
// taip == true implies compute TAIP, else compute TRIP
// Possibly this routine should be generalized to a general rise-time routine.
function compute_TAIP_or_TRIP_signals(min,max,pressures,taip) {
var pressures = pressures.filter(s => s.event == 'M' && s.type == 'D' && s.loc == 'A');
const responseBegin = 0.1;
const responseEnd = 0.9;
var signals = [];
var foundMinSignal = false;
const highFence = (min + (responseEnd * (max - min)))*10;
const lowFence = (min + (responseBegin * (max - min)))*10;
var cur_signal_start;
var state = -1; // Let 1 mean rising, -1 mean fallen, 0 risen, but not fallen
var first_sample_index = taip ? 0 : pressures.length-1 ;
var last_sample_index = taip ? pressures.length-1 : 0;
var increment = taip ? 1 : -1;
for(var i = first_sample_index; i != last_sample_index; i+=increment) {
var p = pressures[i].val;
var ms = pressures[i].ms;
if (state == -1) {
if (p >= lowFence) {
state = 1;
cur_signal_start = pressures[i];
}
if (p >= highFence){
signals.push([ms,ms]);
}
} else if (state == 1) {
//console.log("state = 1",cur_signal_start); for debugging
if (p >= highFence) {
signals.push(taip ? [cur_signal_start.ms,ms] : [ms,cur_signal_start.ms])
state = 0;
} else if (p <= lowFence) {
state = -1;
cur_signal_start = null;
}
} else if (state == 0) {
if (p <= lowFence) {
state = -1;
}
}
}
return signals;
}
function compute_mean_TRIP_or_TAIP_sigs(sigs,min,max,pressures,taip){
if (sigs.length == 0){
return "NA";
} else {
var sum = 0;
for(var i = 0; i < sigs.length; i++) {
sum += sigs[i][1] - sigs[i][0]; // time in ms
}
return sum / sigs.length;
}
}
function testdata(){
//0 (not good enough), 10 (rising), 20 (above threshold) all 10 ms apart
//saw tooth function
var data = []; // pushing 50 things into it
for(var i = 0; i < 10; i++) {
var ms = i*5*10;
data[i*5+0] = {event:'M',loc:'A',ms:ms + 0,type:'D',val: 0};
data[i*5+1] = {event:'M',loc:'A',ms:ms + 10,type:'D',val: 100};
data[i*5+2] = {event:'M',loc:'A',ms:ms + 20,type:'D',val: 200};
data[i*5+3] = {event:'M',loc:'A',ms:ms + 30,type:'D',val: 100};
data[i*5+4] = {event:'M',loc:'A',ms:ms + 40,type:'D',val: 0};
}
return data;
}
function testdataSine(period_sm){ // period expressed in # of samples, each sample 10 ms
//0 (not good enough), 10 (rising), 20 (above threshold) all 10 ms apart
//sine tooth function
var data = []; // pushing 50 things into it
for(var i = 0; i < 1000; i++) {
var ms = i*10;
data[i] = {event:'M',loc:'A',ms:ms + 20,type:'D',val: 200*Math.sin(2*Math.PI*i/period_sm)};
}
return data;
}
function compute_mean_TRIP_or_TAIP(min,max,samples,taip) {
return compute_mean_TRIP_or_TAIP_sigs(
compute_TAIP_or_TRIP_signals(min,max,samples,taip),
min,max,samples,taip);
}
function test_compute_TAIP() {
var samples = testdata();
const TAIP_min = 0; // cm of H2O
const TAIP_max = 20; // cm of H2O
var TAIP_m = compute_mean_TRIP_or_TAIP(min,max,samples,true);
console.assert(TAIP_m == 10);
for (i = 50; i<150; i+=10) {
var sinewave = testdataSine(i);
var TAIP_m = compute_mean_TRIP_or_TAIP(min,max,sinewave,true);
}
}
function compute_current_TAIP(TAIP_min,TAIP_max){ //uses samples from a global var
var TAIP_m = compute_mean_TRIP_or_TAIP(TAIP_min,TAIP_max,samples,true);
return TAIP_m;
}
// Because TAIP and TRIP are symmetric when viewed from
// from the direction of the samples; this tests that
// as a prelude to computing a single way.
function reverseArray(arr) {
var newArray = [];
for (var i = arr.length - 1; i >= 0; i--) {
newArray.push(arr[i]);
}
return newArray;
}
function test_TRIP_and_TAIP_are_symmetric() {
var samples = testdata();
var rsamples = reverseArray(samples);
const min = 0;
const max = 20;
var TRIP_m = compute_mean_TRIP_or_TAIP(min,max,samples,false);
var TRIP_m_r = -compute_mean_TRIP_or_TAIP(min,max,rsamples,true);
console.assert(TRIP_m == TRIP_m_r);
console.assert(TRIP_m == 10);
for (i = 50; i<150; i+=10) {
var sinewave = testdataSine(i);
var rsinewave = reverseArray(sinewave);
var TRIP_m = compute_mean_TRIP_or_TAIP(min,max,samples,false);
var TRIP_m_r = -compute_mean_TRIP_or_TAIP(min,max,rsamples,true);
console.assert(TRIP_m == TRIP_m_r);
var TAIP_m = compute_mean_TRIP_or_TAIP(min,max,samples,true);
var TAIP_m_r = -compute_mean_TRIP_or_TAIP(min,max,rsamples,false);
console.assert(TAIP_m == TAIP_m_r);
}
}
function compute_current_TRIP(TRIP_min,TRIP_max, samples)
{ //uses samples from a global var
if (samples.length == 0){
return "NA";
}
else {
var TRIP_m = compute_mean_TAIP_or_TRIP(TRIP_min,TRIP_max,false);
return TRIP_m;
}
}
// net Pressure-Volume Work:
// integral under P*V curve
function PressureVolumeWork(samples, a,z) {
// -1 for quadilateral approximation
var flows = samples.filter(s => s.event == 'M' && s.type == 'F');
var pressures = samples.filter(s => s.event == 'M' && s.type == 'D' && s.loc == 'A');
var pressureVolume_prod= 0;
for(var j = a; j < z-1; j++) {
// I'll use qadrilateral approximation.
// We'll form each quadrilateral between two samples.
var ms = flows[j+1].ms - flows[j].ms;
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;
if (isNaN(pressureVolume_prod)) {
debugger;
}
}
// pressure cm H2O --> atm (divide by 1033)
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);
}
// This should be in liters...
function integrateSamples(a,z,flows) {
// -1 for quadilateral approximation
var vol = 0;
for(var j = a; j < z-1; j++) {
// I'll use qadrilateral approximation.
// We'll form each quadrilateral between two samples.
var ms = flows[j+1].ms - flows[j].ms;
var ht = ((flows[j+1].val + flows[j].val )/2) * CONVERT_PIRDS_TO_SLM;
// Flow is actually in standard liters per minute,
// so to get liters we divide by 60 to it l/s,
// and and divde by 1000 to convert ms to seconds.
// We could do that here, but will move constants
// to end...
vol += ms * ht;
if (isNaN(vol)) {
debugger;
}
}
return vol/(60*1000);
}
// 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 )) {
zero = i;
}
if (expiring && transitions[i].state == 1) {
breaths.push({ ms: transitions[i].ms,
sample: transitions[i].sample,
vol_e: vole,
vol_i: voli,
trans_begin_inhale: beg,
trans_cross_zero: zero,
trans_end_exhale: i,
}
);
beg = i;
expiring = false;
vole = integrateSamples(last,transitions[i].sample,flows);
last = transitions[i].sample;
}
if (!expiring && ((transitions[i].state == -1) || (transitions[i].state == 0))) {
expiring = true;
voli = integrateSamples(last,transitions[i].sample,flows);
last = transitions[i].sample;
}
}
return 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;
function compute_breaths_based_on_exhalations(transitions) {
var beg = 0;
var zero = 0;
var last = 0;
var voli = 0;
var vole = 0;
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 )) {
zero = i;
}
if (expiring && transitions[i].state == 1) {
breaths.push({ ms: transitions[i].ms,
sample: transitions[i].sample,
vol_e: vole,
vol_i: voli,
trans_begin_inhale: beg,
trans_cross_zero: zero,
trans_end_exhale: i,
}
);
beg = i;
expiring = false;
vole = integrateSamples(last,transitions[i].sample,flows);
last = transitions[i].sample;
}
if (!expiring && transitions[i].state == -1) {
expiring = true;
voli = integrateSamples(last,transitions[i].sample,flows);
last = transitions[i].sample;
}
}
}
breaths = compute_breaths_based_without_negative_flow(transitions,flows);
return [transitions,breaths];
}
$("#useofficial").click(function() {
DSERVER_URL = VENTMON_DATA_LAKE;
$("#dserverurl").val(DSERVER_URL);
});
$("#import").click(function() {
var input_trace = $("#json_trace").val();
samples = JSON.parse(input_trace);
});
$("#export").click(function() {
$("#json_trace").val(JSON.stringify(samples,null,2));
});
// Experimental timing against the data server
function stop_interval_timer() {
clearInterval(intervalID);
intervalID = null;
$("#livetoggle").prop("checked",false);
}
function start_interval_timer() {
if (intervalID) {
stop_interval_timer();
}
intervalID = setInterval(
function() {
retrieveAndPlot();
},
DATA_RETRIEVAL_PERIOD);
$("#livetoggle").prop("checked",true);
}
function toggle_interval_timer() {
if (intervalID) {
stop_interval_timer();
} else {
start_interval_timer();
}
}
function setLimit(ed) {
if(ed.which == 13) {
var id = ed.target.id;
var v = $("#"+id).val();
var vf = parseFloat(v);
var destruct = id.split("_");
LIMITS[destruct[0]][destruct[1]] = isNaN(vf) ? null : vf;
}
}
$(".fence").keypress(setLimit);
$("#livetoggle").change(toggle_interval_timer);
$("#startoperation").click(start_interval_timer);
$("#stopoperation").click(stop_interval_timer);
$( document ).ready(function() {
if (window.location.protocol == "http:")
DSERVER_URL = window.location.protocol + "//" + window.location.host;
else
DSERVER_URL = "http://localhost";
$( "#dserverurl" ).val( DSERVER_URL );
$('#dserverurl').change(function () {
DSERVER_URL = $("#dserverurl").val();
start_interval_timer();
});
// $( "#num_to_read" ).val( NUM_TO_READ );
// $('#num_to_read').change(function () {
// NUM_TO_READ = $("#num_to_read").val();
// });
$( "#traceid" ).val( TRACE_ID );
$('#traceid').change(function () {
TRACE_ID = $("#traceid").val();
start_interval_timer();
});
$( "#samples_to_plot" ).val( MAX_SAMPLES_TO_STORE_S );
$('#samples_to_plot').change(function () {
MAX_SAMPLES_TO_STORE_S = $("#samples_to_plot").val();
});
samples = init_samples();
process(samples);
start_interval_timer();
load_ui_with_defaults(LIMITS);
set_rise_time_pressures(
TAIP_AND_TRIP_MIN,
TAIP_AND_TRIP_MAX,
);
});
</script>