 Yeah, we should be in life If you haven't checked the bargeos.com, please do so We're currently using this music from hand gesture actually using it because What's good for exercising, but also was touching my face and stuff during when talking so it'll actually be a reminder Well, when I do it when I edit the videos later, I can't remove those bit Probably won't stop doing it. It won't do magic, but yeah, it's a good reminder Yeah, that's what thinking thinking pause looks like But yes, we can start a stream by generating some music as well So it will do short notes Long notes and it has a scale and that was a false detection of the other hand which has a different scale Which is more annoying that's why I don't don't normally use it I'm left-handed so probably should switch between them and Only after finishing this after publishing this tool. I realized I never heard of the theramine before But yeah, it's a really cool instrument, but that one has A distance to an antenna And then another antenna for that controls the volume So I probably should have done it that way, but yeah, maybe next time when we get to it And if you haven't checked any of the other tools, please do so currently We're working on fuzzy logic We start the development in a second We might as well start now So we're combining fuzzy logic with this ecg game That's essentially a bot that will be playing the game For us or in addition So we could like compete compete with the robot currently it looks like Is Is that It has now a noise option And that's mainly to see how well the Robot is doing When the noise is increased So currently it's just generating all these false false alarms We will be fixing this before publishing the tool and yes, you can still Play yourself by clicking on Ab normal ecg The text to speech can never get me saying abnormal It's always thinks it's something else. So you should not click on what that one, which was a normal ecg and this one missing a bit missing the peak And at the front. So we are not clicking on it. We're getting Correct rejection And when clicking on an abnormal ecg waveform, we get a hit And that's what the bot does as well We had a tuning of it before that just works 100% of the time, but it was relying on some Magic numbers that we now removed The system now performing much more. So it's essentially clicking on everything It's making a decision that everything is abnormal And we will be fixing that we're looking at the was it four parameters Positive peaks the number of positive peaks the number of negative peaks Amplitude and the R peak sharpness. So it's finding It's assuming that Yeah, so this is when I have to go edit this stuff in the video when I Doing something funny A with my face So obviously now I can Win the the bot, but we pretty sure can easily make it Work much better to the point where human can Sit back relax Watch the robot in action And so we have this four files of this html that you see on the screen Might start populating gpt. We might try and do something different. We're also okay before you're screaming at me I also do use a github co-pilot But it's most of the time not producing great results Hey, but yes, we use that as well. So we have a html Something funny with the how the text box on the open a website works. I don't know. It could be specific to chrome on linux Then we have So the waveforms are being generated using simple math equations This is all happening in javascript. So front end and the fuzzy logic Which I'll get to in a sec is working working back end. So they Sort of fuzzy logic the robot doesn't know What the Current waveform label is So before you start saying when playing against the robot before you start saying oh, the robot is cheating somehow No, it doesn't have the labels Now we have this game logic doesn't do much Or might as well get the co-pilot to work Just by explaining the code quickly And we'll try this one shot prompt single shot because it tends to work Better to begin with and then performance drops with consecutive prompts Yeah, we do Constance waveform functions variations. Yeah, we have a bunch of variations as you can see as you saw in the game itself Generation and noise addition is also in javascript and now the big Reveal the python code So this one has the It's a flask application and It does the fuzzy logic business So just well The game logic, I don't think it does much but we will explain it with a co-pilot as well No, it's actually does quite a bit the initialization drawing The game itself. So it does the scoring in the game calculating the scores Yeah, I probably should break it break it up a bit, but that's uh, yeah 200 lines of code. It's not too bad It does the waveform analysis noise level adjustment And starting the game out the python code This message is too long. Okay. So the python code. Yes, it's a 400 lines of code We'll get rid of a github. Um, what's called the hhpt can take How long a message can be it's taking the code as an input. Yeah, it won't tell you Just won't reveal any information about itself, but Oops, yeah, that's the kind of stuff we have to then edit out in the video This is a Thinking thinking pose. Yeah, the pod currently is this it just keeps Saying that everything is abnormal You can still get some points out of it well because the algorithm generation I think is biased. I think it has something around the The other thing if the co-pilot the code thing about it is we can use this workspace And actually ask How what's the ratio between normal and abnormal ecg waveforms? So it will Try and find the relevant bit Supposedly in all the files that are currently open Should tell you the reference as well. So it should tell you what it was looking at But yeah, it's taking some time So it looked at the waveforms js and the html file And it didn't produce a result She's unfortunate because I think it's 60 40 check It was looking at the wrong file I vaguely remember something about the 60 40 Unconfirm Where's the Generate waveform No, it's level. Yeah, this one point six Yeah, so it is 60 40 well, that's why by clicking on every waveform you are able to A overall over a longer periods of time gain some points But you won't be doing it very well Because you're producing all this false alarms. So yes, there's the 52 to 38 Ratio So yeah, this is the kind of copilot is not being able to handle even though it's fairly simple As stuff Okay, so we are We are live streaming on Online Well, actually live streaming on three different platforms. So we won't mention the names And we are developing this flask application that we would like to publish today But I need your help We need to update the fuzzy logic algorithm parameters As in the rules and the membership functions We also got some examples of the ad output that i'm getting Can you look at the fuzzy logic analysis result? And obviously we also having an issue with the Number of peaks being calculated I assume this is to do with the noise Last time we were Trying to add a basic Filter, but if we do do that, we'll have to show it to the human Playing the game as well To keep things fair Can you suggest the specific code changes or Prompts for github copilot. So if you could generate code with placeholders That github copilot could feel out that will be great Please go over all of the code provided and the images uploaded Yep You've got a comprehensive flask out with embedded javascript for waveform analysis and game mechanics plus a fuzzy logic analysis in python Let's break down what you're looking for Fuzzy logic algorithm parameters your fuzzy logic setup needs refining You want rules and membership functions that accurately reflect the characteristics of the ecg waveforms and their abnormalities Output analysis you've observed some inconsistencies in the peak calculations likely affected by noise Filtering and fairness you consider applying a basic filter to clean the noise but want to maintain fairness for the game participants Given the complexity of the ecg signal, especially on the noise the fuzzy logic rules should be sophisticated enough to differentiate between nuanced patterns Here's a game plan Refine fuzzy rules ensure that your rules account for normal variations in ecg waveforms so that only genuine abnormalities increase the abnormal score You want to look at aspects like the The typical number of peaks in a normal ecg cycle Expected variations in amplitude due to noise versus pathological changes Adjust the prominence and height parameters used in skippy signal find underscore peaks to be more tolerant of noise Implement a pre-processing step to smooth the signal such as a moving average or low pass filter which can help reduce the effect of high frequency noise Fairness in filtering if you apply a filter to the signal that the fuzzy logic sees you should apply the same filtering in real time to the waveform displayed to the user This way both the human and the algorithm are making decisions based on the same input data For the fuzzy logic part you need a balance of specificity and sensitivity You don't want to tag normal variations as abnormal false positives, nor do you want to miss actual abnormalities false negatives Adjust your membership functions to reflect the degree of certainty you have about a segment's abnormality based on the input variables Here's a sample set of refined fuzzy rules and membership functions as placeholders that you might want to consider for github copilot to fill These are starting points and you need to attractively adjust these based on the performance of your system in detecting the ecg abnormalities For the peak detection issue, here's a possible direction Remember to integrate any pre-processing step into both the analysis pipeline and the real-time display for the user Lastly, since this is an iterative process, you want to test these changes extensively and tweak them based on results you're getting This isn't a one-size-fits-all kind of situation and yeah, gpt 4 Yes, single single shot prompt. I mean it says everything seem legit however the code It's not quite there. So it's suggesting Suggests to just to rename the sharpness And that should be fine. We don't have to do it Oh, it's actually changed it from triangular to trapezoidal with a triangle triangle in the middle Now we really have this code. I'm not sure why it's generating it Again, I don't think this will make much difference. So A comment that out, a comment that that was a gpt 4 suggestion And notice that it's fine. It's doing the same for amplitude and using trapezoidal membership functions instead of triangular ones Which Yeah, I don't think it will make much difference. I used trapezoidal ones before to kind of make more sense But the triangle ones should work just fine I'm not sure why they decided to Make these suggestions if they can saying a co-pilot can do the right kind of thing Right now the rules The rules is something We do have to go over Now, yeah, when noise is removed. So that's actually what we are trying to show is that When there is no noise The algorithm the machine the fuzzy logic algorithms doing much better So it's like playing this is abnormal, which is correct Yeah, it's now started moving much slower because we The human went a negative score. Let's go That's because I wasn't paying attention. It's a normally city. So I should get 10 points Yeah, I'll need 12 correct responses to get back to zero The machine is doing okay So that's after Lowering the noise Level all the way to zero So the false alarms and misses are at 57 and 21 Ideally it will just stay that way Yeah, so we have no noise The fuzzy logic is doing pretty pretty pretty good I think it might not be making any mistakes whatsoever So for the demo, we might just add the low amount of noise where it does mistakes sometimes No, I just didn't miss So it was an abnormal A waveform and it didn't click on it. So it's making mistakes even When there is no noise. This is something This is something we definitely want to sort out. It should be pretty straightforward There's some sort of basic adjustments that we need to make The positive peaks 3 and 1 this is working okay The amplitude doesn't look like raw amplitude. That amplitude doesn't seem to be changing at all So it's 0.83 y now it changed to 0.5 Right when you don't have the negative peak The amplitude is changing 0.58 seem to be the maximum amplitude which is a bit old should go to A One or as close to one as possible Yes, so that the amplitude is probably not oops The false detection of a hand Yeah, sometimes falsely detecting a hand on my ear or Something like that The music bit I don't know if you call it music or not I do When the Yeah, the false alarm stayed at 57 The misses Went from 21 to 28 So I think it's missing a very specific waveform The thing about it is that we don't want to tune it up You know, we we don't have any we don't want any magic numbers That You know make the Algorithm work better we want to just to Just give it the general instructions And for it to just Do its thing Let's go over those suggested rules I need to explain Each one Because I forgot You Don't feed this screen as well, which is not good Yes, those are Again the gpt4 suggestion Don't think we will be testing this That's not what the problem Is Right there peak Detection it says suggesting to do Change the prominence value And yes, we do have a prominence value They currently every time There's something funny on your face. It's a It's a prompt for me to Have a break listen to some music Hopefully this music is not copyrighted I'm assuming if you create a musical instrument, then the music is yours. I don't know. What do you think? It's the quick recap. We tried this A Single what's called one shot prompt Of gpt4 to try and fix some things with this fuzzy logic Algorithm that is playing This ecg scoring game That's currently hallucinating a bit and pressure one of the waveforms that Never detects correctly It's why they miss it. So one of the it's always missing A one abnormal ecg and yes, I know which one it is So this is kind of unfair For me to do this because I know exactly what the waveforms are A later at the later stage we're also trying to add We can assume because this synthetic ecg we can get add like an infinite number of A different waveforms And see how the algorithm responds So the rules should just be Logical nothing fancy. So we'll get the era in gpt4 Was an error generating a response. Obviously if I click regenerate it will Start again. It was a long prompt and a long response. What if I just Thresh the page And I haven't finished when it's in this continue generating position that actually gives me And the option to interact with it again, but I don't have to continue If I do continue I suspect it will Give me the same error again. Yes That's right. So it's behaving in an odd way. I don't know is it just for me Is it because I'm on using the chrome browser in linux I was thinking actually doing A tool where it's using an api and my python just prompts The gpt for whichever model just continuously non non stop Obviously monitoring the cost. Maybe it will be even Cheaper, I mean you can always cap it at whatever 20 dollars a month That gpt4 cost So for that, that's how drinking sounds like. It's the other hand. I like the other hand much better I was saying I have to change their hands because I'm well I can do both at the same time That was the idea but essentially applying to Musical instruments at the same time. I wonder if there's any musicians In the crowd who would like to test this and provide the feedback Okay, I don't know gpt4 just got stuck on me And yeah, there's no point asking you anything about the working the behind the scenes of how this terminal Actually works is there So I think we will just have to Leave with it And so you generated pretty generic responses. I'm trying to get to the specifics of the code And now it seems at the moment In the past we removed the frequency A metric we were looking at the frequency as a parameter And now the result of it Is that we always get a miss for a certain type of waveforms synthetic waveforms That have the r big too close to the t wave And this must be because we removed the frequency A component How would you suggest fixing it? I Would like a specific code Yeah, I'm thinking should we bring The frequency back the reason we removed frequency to begin with is because we are not looking at the continuous ECG waveform We're looking at each q R s complex one at a time so it kind of didn't make sense to look at frequency But obviously now it seems like that might have been a mistake Because if the r big is moving around being too Coming too quickly or Coming too late We don't have a detection mechanism for that We could of course Look at distances between peaks, but then we'll have to make an assumption Assumptions as to which big is which And also if we have a missing peak that would not work as well Any suggestions Welcome Yep It sounds like the removal of the frequency metric from your fuzzy logic analysis has created a gap in your ability to accurately characterize ECG waveforms where the r peak is too close to t wave This is indeed a crucial aspect of the ECG waveform analysis as the timing between different peaks like the r interval For example, you indicate various cardiac conditions If the frequency component was helping in detecting such abnormalities One approach would be to reintroduce a similar metric that considers the timing between peaks Since you're looking at qrs complexes individually, the concept of frequency might not apply directly, but the interval between peaks is still very relevant Here's a high level suggestion for your python code that involves calculating the interval between peaks and using that as a metric Calculate intervals between peaks for each waveform calculate the intervals between the significant peaks p q r s and t For example, measure the pr interval qrs duration and quart interval Create a fuzzy variable for intervals define a new fuzzy variable for each of these intervals with appropriate membership functions based on normal ranges Define rules using intervals create rules that consider these intervals For instance, a short quart interval might lead to a higher abnormality score Here's a conceptual python snippet to get you started It's nice, but again, what happens if uh, if one of the peaks is missing as we do Well have happening in reality and specifically in reality One of the peaks might be missing So how do we deal with that? When calculating intervals, how would you make an assumption? Which peak is which? And which one is missing In the code pr underscore interval qrs underscore duration and quart underscore interval are placeholders for the intervals you calculate You'll define ranges and membership functions for these based on the typical values you expect in a normal ecg Then use these as antecedents in your fuzzy logic rules Adjusting your peak detection to be tolerant of noise will still be important But this approach gives you a way to capture the temporal relationships between peaks that are crucial for diagnosing certain cardiac issues By doing this, you bring back a form of frequency analysis that's tailored to the segmented nature of your ecg analysis Which could mitigate the issue of missing certain waveform abnormalities This method also naturally extends to handling missing peaks since the absence of a peak would drastically alter the expected interval thus flagging a potential abnormality I wasn't actually listening to the point But yes, I'm suggesting to add these four intervals that yes, it's uh, we have similar stuff obviously in the waveform generation So say We have these two qrs variations so one of them will have A gap between So the r peak comes late However, the fuzzy logic algorithm deport the machine that is playing the game Should not know About how the waveforms were generated So I'm suggesting adding three more parameters. I don't think this will work Because again, some of the waveforms might be missing some of the peaks Not might they are missing some of the peaks How do I say peaks correctly? Yeah, I don't want to Trigger the microphone So I'm trying to say the p In a softer way, but the Speech to text never picks it up correctly peaks peaks Yay, English is funny that way funny Yep, really have to get rid of those false detections of the Other hand. It's really annoying. I think it might be happening when it's over the face When the hand is over the face Don't really need the face detection might get rid of it It's clear The challenge of identifying which peaks are present and which are missing is a common one in ecg analysis Especially when dealing with noisy data or atypical waveforms In a real ecg missing peaks can indicate a variety of cardiac arrhythmias and abnormalities So it's crucial to handle this correctly Here's a step-by-step approach to deal with missing peaks in an algorithmic way Peak detection robustness use a robust peak detection algorithm that can handle noise and atypical waveforms You can employ methods like adaptive fresh holding or machine learning based peak detection Peak labeling after detecting all the peaks you need to label them You can do this by looking at the expected sequence of peaks p q r s t and the typical relative positions and amplitudes For example, the r peak is usually the highest positive peak and the s peak follows the r peak If a peak is missing like the p wave the sequence will be disrupted and you might see a different pattern Assigning intervals once you have labeled the peaks you can assign intervals If a peak is missing you can skip the calculation that involves the missing peak or use a placeholder value that indicates a missing peak Fuzzy logic adaptation adapt your fuzzy logic system to handle missing data For instance, if the p r interval is missing because the p peak wasn't detected your system should increase the likelihood of an abnormality Account for variability understand that in the real world the distance between peaks can vary even within the same patient over time Your algorithm needs to account for this variability and not rely on fixed thresholds For the fuzzy logic part, here's a sample of how you might modify your code to handle missing peaks Yeah, I'll have to read this again So yeah humans are really good at getting distracted on they In the above code we use none to indicate a missing peak and adjust our fuzzy logic inputs accordingly You may decide to input a specific value that indicates a missing peak to the fuzzy system We could have separate rules that specifically handle missing data scenarios Finally about your speech to text issue with the word peaks it can indeed be a bit tricky If your speech to text software is consistently misinterpreting it You might need to enunciate very clearly or even consider using different software writing custom words to its dictionary if that's an option But in the context of coding and development as long as the term is clear in the written code and documentation I'm getting this network errors we have GPT-4 a co-pilot also playing up saying it doesn't have the code which is a bit odd GPT-4 didn't finish that code We need to regenerate the whole thing When we regenerate there is normally an option to move back and forth to the new and the previous version being generated Yeah monitoring That should be the moment we need to fix I did remember that we have a calculate membership as a separate function, but that's only Now that doesn't do much So I actually need to Select a code Okay, now it's working. Yeah, so we implementing a fuzzilogic system To analyze some data. Yeah, it doesn't know what data We are looking at even though could have looked at the names Likely related to ecg readings. Okay, it did do that to actually read the whole thing. Don't you? fuzzilogic is the form of Many valued What logic in which the truth values Of variables may be any real number between zero and one. Yeah, so all the numbers have to be normalized, which is I think that's the case at the moment Well, especially not when we have noise then the number of positive peaks it just shoots up through the roof Remove the noise. It just gives the correct number of positive and negative peaks Might first sort out the no noise situation that will kind of make sense Yeah, I think it's still giving we had the frequency Components or I keep repeating the same thing over and over again, but that's important. That's why Our system is not working at the moment It's such as that Looking at calculating intervals The thing is our python code is already 400 lines of code. So I'm not sure if we Should add the extra parameters or not I think it's suggesting a three parameters If we measure if we are calculating the qrs detection Do we still need R peak sharpness To be calculated might have more questions as well Yes, so the intervals are nice Then we asked what Happens if one of the peaks is missing and I was suggesting to calculate intervals with missing data An additional function Obviously every time you ask for something it generates a An additional function. So can I make sure I understand what you mean? If I have Do I still need But look by looking at the inputs of these functions The answer would be yes that I do still need them both Just inflates my code So after the suggested changes, how many parameters and what are they We will be looking at Calculating the qrs duration and the sharpness of the rp can serve different purposes and give different insights into the waveform qrs duration This metric gives you information about the overall width of the qrs complex Which is valuable for identifying certain types of cardiac abnormalities such as bundle branch blocks R peak sharpness this measure can indicate the steepness of the r waves ascent and descent It's useful for detecting specific conditions that affect the shape of the r wave such as myocardial infarction or pericarditis So even if you're calculating qrs duration, you might still want to calculate r peak sharpness because it provides additional complementary information Now regarding the functions you mentioned Def calculate underscore intervals underscore with underscore missing underscore data detected underscore peaks This function is intended to handle situations where you may have missing peaks within your ecg waveform It uses the detected peaks and calculates the intervals between them even if some are missing Def calculate underscore intervals waveform This function seems to calculate intervals based on a complete waveform with no missing peaks If you have two separate functions for calculating intervals one that assumes a complete waveform and another that can handle missing peaks You may end up with redundant code Instead you could combine these into a single more robust function that calculates intervals and handles missing data within the same function Here's an example of how you could do that With this approach you have a single function that calculates all the necessary intervals and the r peak sharpness handling missing peaks as part of its logic After these suggested changes the parameters you will be looking at are the intervals between identifiable peaks Which may include the pr interval qrs duration quart interval etc and the sharpness of the r peak You may have a different number of parameters based on what is detectable in the waveform The goal is to streamline your code to avoid redundancy while still capturing all the necessary information from the ecg waveform to make accurate determinations about cardiac health Are we adding another A function Assuming waveform is not by array calculate the intervals between peaks for example intervals between r peak in the ecg no we do not have intervals between r peak because We're looking at in the visual p q r s d No, so that's no good As the peak detection logic Do have that function Why do you stuff up the name? Yeah, we have peaks mentioned 174 times Just a variable is it? Yeah, we'll just have them in process data Can we have it in a separate function? Yeah, there's a placeholder. This is not being Copilot do anything useful. Let's do a musical break check for any questions as well. I don't think there are any But we will check Anyway With this approach you have a single function that calculates all the necessary intervals in the r peak sharpness handling missing peaks as part of its logic After these suggested changes the parameters you will be looking at the intervals between Identifiable peaks which may include the pr interval q i s duration court interval, etc. And the sharpness of the r peak You may have a different number of parameters based on what is detectable in the waveform The goal is to streamline your code to avoid redundancy while still capturing all the necessary information from the ecg waveform to make accurate Determinations about cardiac health You generate the following functions Or regenerate them if you already generated them before Can you make sure you include all the necessary code in the function? So it can be executed with no errors We eventually want to integrate everything into app by What is it analyzing for? Yeah, don't like when always expand the output okay Don't like when it's analyzing it means it's trying to execute something on its own server I think Which is Not what I want I need the code in the text Or Yeah, because now it will say oh, I can't execute it. I don't have the data Something silly like that So I'm not sure why try To begin with I have created placeholder functions for detect underscore peaks and calculate underscore intervals in python You would need to integrate and adjust them based on your actual waveform data The detect underscore peaks function is designed to detect peaks using a skippy signal find underscore peaks function I've set a relative height threshold of 50 of the maximum value of the waveform and the minimum distance of 25 samples between peaks These values are arbitrary and should be adjusted based on the characteristics of your ecg data The calculate underscore intervals function uses the indices of the detected peaks to calculate the intervals between successive peaks and returns these intervals in a dictionary Again, you might need to modify this function to fit the specific peaks. You're looking for eg pq qrs duration, etc Here's the code for you to integrate into your app.py I think it's looking at my previous code. We shared all the code with you So first, I don't think it's a good idea to try and execute anything on your server. Give me the text of the code To integrate this into app.py you would place these functions in your script and call calculate underscore intervals within your process underscore data function Make sure to replace your underscore waveform underscore data underscore here with your actual data when using these functions Please note that this code is a starting It kind of always fails at the end of the response. It's a bit odd It's actually not bad the minimum number of samples between It's meant to be consecutive Successive peaks well one one thing is for sure A ggp is much better As a much better english than I am that's for sure Yes, I like that one Turning peaks So it's a different way of calculating peaks A calculating intervals Still have a missing before we had a missing beat Still calculating the rpx sharpness. That's okay Usage is good because later when we update the code above It might just refer to this hopefully To refresh this page I want the missing that one was a dealing with missing data Okay, this is messy. Why is it returning? The new one is not dealing With a missing ex I wanted just to remind all the tools we make are available on bionicaos.com Go check them out Don't forget to Leave your comments that can be on any platform wherever you watch this The website doesn't actually have a tool for it. Yeah, the other thing is we are Gonna be doing a summary of all available biomedical data sets There's quite a lot. Yeah, the good thing about the gpt4 now actually providing links I'm more familiar with the eeg ones that gave a Actually not Know any of those to know if they are legit or not Let's provide the links now from where it actually took the information So this is from a readme file from six months ago. Looks like quite a comprehensive list of eeg data sets Yeah, ieg Dot org is not on the list Kind of really comfortable showing what's on the github Because of Where is it? The license where is the license? Well, anyway, it all meant to be open source creative comments or mit one of those Very missive licenses and you have a page here Yes, this is on publicly available eeg data sets on open bci Website yet. I don't want to show that Not because I don't like it, but because there might be Some copyright issues even you know by showing the logo And this one is an open Discover eeg and open fully automated eeg pipeline. I mean, I'm not sure what they They use the word pipeline might suggest It's not actually accessible Front yes, so this push should be open source A website as well But yeah, so in this case we have this nmt. This this name comes up a lot Sculpey gdata set open source annotated that set Of healthy n pathological eeg recordings for predictive modeling Now that's all nice and good. There's a standard montage So that's nice Some histograms on the population age and Abnormal normal eeg That's that structure. That's looks all great. But obviously One will be looking for the link To the actual data Which must be hiding somewhere At the bottom of the article There it is when you open it it sends you to this We at the university website That has some data set code repository download Yeah, that's obviously not related. Here it is halfway through the list I have code sitting on key tab And then you have this Z file sitting on this chatbotmart.com And when you open this one it goes to go daddy you can buy chatbotmart.com Or I don't know how much And obviously the data Is not available So that's zip file Um, you know when linking from the Paper Is nowhere to be found You of course can try the A github This also has link To the data set It's from two years ago data folder Labels good doesn't seem to Have the actual data Has a different link Which goes to the same thing with chatbotmart Are all of them on chatbotmart? No, anyway the links are just weird Yeah from all over the shop So i'm not sure if this Data set is available anywhere. So yeah, that's what happens to most Of public datasets So this lists here An educated guest that only Um Like 1% or so under 10% of these datasets will actually be available Some will require some sort of crazy registration And some just Essentially not be available anymore But yes, we will be Essentially creating a list like that And uh indicating, you know, essentially some sort of difficulty score of how Easy it was or how difficult it was to actually Get hold of the data And once you do get hold of that the main question then is if the data is in its raw format or some sort of metadata A down sample or processed or whatever which we do not like Okay, a couple of things with the code that we Currently have we need to fix it and integrate it properly And Can you help with that? Ideally just Regenerate the whole code if it's too much regenerate functions If that's too much give instructions for github co-pilot to do it And we want to make sure that with noise level Set to zero the Puzzy logic algorithm doesn't make any mistakes I think for that we need to sort Out that frequency Uh component or which Sorry for that noise So for which we have I think instead of frequency we now have the distance the time Between the different peaks, but it's not currently being fully integrated We need to add the membership functions for it And the rules for the additional parameters And are you can you do it? Yourself or provide prompts for github co-pilot which are where you prefer by the way if you feel like being funny or something Eh Go for it, but probably not too funny It's something really wrong with the text window with the Window we insert the prompt they were expected to Is scroll automatically to the bottom or something, but let's do that Clear Understood you're looking for an integrated solution that correctly processes ecg waveform data with noise level set to zero And makes use of the intervals between peaks in the fuzzy logic analysis Since the frequency component has been removed the intervals between peaks will serve as the new metric for analysis We will need to modify detect underscore peaks to handle noiseless data accurately Integrate interval calculation into the processing function Add new membership functions and rules for interval-based analysis in the fuzzy logic system Here's how you can integrate everything into your flask application along with placeholder membership functions and rules that you can further refine Generating like a while I mean we have been Do working on this tool for quite some time. Yeah, that's the one that's always being missed So that's the one we always get the miss for currently Rules in this code you need to add the logic for calculating the specific intervals you're interested in For instance the r-interval is the time between two consecutive r peaks and you might want to add pr interval qrs duration and so forth Ensure to populate the intervals dictionary with the calculated intervals and use them as inputs for fuzzy logic system Update the membership functions and rules to match the actual intervals found in normal ecg readings Remember this is a template and requires testing and refinement to ensure that it functions correctly with your specific ecg data Regarding the noise level set to zero requirement. You would ensure that your waveform data is noise free before it's processed by this system If you have any noise reduction or filtering implemented, you can skip it or set the parameters to a state that doesn't alter the signal Lastly to avoid any text window issues Make sure your id or text editor is functioning correctly and if the issue persists consider resetting it or switching to another editor If you're using a web interface for coding check for any browser extensions that might interfere with the text input Yeah, we're not plotting anything in python So we can comment the the mudplotlib Byplot out Everything else is correct. Yes. We have this flash application Have the analyze waveform Have data processing Save a copy of this quickly. Ah git Is not properly working because I mean eventually we I don't mind for the whole project to be on github, but It's just gonna be an absolute mess So essentially what you see on the website Is trying to deal with that mess Is this um a lot of tools that actually not being listed that are under development You can go to them if you know the url Like the bot currently This one would not be working a because We haven't added it as a flask application yet So we don't do frequency anymore When processing the data we should calculate intervals as well After existing peak detection Yeah, we have it for debugging at the moment plotting Is tough But I'm not I don't think it will Actually work at the moment Maybe it will have to bring the plot function back Yeah, so this is how the current detection Detection works We'll just keep uh overlaying stuff This is the type of waveforms that we have Yeah, so this noise level that's found the 35 positive peaks Which is obviously not correct Popping up would be an easy way of Breaking uh stream and everything In case of finding the A peaks and doing the amplitude calculation Printing it out as well We are not normalizing it because This is essentially dividing by 600. We'll do the Normalization Yeah, we're not returning processed data. I'm doing it for any other parameters And no If you're doing extra Extra hours Yeah, that's a plot. It's trying to plot still That's okay now Yes, we're running this application there Only local at the moment. Yeah, we better not do this Again because it's uh plotting stuff In the back end that breaks the the flow Of the software Yeah, it's good to print the intervals So need to add them in here. When does it get the frequency from it should be? intervals Yeah, that is for whatever reason being generated at the dc level of 300 So we actually reduce it back to to zero That's instead of a d trending. Yes, we could use a fancy d trending algorithm as well. Do we have frequency currently Yeah, the amplitude is not normal as anymore. You can get rid of that. Don't have frequency Abnormality is now called Abnormality score and we also produce a decision. So it's a yes. No normal abnormal A decision Yeah, I wasn't sure about this auto a generation Of a membership functions I don't think we need this where's uh Yeah process that we have the intervals And the intervals should be returned Oops Yes intervals That's right Yeah, don't need that line. Let's do Some music and recap the calculate intervals function Is it giving a different function every time? So this is better. This is a covering A case Where there is no rp for example, I need to modify Get rid of that Yeah, fuzzy logic analysis That's the tricky business Yes, so we don't have our our interval because it's not continuous waveform A can we rewrite this function? Taking into account the newly added parameters That to do with the time A distance interval between Um the different peaks To rewrite the fuzzy underscore logic underscore analysis function with the newly added interval parameters You'll first need to define fuzzy variables for each interval you're analyzing You'll also need to define membership functions and rules for these intervals Here's how you can adjust your fuzzy underscore logic underscore analysis function In the rewritten function I've added a new antecedent for the rR interval to find its membership functions and create new rules that relate the rR Interval to the likelihood of abnormality This is just an example and you need to adjust the ranges and membership function parameters According to the specifics of your data and the expert knowledge you have on ecg interpretation You would also add similar antecedents membership functions and rules for any other intervals you're analyzing pr interval qrs duration etc Remember to test the new fuzzy logic system thoroughly with a variety of input data to ensure that its functioning is expected and making accurate assessments A getting confused here again just to Make sure we are clear We are reviewing every individual pq rsd waveform at a time So Doing an rR interval would not make any sense Instead We would like to be able to detect if the r peak is too close to the p wave or the t wave within the one complex Thank you for clarifying If we are analyzing individual pqrs complexes and need to determine the proximity of the rp to the p wave and t wave within a single complex We would focus on the pr interval and the rt interval respectively These intervals are important in diagnosing various cardiac conditions Here's how you can adjust the fuzzy underscore logic underscore analysis function to include these considerations Can you continue the code generation? And address a couple of questions Why the rt npr intervals antecedent Variables do not go all the way to one But zero point to one instead Also, if the rules Instead of adding four new rules, it's the way combining them all considering The output for all of them for the abnormality Is set to be likely Certainly, let's continue the code and address your questions The pr and rt intervals are typically measured in tenths of a second, hence the 0.21 upper limit, which could represent 210 milliseconds However, the actual range will depend on the typical duration of these intervals in a normal ecg If you expect intervals to be up to one second, then the range should indeed go up to 1.0 The choice of 0.21 was arbitrary and based on a common duration for pr intervals It should be adjusted to reflect the actual data you're working with As for combining the rules, since they all suggest the same outcome, likely, abnormal, you could create a composite rule that triggers when any of the conditions for the pr or rt intervals being too short or too long are met This would simplify the rulebase Here's how you can continue the function and implement these adjustments This code snippet completes the fuzzy underscore logic underscore analysis function and incorporates the modifications for the pr and rt intervals, as well as the combined rule for an abnormality Ensure that the rest of the function, as well as rule one through rule six, are implemented appropriately with your data Remember, this code needs to be tested with actual ecg data to fine-tune the membership functions and rules to match clinical standards and ensure accurate analysis I shared both the current python code that we have in the game logic javascript as well Probably the javascript needs some adjustment Considering we added more parameters to the mix Can you review the whole code? and Explain why potentially we're getting this error The error message you're encountering error in analyze underscore waveform pr underscore interval indicates that when the fuzzy underscore logic underscore analysis function is called It expects an input for pr underscore interval, which is not being provided This is because the process underscore data function calculates the intervals, but does not separate them into pr underscore interval and rt underscore interval, which are required by the fuzzy logic system you've set up Here is a step-by-step review to address the issue Ensure that process underscore data actually calculates and returns pr underscore interval and rt underscore interval Add these intervals to the process underscore data underscore converted dictionary before passing it to fuzzy underscore logic underscore analysis Update the fuzzy underscore logic underscore analysis function to use these new intervals as inputs to the fuzzy system For the javascript part, you'll need to update the function display analysis result to include elements in your html to display the new pr underscore interval and rt underscore interval If they're part of the response data If they're not meant to be displayed with a use for calculations, ensure that the server response includes these values and they're passed correctly within the analyze waveform function Here's how you might adjust the python code for the fuzzy logic to handle these intervals Remember to adjust the actual calculation of pr underscore interval and rt underscore interval according to your data and how these intervals are defined in the context of your application The above code assumes that you have already calculated these values and added them to the processed underscore data dictionary If you haven't you need to implement that calculation based on the detected peaks in the ecg waveform data Yeah, we're getting a bit confused now. Yeah, the more prompt We're doing That less uh Bank for the bug We are getting there's something wrong now You can actually get the key tab co-pilot to do this instead Might use the workspace function because we don't actually know Where do we need to make the change Essentially, we added the more parameters more features to look at right so in processed data Sometimes it provides these links that are very helpful So I don't have to search What a code So we're calculating the intervals here somewhere Yes, and we're not We were not doing this correctly This is still not correct, but this is But uh, yeah get rid of the print statement. We will display it on the front page eventually So we'll need to change the html code as well I'll share it with you In a second Should be just called NP data Don't need that We just update What's updating it should be looking at the previous code for any changes we made No, it's not doing that As well get print interval Sorry PR interval Yes, that's we want an RT interval So this is correct and we Returning all that so that's fine So in calculate intervals It's not a hypothetical function. It's an actual function clear clear Doesn't want to clear So we adding them to the dictionary before passing on do the same thing again with a workspace function Update the fuzzy logic analysis function to use these new intervals As inputs to the fuzzy system, let's see it can find the relevant code We'll give GPT for a bit of a break just so we also don't hit the 40 messages per three hour limit That's still searching for stuff. We'll ask it eventually to give an overview for what we Have so far. It's getting stuck. Can you get it to work twice request time out what? so we Server error This one is not Do anything Fuzzy logic analysis Where the function is we can do that to select the whole code. No, we cannot We're not doing the calculation in this function Have this funny default rule that I thought we could read off. We're not actually No, we are using it So we have those six rules a default rule And rule for abnormal intervals So essentially if they're too short or too long the abnormality of the signal is highly likely This again still getting Error Calculate out Calculate intervals should take one position argument, but two were given. That's not good I think this might be something for A copilot to sort out Because we don't know where it is in the code. We just Use the workspace function. So it tries to find it itself I mean, yeah gpt4 is so much better with these things Or pretty much anything Okay, and calculate intervals We have the It's not in calculate intervals You mean this one? No, this is just initializing an array I wanted to when oops An interval Type, oh, it's okay We're not using interval type Okay, that should be fine Now we actually need to use the interval type Interval type is not being used I think we need to rewrite the whole thing returning intervals here now it's doing And the interval between r and d wave and p and r wave Instead of r r Which we don't have because we're looking at the each pq rst A complex individually So this should be better Still getting an error Pop it into a gpt4 If I select the whole code it might tell me that the code is too long No, it's dealt with 500 lines In analyze waveform now it's not getting the links. It's pretty annoying So we have the analyze waveform It actually did this for me It's only taking one line of code. That's not good. Yeah, I need to make sure that the PR Interval is in the json response And it's not And githubcopa does not correct that Yeah, interval should be there At the interval should be there It responds data And this one's a bit odd Yeah, now we're having another problem Every time you fix something you break something else, don't you? Yeah, I'm not entirely sure how to prompt a core pilot in terms of giving it the code what code does it need comparing it into converting the There's something in the dictionary format Oops What's Being written here Oops Yeah, I think it's a job for a gpt and we will Be finishing up soon and we'll be asking you to summarize the whole thing. Anyway Okay, I'll be sharing the whole code that we currently have For the python flask application that does the fuzzy logic analysis We also get this error Maybe you could Quickly sort it for us Hopefully it's nothing to do the JavaScript. No, it shouldn't be So I'll give the entire code and they could you also provide a summary for the whole thing And the changes that we have made today They should be the the previous code should be still commented out In the script If you wish to be funny or something make a general comments Suggestions They go for it It might be thinking for a while Clear Your code shows a good approach to processing ECG waveform data and analyzing it using fuzzy logic However, the area you're encountering seems to be related to how data is handled in the fuzzy underscore logic underscore analysis function and potentially how intervals are calculated and passed Let's break it down and provide some suggestions for improvement error message less than not supported between instances of float and dig this This error typically occurs when a comparison operation is performed between incompatible types In your case, it might be happening in the fuzzy logic analysis where a dictionary is being compared with the float or when processing the intervals Ensure that the values passed the fuzzy logic system are numerical floats or ints and not dictionaries or other data structures The intervals are initialized, but seem to not be populated correctly This could be due to the logic in calculate underscore intervals not functioning as expected Calculating intervals in In the calculate underscore intervals function ensure that the peaks p r t are correctly identified and the interval calculation logic is correctly implemented For instance, if you're calculating pr intervals, you need to make sure both p and r peaks are correctly identified and their indices are used to calculate intervals When passing pr underscore interval and r t underscore interval data to fuzzy underscore logic underscore analysis, ensure these are numerical values representing the intervals You might need to process the intervals dictionary to extract meaningful numerical data like average interval length maximum minimum etc Before passing it to the fuzzy logic analysis In the fuzzy underscore logic underscore analysis function ensure that the data you're inputting into the fuzzy system like pr underscore interval Rt underscore interval amplitude etc are in the correct format and range is expected by your fuzzy variable definitions debugging tips Add print statements or use a debugger to check the values of intervals and other parameters before they are passed to the fuzzy logic system This will help you identify where the mismatch or error is occurring improving comments and documentation Adding more descriptive comments can help maintain clarity, especially in complex sections like the fuzzy logic analysis This will make the code more maintainable and understandable to others or even to yourself in the future JavaScript integration As long as the python back end is handling the data correctly, the javascript front end should work fine Just make sure that the front end is prepared to handle and display any new data sent from the back end Remember, debugging complex systems often involves checking each part of the system separately to ensure they function as intended before integrating them This modular approach can help isolate and fix issues more efficiently I'm not sure how much progress we made today currently The application is not running properly The robot is not generating any output because we're getting a silly error And we summarize the whole application so far. Give it a broader context If you feel like being funny go for it But not too funny Definitely do not use any emojis now every time I say this it's actually picking up on the actual word and starts It will start to actually generate emojis Give a general context for the application how it might be useful or not We already have The game published on our website But this one will obviously provide extra features Where you play against the machine All right, let's step back and look at the big picture of your application with a touch of light-heartedness But not too much to throw us off course Imagine this you've got a game not just any game but one where humans and machines face off in the grand arena of ecg waveform analysis Picture it as a whose line is it anyway? But for ecg waveforms where the points do matter Players likely healthcare professionals are enthusiasts get to test their skills and identifying abnormalities in ecg waveforms It's like playing a medical version of wears Waldo But instead of Waldo you're looking for sneaky little changes in those squiggly lines Here's where your code steps in flexing its fuzzy logic muscles It's like having a robot judge in a talent show but instead of judging singing it's judging the peaks and valleys of heartbeats The machine uses sophisticated algorithms to analyze these waveforms Considering factors like peak sharpness interval lengths and amplitudes. Basically, it's looking for the heartbeats rhythm and style Players are presented with a waveform and have to decide whether it's normal or abnormal Each decision is a gamble like choosing door number one or two in a game show but with more medical credibility at stake Meanwhile the machine your python back end does its own analysis It's like having Sherlock Holmes, but instead of solving crimes. He's deducing heart conditions The machine's verdict is based on fuzzy logic, which is a fancy way of saying it makes decisions in a very human like somewhat uncertain way It's not just about zeros and ones. It's about maybe this peak is too sharp or perhaps this interval is too long Your application is not just a simple game It's an educational tool a training simulator and a way to introduce people to the complexities of ecg interpretation It's like combining a game of chess a medical seminar and a detective novel all into one You've got peak detection interval calculations and amplitude analysis It's like the machine is putting on its detective hat and magnifying glass to scrutinize every heartbeat The integration of fuzzy logic adds a layer of sophistication like adding a plot twist to a mystery novel The javascript front end makes it interactive and engaging because what's the point of having a cool game if it's not fun to play Dealing with errors and making sure the data passed around is in the right format It's like making sure all the actors in a play know their lines and cues Your application is a bridge between gaming and medical education turning the daunting task of ecg analysis into an interactive learning experience It's like if Grey's Anatomy met who wants to be a millionaire equal parts educational thrilling and potentially life saving So while there might be some hiccups along the way like our current era situation Remember every great invention had its share of tuning Once this is all ironed out, you're not just launching a game. You're launching a new way to learn engage and possibly save lives No pressure right winking face