> On 3 Des, 21:09, Randy Yates <ya...@ieee.org> wrote:
>> Randy Yates <ya...@ieee.org> writes:
>> > Rune Allnor <all...@tele.ntnu.no> writes:
>>
>> >> On 3 Des, 20:38, Randy Yates <ya...@ieee.org> wrote:
>> >>> Rune Allnor <all...@tele.ntnu.no> writes:
>> >>> > On 3 Des, 19:56, Randy Yates <ya...@ieee.org> wrote:
>> >>> >> John O'Flaherty <quias...@yeeha.com> writes:
>> >>> >> > One aspect is that heart rate (and maybe respiration rate) isn't
>> >>> >> > really periodic*. Separating the signals by the spectra of the
>> >>> >> > impulses (for heart rate, at least), or the fact that heart sound is
>> >>> >> > double (lub-dub), and finding time intervals between beats would give
>> >>> >> > a series of instantaneous heart rates, which could be averaged
>> >>> >> > appropriately.
>>
>> >>> >> Hi John,
>>
>> >>> >> True it's not strictly periodic. But I was hoping it's close
>> >>> >> enough... and that there was a more robust method than bone-headed peak
>> >>> >> detection. Where are you going to set the threshold? This is an
>> >>> >> algorithm that has to run unattended on a platform over multiple
>> >>> >> subjects, multiple signal strength scenarios, multiple SNR scenarios,
>> >>> >> etc.
>>
>> >>> > Do you have an example data set you can post?
>>
>> >>> Hi Rune,
>>
>> >>> Sure - try these:
>>
>> >>> �http://www.digitalsignallabs.com/signals
>>
>> >> I get a "you don't have access" error.
>>
>> > Sorry - try again.
>>
>> Grrr. Try this instead:
>>
>> �http://galois.digitalsignallabs.com/signals
>
> I got the data.
>
> I looked at the left_clavicle_mix1_amplified_orig.wav file,
> and it seems that both the signals occupy the same frequency
> band, 10-500 Hz.
>
> I can see what I believe are the heartbeats in the time
> domain data, but there is no way I can extract them by
> means of simple filtering.
>
> As far as I can tell, you have two options:
>
> 1) Get a reference recording of respitory only, make
> a Wiener filter for it, try and detect the heartbeats
> in the prediction error signal. (Maybe an adaptive
> filter works too; I don't know.)
> 2) Look for the spike train in the cepstrum.
>
> Both approaches will take lots of efforts (more than I
> can do just like that) and either may or may not work.
I'm glad you said that - I couldn't see a way to do
it right off either.
These people have what looks like the most promising method:
@inproceedings{hult,
author = "P. Hult and T. Fjallbrant and S. Dahle and P. Danielsson and P. Ask",
title = "{A method for respiration monitoring by the use of a bioacoustic signal}",
year = "2000",
booktitle = "{IEE Conf. Publ. No. 476}",
month = "September",
organization = "First International Conference on Advances in Medical Signal and Information Processing (IEEE)"}
They propose the use of a "dual tracking loop" where the heart beat is
modeled in one loop and subtracted from the other, and vice-versa for
the respiration signal. I'd call this method a joint source separation /
parameter estimator.
--Randy
--
% Randy Yates % "My Shangri-la has gone away, fading like
%% Fuquay-Varina, NC % the Beatles on 'Hey Jude'"
%%% 919-577-9882 %
%%%% <yates@ieee.org> % 'Shangri-La', *A New World Record*, ELO
http://www.digitalsignallabs.com
Reply by Jerry Avins●December 3, 20082008-12-03
John O'Flaherty wrote:
> On Wed, 03 Dec 2008 07:41:40 -0500, Randy Yates <yates@ieee.org>
> wrote:
>
>> Andor <andor.bariska@gmail.com> writes:
>>
>>> On 3 Dez., 12:45, Rune Allnor <all...@tele.ntnu.no> wrote:
>>>> On 3 Des, 12:23, Andor <andor.bari...@gmail.com> wrote:
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>> On 3 Dez., 11:04, Rune Allnor <all...@tele.ntnu.no> wrote:
>>>>>> On 3 Des, 09:45, Andor <andor.bari...@gmail.com> wrote:
>>>>>>> Randy Yates wrote:
>>>>>>>> It seems that the MUSIC algorithm is for estimation of sinusoids. Is
>>>>>>>> there an adaptation or other similar algorithm that can be applied to
>>>>>>>> estimate the fundamental frequencies of a mixture of periodic signals?
>>>>>>> Hello Randy
>>>>>>> In the presence of noise and with only finitely many samples of the
>>>>>>> signal, I don't think your task is solvable, unless you can supply
>>>>>>> some constraints.
>>>>>>> you need very many samples (multiple periods) to determine the period.
>>>>>> Wrong. MUSIC can do that in very few samples, depending
>>>>>> on the SNR.
>>>>> No, what I said is correct (and you are saying the same thing): in the
>>>>> presence of noise, the number of samples required for determining the
>>>>> frequencies of the summands depends on the width of the confidence
>>>>> intervals and the SNR. In the examples I gave and that you snipped it
>>>>> is clear why there are many samples required.
>>>> Sorry, I axed your first post too badly: While you are
>>>> right for general (quasi) periodic signals, you chose
>>>> an example that doesn't does not support your claim:
>>>> The sinusoidal is the one quasi-periodic signal where the
>>>> period can actually be determined with just a few samples.
>>> You are forgetting the noise, Rune. Any noise, however small, will not
>>> allow to determine the frequencies of two sinusoids accurate enough
>>> (with finitely many samples) to exclude the possiblity that there is
>>> no fundamental period.
>> I see your point, Andor.
>>
>> Actually, what I'm trying to figure out how to do (as an academic
>> exercise at this point rather than a paying job) is estimate heart rate
>> R_H and respiratory rate R_R from a single microphone signal containing
>> both.
>>
>>> This is why I asked Randy if he could supply constraints. If we knew
>>> that the frequencies of the sinusoids were selected from a finite set
>>> of possible frequencies (eg DTMF tones), then, given some frequency
>>> estimation method (MUSIC or any other) and the SNR, we can supply
>>> bounds on the number of samples required to determine the fundamental
>>> frequency with 1-eps chance for error (the value of eps will give a
>>> lower bound on the number of required samples).
>> Generally R_H > R_R, but not necessarily so. And there's nothing that
>> would prevent R_H = M * R_R, either.
>>
>> Sounds in general to me like MUSIC is a bad approach. Thank you both,
>> Rune/Andor, for your responses and guidance.
>
> One aspect is that heart rate (and maybe respiration rate) isn't
> really periodic*. Separating the signals by the spectra of the
> impulses (for heart rate, at least), or the fact that heart sound is
> double (lub-dub), and finding time intervals between beats would give
> a series of instantaneous heart rates, which could be averaged
> appropriately.
You will find that the only difference between the average of ten beat
intervals and (time-between-first-beat-and-eleventh-beat)/10 is less
accumulated round-off error in the second method.
Jerry
--
Engineering is the art of making what you want from things you can get.
�����������������������������������������������������������������������
Reply by Rune Allnor●December 3, 20082008-12-03
On 3 Des, 21:09, Randy Yates <ya...@ieee.org> wrote:
> Randy Yates <ya...@ieee.org> writes:
> > Rune Allnor <all...@tele.ntnu.no> writes:
>
> >> On 3 Des, 20:38, Randy Yates <ya...@ieee.org> wrote:
> >>> Rune Allnor <all...@tele.ntnu.no> writes:
> >>> > On 3 Des, 19:56, Randy Yates <ya...@ieee.org> wrote:
> >>> >> John O'Flaherty <quias...@yeeha.com> writes:
> >>> >> > One aspect is that heart rate (and maybe respiration rate) isn't
> >>> >> > really periodic*. Separating the signals by the spectra of the
> >>> >> > impulses (for heart rate, at least), or the fact that heart sound is
> >>> >> > double (lub-dub), and finding time intervals between beats would give
> >>> >> > a series of instantaneous heart rates, which could be averaged
> >>> >> > appropriately.
>
> >>> >> Hi John,
>
> >>> >> True it's not strictly periodic. But I was hoping it's close
> >>> >> enough... and that there was a more robust method than bone-headed peak
> >>> >> detection. Where are you going to set the threshold? This is an
> >>> >> algorithm that has to run unattended on a platform over multiple
> >>> >> subjects, multiple signal strength scenarios, multiple SNR scenarios,
> >>> >> etc.
>
> >>> > Do you have an example data set you can post?
>
> >>> Hi Rune,
>
> >>> Sure - try these:
>
> >>> �http://www.digitalsignallabs.com/signals
>
> >> I get a "you don't have access" error.
>
> > Sorry - try again.
>
> Grrr. Try this instead:
>
> �http://galois.digitalsignallabs.com/signals
I got the data.
I looked at the left_clavicle_mix1_amplified_orig.wav file,
and it seems that both the signals occupy the same frequency
band, 10-500 Hz.
I can see what I believe are the heartbeats in the time
domain data, but there is no way I can extract them by
means of simple filtering.
As far as I can tell, you have two options:
1) Get a reference recording of respitory only, make
a Wiener filter for it, try and detect the heartbeats
in the prediction error signal. (Maybe an adaptive
filter works too; I don't know.)
2) Look for the spike train in the cepstrum.
Both approaches will take lots of efforts (more than I
can do just like that) and either may or may not work.
Rune
Reply by Randy Yates●December 3, 20082008-12-03
Randy Yates <yates@ieee.org> writes:
> Rune Allnor <allnor@tele.ntnu.no> writes:
>
>> On 3 Des, 20:38, Randy Yates <ya...@ieee.org> wrote:
>>> Rune Allnor <all...@tele.ntnu.no> writes:
>>> > On 3 Des, 19:56, Randy Yates <ya...@ieee.org> wrote:
>>> >> John O'Flaherty <quias...@yeeha.com> writes:
>>> >> > One aspect is that heart rate (and maybe respiration rate) isn't
>>> >> > really periodic*. Separating the signals by the spectra of the
>>> >> > impulses (for heart rate, at least), or the fact that heart sound is
>>> >> > double (lub-dub), and finding time intervals between beats would give
>>> >> > a series of instantaneous heart rates, which could be averaged
>>> >> > appropriately.
>>>
>>> >> Hi John,
>>>
>>> >> True it's not strictly periodic. But I was hoping it's close
>>> >> enough... and that there was a more robust method than bone-headed peak
>>> >> detection. Where are you going to set the threshold? This is an
>>> >> algorithm that has to run unattended on a platform over multiple
>>> >> subjects, multiple signal strength scenarios, multiple SNR scenarios,
>>> >> etc.
>>>
>>> > Do you have an example data set you can post?
>>>
>>> Hi Rune,
>>>
>>> Sure - try these:
>>>
>>> �http://www.digitalsignallabs.com/signals
>>
>> I get a "you don't have access" error.
>
> Sorry - try again.
> On 3 Des, 20:38, Randy Yates <ya...@ieee.org> wrote:
>> Rune Allnor <all...@tele.ntnu.no> writes:
>> > On 3 Des, 19:56, Randy Yates <ya...@ieee.org> wrote:
>> >> John O'Flaherty <quias...@yeeha.com> writes:
>> >> > One aspect is that heart rate (and maybe respiration rate) isn't
>> >> > really periodic*. Separating the signals by the spectra of the
>> >> > impulses (for heart rate, at least), or the fact that heart sound is
>> >> > double (lub-dub), and finding time intervals between beats would give
>> >> > a series of instantaneous heart rates, which could be averaged
>> >> > appropriately.
>>
>> >> Hi John,
>>
>> >> True it's not strictly periodic. But I was hoping it's close
>> >> enough... and that there was a more robust method than bone-headed peak
>> >> detection. Where are you going to set the threshold? This is an
>> >> algorithm that has to run unattended on a platform over multiple
>> >> subjects, multiple signal strength scenarios, multiple SNR scenarios,
>> >> etc.
>>
>> > Do you have an example data set you can post?
>>
>> Hi Rune,
>>
>> Sure - try these:
>>
>> �http://www.digitalsignallabs.com/signals
>
> I get a "you don't have access" error.
Sorry - try again.
--
% Randy Yates % "The dreamer, the unwoken fool -
%% Fuquay-Varina, NC % in dreams, no pain will kiss the brow..."
%%% 919-577-9882 %
%%%% <yates@ieee.org> % 'Eldorado Overture', *Eldorado*, ELO
http://www.digitalsignallabs.com
Reply by Rune Allnor●December 3, 20082008-12-03
On 3 Des, 20:38, Randy Yates <ya...@ieee.org> wrote:
> Rune Allnor <all...@tele.ntnu.no> writes:
> > On 3 Des, 19:56, Randy Yates <ya...@ieee.org> wrote:
> >> John O'Flaherty <quias...@yeeha.com> writes:
> >> > One aspect is that heart rate (and maybe respiration rate) isn't
> >> > really periodic*. Separating the signals by the spectra of the
> >> > impulses (for heart rate, at least), or the fact that heart sound is
> >> > double (lub-dub), and finding time intervals between beats would give
> >> > a series of instantaneous heart rates, which could be averaged
> >> > appropriately.
>
> >> Hi John,
>
> >> True it's not strictly periodic. But I was hoping it's close
> >> enough... and that there was a more robust method than bone-headed peak
> >> detection. Where are you going to set the threshold? This is an
> >> algorithm that has to run unattended on a platform over multiple
> >> subjects, multiple signal strength scenarios, multiple SNR scenarios,
> >> etc.
>
> > Do you have an example data set you can post?
>
> Hi Rune,
>
> Sure - try these:
>
> �http://www.digitalsignallabs.com/signals
I get a "you don't have access" error.
Rune
Reply by Randy Yates●December 3, 20082008-12-03
Randy Yates <yates@ieee.org> writes:
> Rune Allnor <allnor@tele.ntnu.no> writes:
>
>> On 3 Des, 19:56, Randy Yates <ya...@ieee.org> wrote:
>>> John O'Flaherty <quias...@yeeha.com> writes:
>>> > One aspect is that heart rate (and maybe respiration rate) isn't
>>> > really periodic*. Separating the signals by the spectra of the
>>> > impulses (for heart rate, at least), or the fact that heart sound is
>>> > double (lub-dub), and finding time intervals between beats would give
>>> > a series of instantaneous heart rates, which could be averaged
>>> > appropriately.
>>>
>>> Hi John,
>>>
>>> True it's not strictly periodic. But I was hoping it's close
>>> enough... and that there was a more robust method than bone-headed peak
>>> detection. Where are you going to set the threshold? This is an
>>> algorithm that has to run unattended on a platform over multiple
>>> subjects, multiple signal strength scenarios, multiple SNR scenarios,
>>> etc.
>>
>> Do you have an example data set you can post?
>
> Hi Rune,
>
> Sure - try these:
>
> http://www.digitalsignallabs.com/signals
>
> Thanks.
>
> --Randy
PS: Give it a few more minutes - files are still transferring.
--
% Randy Yates % "How's life on earth?
%% Fuquay-Varina, NC % ... What is it worth?"
%%% 919-577-9882 % 'Mission (A World Record)',
%%%% <yates@ieee.org> % *A New World Record*, ELO
http://www.digitalsignallabs.com
Reply by Randy Yates●December 3, 20082008-12-03
Rune Allnor <allnor@tele.ntnu.no> writes:
> On 3 Des, 19:56, Randy Yates <ya...@ieee.org> wrote:
>> John O'Flaherty <quias...@yeeha.com> writes:
>> > One aspect is that heart rate (and maybe respiration rate) isn't
>> > really periodic*. Separating the signals by the spectra of the
>> > impulses (for heart rate, at least), or the fact that heart sound is
>> > double (lub-dub), and finding time intervals between beats would give
>> > a series of instantaneous heart rates, which could be averaged
>> > appropriately.
>>
>> Hi John,
>>
>> True it's not strictly periodic. But I was hoping it's close
>> enough... and that there was a more robust method than bone-headed peak
>> detection. Where are you going to set the threshold? This is an
>> algorithm that has to run unattended on a platform over multiple
>> subjects, multiple signal strength scenarios, multiple SNR scenarios,
>> etc.
>
> Do you have an example data set you can post?
Hi Rune,
Sure - try these:
http://www.digitalsignallabs.com/signals
Thanks.
--Randy
--
% Randy Yates % "And all that I can do
%% Fuquay-Varina, NC % is say I'm sorry,
%%% 919-577-9882 % that's the way it goes..."
%%%% <yates@ieee.org> % Getting To The Point', *Balance of Power*, ELO
http://www.digitalsignallabs.com
Reply by John O'Flaherty●December 3, 20082008-12-03
On Wed, 03 Dec 2008 13:56:55 -0500, Randy Yates <yates@ieee.org>
wrote:
>John O'Flaherty <quiasmox@yeeha.com> writes:
>
>> One aspect is that heart rate (and maybe respiration rate) isn't
>> really periodic*. Separating the signals by the spectra of the
>> impulses (for heart rate, at least), or the fact that heart sound is
>> double (lub-dub), and finding time intervals between beats would give
>> a series of instantaneous heart rates, which could be averaged
>> appropriately.
>
>Hi John,
>
>True it's not strictly periodic. But I was hoping it's close
>enough... and that there was a more robust method than bone-headed peak
>detection. Where are you going to set the threshold? This is an
>algorithm that has to run unattended on a platform over multiple
>subjects, multiple signal strength scenarios, multiple SNR scenarios,
>etc.
ECG and plethysmograph heartrate detection systems face all those
problems; there's AGC for threshold control.
At any rate, googling around idly, I found this, using the "blind
source" thingy you mentioned up-thread, for separation of fetal from
mother's heartbeat in ECGs. Maybe it could be adapted to microphone
signals and heart vs. respiration-
http://www.comp.nus.edu.sg/~changec/publications/P0861.pdf
--
John
Reply by Rune Allnor●December 3, 20082008-12-03
On 3 Des, 19:56, Randy Yates <ya...@ieee.org> wrote:
> John O'Flaherty <quias...@yeeha.com> writes:
> > One aspect is that heart rate (and maybe respiration rate) isn't
> > really periodic*. Separating the signals by the spectra of the
> > impulses (for heart rate, at least), or the fact that heart sound is
> > double (lub-dub), and finding time intervals between beats would give
> > a series of instantaneous heart rates, which could be averaged
> > appropriately.
>
> Hi John,
>
> True it's not strictly periodic. But I was hoping it's close
> enough... and that there was a more robust method than bone-headed peak
> detection. Where are you going to set the threshold? This is an
> algorithm that has to run unattended on a platform over multiple
> subjects, multiple signal strength scenarios, multiple SNR scenarios,
> etc.
Do you have an example data set you can post?
Rune