Thank you Sergey, > 1) Are you trying to predict or detect anomalies? I want to detect anomalies, not predict.
> 2) How are you encoding ECG data? I use Adaptive Scalar Encoder. Here is model params, https://github.com/iizukak/ecg-htm/blob/master/model_params/model_params.py And sample data (It’s big CSV File) https://github.com/iizukak/ecg-htm/blob/master/data/normal.csv > Also, make sure to resetSequenceStates every time you start feeding in data > from > a new person. OK, I keep in mind. > Finally, you might want to shuffle the data Shuffling the data is sound good. I’ll try if person1, person2, person3, … one after another of learning data dose not make enough good model. I think I don’t have a trouble with extracting data, but I'll read the paper you suggested. Hope this answers your question. Thanks a lot! 2015-10-22 18:18 GMT+09:00 Sergey Alexashenko <[email protected]>: > Actually, I can write out the scenarios here. > > NuPIC should definitely be able to learn different people's heartbeats in > one model. You have to give it plenty of data to learn on. Also, make sure > to resetSequenceStates every time you start feeding in data from a new > person. Finally, you might want to shuffle the data so that you don't feed > it person 1, then person 2, then person 3, but rather a mixture of all the > data to reduce bias towards the latest people (but I don't think that this > is necessary to be honest). > > There is, however, the issue of encoding. I'm assuming that you are using a > scalar encoder produced by swarming. That's fine, that's a quick approach > and it might work (in fact I would bet that it will produce usable results - > be mindful of swarming on a data set including different people's data, > though!). > > However, if you think about the data type - ECG data, unlike, say, EEG data, > consists of almost perfectly discrete steps (heartbeats) which could be > matched to NuPIC timesteps very well. If you run through the trouble of > extracting features from your data (there is ample literature on how to do > it - see [1] for example), and creating encoders for all the > intervals/amplitudes, I think that NuPIC would do a marvelous job. Note that > this approach condenses the time interval per step to one per heartbeat and, > thus, is not going to work if you are trying to do super-rapid detection or > prediction (on a time scale shorter than one heartbeat). It is also more > time-consuming for you - once again, swarming could work well enough. > > Hope this helps, > > Sergey > > [1] http://arxiv.org/pdf/1005.0957.pdf > > > > On Thu, Oct 22, 2015 at 1:58 AM, Sergey Alexashenko > <[email protected]> wrote: >> >> Hello Kentaro, >> >> I think that NuPIC can definitely work with ECG data, but I need a little >> more information about your project to make any helpful suggestions. Two >> questions: >> >> 1) Are you trying to predict or detect anomalies? You use both terms, but >> they involve somewhat different mechanisms. >> >> 2) How are you encoding ECG data? >> >> Best, >> >> Sergey >> >> >> On Wed, Oct 21, 2015 at 10:07 PM, Kentaro Iizuka >> <[email protected]> wrote: >>> >>> Hello NuPIC. >>> >>> Thank you Matt for post. >>> >>> Here is my question detail. (It is same as gitter post) >>> https://gist.github.com/iizukak/72526863d3f504f2ff5e >>> >>> I hope somebody have good idea for that. >>> >>> Thank you! >>> >>> >>> 2015-10-22 13:29 GMT+09:00 Matthew Taylor <[email protected]>: >>> > Hello NuPIC, >>> > >>> > Check this out: >>> > https://gitter.im/numenta/htm-challenge/archives/2015/10/21 >>> > >>> > Watch the ECG anomaly in the video: >>> > https://youtu.be/5KdwV-trMhE?t=1m41s >>> > >>> > He has an interesting question about how to train a model on a healthy >>> > heartbeat, and it is expressed well with pictures in the link above. He >>> > wants to train a model with the ECG history of more than one person to >>> > get a >>> > representation of a "healthy heartbeat". The problem is that every >>> > person's >>> > heartbeat is a little different. Is it feasible to train a model on >>> > multiple >>> > heartbeats in sequence? I'm not sure if it will work, but maybe someone >>> > has >>> > a better idea? >>> > >>> > Solving this problem would help in a lot of different signal analysis >>> > applications of HTM... >>> > >>> > --------- >>> > Matt Taylor >>> > OS Community Flag-Bearer >>> > Numenta >>> >>> >>> >>> -- >>> Kentaro Iizuka<[email protected]> >>> >>> Github >>> https://github.com/iizukak/ >>> >>> Facebook >>> https://www.facebook.com/kentaroiizuka >>> >> > -- Kentaro Iizuka<[email protected]> Github https://github.com/iizukak/ Facebook https://www.facebook.com/kentaroiizuka
