Re: [time-nuts] simulation of interconnected clocks
On Sat, 30 Nov 2013 06:31:01 -0800 Jim Lux wrote: > Recently, I've been looking at the variations of some human clocks which > are millenia old: Galileo used his pulse as a timer for his famous "roll > balls down a ramp" experimenet". I thought that some time-nuts might be > interested in working with a clock that's a bit different than one > depending on atomic vibrations, or motion within a crystal lattice. I don't know whether this is of any help to you, but some time ago i stumbled about some old lectures by Charles Peskin on the heart and to its chaotic self-synchronization [1]. If you are interested in the synchronisation phenomena in biological oscillators, i can recommend you [2]. Also a good read is [3] which gives a quite lengthy analysis on Kuramotos model [4]. Also a nice review paper is [5], which starts from Kuramoto and explains the current unsolved problems with coupled oscillators and their mathematical description. Attila Kinali [1] "Mathematical aspects of heart physiology", by Peskin, 1975 http://math.nyu.edu/faculty/peskin/heartnotes/index.html [2] "Synchronization of Pulse-Coupled Biological Oscillators" by Mirollo and Strogatz, 1990 http://math.bd.psu.edu/faculty/stevens/MATH497K/Papers/Syncrhonization.pdf [3] "The Kuramoto model: A simple paradigm for synchronization phenomena", by Acbron, Bonilla, Vincente, Ritort, Spigler, 2005 http://rmp.aps.org/abstract/RMP/v77/i1/p137_1 [4] "Self-entrainment of a population of coupled non-linear oscillators" by Kuramoto, 1975 http://www.springerlink.com/content/71073361941277h8/ [5] "From Kuramoto to Crawford: exploring the onset of synchronization in populations of coupled oscillators", by Strogatz, 2000 http://www.sciencedirect.com/science/article/pii/S016727890944 -- 1.) Write everything down. 2.) Reduce to the essential. 3.) Stop and question. -- The Habits of Highly Boring People, Chris Sauve ___ time-nuts mailing list -- time-nuts@febo.com To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.
Re: [time-nuts] simulation of interconnected clocks
So, are we any closer to finding the body oscillator that lets us wake up just before the alarm goes off? Or could it be that we are awakened by the alarm but recognition of it is delayed? Bill Hawkins (currently dealing with a low, irregular heartbeat) ___ time-nuts mailing list -- time-nuts@febo.com To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.
Re: [time-nuts] simulation of interconnected clocks
On 12/01/2013 01:36 PM, paul.alfille wrote: > Heart rate depends on a feedback circuit through the autonomic nervous > system. Microvascular disease (diabetes), denervation (heart transplant), and > drugs can all alter the variabilility. > > There actaully is a large literatuee in fetal heart rate variability used to > diagnoses fetal distress and precipirate energent cesarian section. ___ time-nuts mailing list -- time-nuts@febo.com To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.
Re: [time-nuts] simulation of interconnected clocks
Heart rate depends on a feedback circuit through the autonomic nervous system. Microvascular disease (diabetes), denervation (heart transplant), and drugs can all alter the variabilility. There actaully is a large literatuee in fetal heart rate variability used to diagnoses fetal distress and precipirate energent cesarian section. Sent via the Samsung Galaxy S™ III, an AT&T 4G LTE smartphone Original message From: Jim Lux Date: 11/30/2013 6:41 PM (GMT-05:00) To: time-nuts@febo.com Subject: Re: [time-nuts] simulation of interconnected clocks On 11/30/13 2:15 PM, Tom Van Baak wrote: > Jim, > > Could you just replay real data instead of trying to generate > simulated data? There's plenty of storage with Arduino or SD card > shields. > > Attached is frequency and ADEV of my heart beat for 10 hours. You > could do the same. In this case the flicker floor is just under 1e-1 > from 10s to 10ks. > > One could do that. Or in a limited sense, have a shorter table which you play back repetitively. If you did some processing on your heartbeat data to remove the sinusoidal modulation from respiration, you might find the ADEV/phase noise is less. That's something I'm looking into. In my case, I need to be able to generate multiple different realistic targets. I could probably record a bunch of sequences and then play back different pieces of them. or use one person and have them breathe at different rates and depths. But an algorithmic approach is interesting. And even more interesting is being able to generate a particular pattern (using the model), and see if you can retrieve the model parameters using the device. Here's where I'm using it: http://www.jpl.nasa.gov/news/news.php?release=2013-281 http://www.jpl.nasa.gov/news/news.php?release=2013-290 http://www.jpl.nasa.gov/video/?id=1252 We use the model parameters to distinguish targets from one another (and targets from bystanders and the operator); and also to separate humans from other targets (oddly enough, that slowly rotating fan, or swinging grandfather clock pendulum have much lower 1/f noise than your heart). One finds as you delve into the physiology literature that they have exceedingly different ways to measure, describe, and model things than engineers do. In some cases it's because they're working from the biological structures that make it happen. In others, it's just because historically it's been described differently: often with reference to particular methods of recording the signal. It's kind of like how the Richter scale is in terms of the height of the trace in mm on a particular kind of seismograph. Someone goes out and records ECG data and they write the paper and say "data was recorded using a Grass model X with the filter set at position 3", and since everyone in that field of research uses the same machines, they all know how it was recorded, and can duplicate it if needed. The signal processing details of the Grass Model X with filter set at Position 3 might be left as an exercise for the reader (or a letter to Al Grass at the Grass Instrument Company). The same thing happens in the nuclear instrumentation area, where everything is in terms of pulses and time domain processing, and you refer to a particular model of Ortec pre-amp, feeding some other model discriminator, finally feeding your multichannel analyzer (which name confused me, since it has only one input channel). The other thing is that a until recently, computers weren't used to analyze the data, so the analytical methods tend to favor those that are paper, pencil, and slide rule tractable. There's a lot of log/log plots with visually placed curve fits, with not a huge number of test subjects (20 subjects would be a lot in most of these papers). Finally, there might be a historical reason why decent math models aren't popular: The grand man of physiology was Carl Ludwig in Leipzig: he had hundreds of postgraduate students (Pavlov was one), but apparently "he had little use for mathematical treatment of biological problems". Ludwig wrote the 1847 paper everyone cites as the beginning: "Beitraege zur Kenntniss des Einflusses der Respirations bewegungen auf den Blutlauf im Aortensysteme". But hey, if your supervisor says math models aren't important, you're sure not going to argue with him, and someone of distinctly math modeling bent would likely find another place to study or field of study. So Ludwig casts a long shadow on published research, probably for 2 or 3 generations. Thanks to the miracle of the internet and big efforts to scan stuff this kind of thing is readily available. It's come a long ways since I had to hunt down a copy of Paschen's paper/thesis on high voltage breakdown as an actual printed copy and then ph
Re: [time-nuts] simulation of interconnected clocks
> Neat. What did you use to collect the raw data? Hi Hal, The pulse data came from a sports chest-strap heart rate monitor, made by Polar. See the 10^-1 page of the PDF at http://leapsecond.com/ten/ There are two data formats, non-coded (T34) and coded (T31). More info: https://www.sparkfun.com/products/8661 https://www.sparkfun.com/datasheets/Wireless/General/RMCM01.pdf http://danjuliodesigns.com/sparkfun/sparkfun.html http://danjuliodesigns.com/sparkfun/hrmi_assets/hrmi.pdf https://www.adafruit.com/products/1077 http://learn.parallax.com/KickStart/28048 /tvb ___ time-nuts mailing list -- time-nuts@febo.com To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.
Re: [time-nuts] simulation of interconnected clocks
On 11/30/13 5:33 PM, Hal Murray wrote: t...@leapsecond.com said: Attached is frequency and ADEV of my heart beat for 10 hours. Neat. What did you use to collect the raw data? There's a few Arduino/Sparkfun/Adafruit widgets out there that receive the signals from off the shelf Polar heart rate monitors. I had a grad student last summer build a box to log heart beats using photoplethysmography (photocell sensing blood flow in fingertip). He used a widget from one of the dealers that has the analog circuitry to buffer the optical sensor. If I were collecting it on a long term (many hours) basis, I'd go with ECG based approaches (which is what the Polar sensors use), but with stick on electrodes. Motion artifacts are a big problem. Holter is the big name in commercial ECG loggers, but they're real pricey (being FDA approved medical devices and all). Microwave monitoring (radar) is a good "standoff" way to measure heartbeats, but only works in fixed locations (e.g. I can set it up in my office, in my car, or a room at home, and collect data, but it doesn't work well when you're out walking around). If you get one of those microwave Doppler door sensors at 10.5 or 24 GHz, you can get a good heartbeat signal from them. ___ time-nuts mailing list -- time-nuts@febo.com To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.
Re: [time-nuts] simulation of interconnected clocks
t...@leapsecond.com said: > Attached is frequency and ADEV of my heart beat for 10 hours. Neat. What did you use to collect the raw data? -- These are my opinions. I hate spam. ___ time-nuts mailing list -- time-nuts@febo.com To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.
Re: [time-nuts] simulation of interconnected clocks
On 11/30/13 2:15 PM, Tom Van Baak wrote: Jim, Could you just replay real data instead of trying to generate simulated data? There's plenty of storage with Arduino or SD card shields. Attached is frequency and ADEV of my heart beat for 10 hours. You could do the same. In this case the flicker floor is just under 1e-1 from 10s to 10ks. The flat zero slope adev shows the basic 1/f characteristic reported in the literature. There's been quite a few people who have hooked up monitors to people for 24 hours or more and found that the power spectrum of heart rate follows 1/f from about 0.3 Hz down 4 decades at least. I'm not sure what the ADEV/Power spectrum of respiration rate would be, since it's mostly determined by what the person is doing. Power spectrum (averaged over a long time) would probably be more a histogram of "level of physical activity". ___ time-nuts mailing list -- time-nuts@febo.com To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.
Re: [time-nuts] simulation of interconnected clocks
On 11/30/13 2:15 PM, Tom Van Baak wrote: Jim, Could you just replay real data instead of trying to generate simulated data? There's plenty of storage with Arduino or SD card shields. Attached is frequency and ADEV of my heart beat for 10 hours. You could do the same. In this case the flicker floor is just under 1e-1 from 10s to 10ks. One could do that. Or in a limited sense, have a shorter table which you play back repetitively. If you did some processing on your heartbeat data to remove the sinusoidal modulation from respiration, you might find the ADEV/phase noise is less. That's something I'm looking into. In my case, I need to be able to generate multiple different realistic targets. I could probably record a bunch of sequences and then play back different pieces of them. or use one person and have them breathe at different rates and depths. But an algorithmic approach is interesting. And even more interesting is being able to generate a particular pattern (using the model), and see if you can retrieve the model parameters using the device. Here's where I'm using it: http://www.jpl.nasa.gov/news/news.php?release=2013-281 http://www.jpl.nasa.gov/news/news.php?release=2013-290 http://www.jpl.nasa.gov/video/?id=1252 We use the model parameters to distinguish targets from one another (and targets from bystanders and the operator); and also to separate humans from other targets (oddly enough, that slowly rotating fan, or swinging grandfather clock pendulum have much lower 1/f noise than your heart). One finds as you delve into the physiology literature that they have exceedingly different ways to measure, describe, and model things than engineers do. In some cases it's because they're working from the biological structures that make it happen. In others, it's just because historically it's been described differently: often with reference to particular methods of recording the signal. It's kind of like how the Richter scale is in terms of the height of the trace in mm on a particular kind of seismograph. Someone goes out and records ECG data and they write the paper and say "data was recorded using a Grass model X with the filter set at position 3", and since everyone in that field of research uses the same machines, they all know how it was recorded, and can duplicate it if needed. The signal processing details of the Grass Model X with filter set at Position 3 might be left as an exercise for the reader (or a letter to Al Grass at the Grass Instrument Company). The same thing happens in the nuclear instrumentation area, where everything is in terms of pulses and time domain processing, and you refer to a particular model of Ortec pre-amp, feeding some other model discriminator, finally feeding your multichannel analyzer (which name confused me, since it has only one input channel). The other thing is that a until recently, computers weren't used to analyze the data, so the analytical methods tend to favor those that are paper, pencil, and slide rule tractable. There's a lot of log/log plots with visually placed curve fits, with not a huge number of test subjects (20 subjects would be a lot in most of these papers). Finally, there might be a historical reason why decent math models aren't popular: The grand man of physiology was Carl Ludwig in Leipzig: he had hundreds of postgraduate students (Pavlov was one), but apparently "he had little use for mathematical treatment of biological problems". Ludwig wrote the 1847 paper everyone cites as the beginning: "Beitraege zur Kenntniss des Einflusses der Respirations bewegungen auf den Blutlauf im Aortensysteme". But hey, if your supervisor says math models aren't important, you're sure not going to argue with him, and someone of distinctly math modeling bent would likely find another place to study or field of study. So Ludwig casts a long shadow on published research, probably for 2 or 3 generations. Thanks to the miracle of the internet and big efforts to scan stuff this kind of thing is readily available. It's come a long ways since I had to hunt down a copy of Paschen's paper/thesis on high voltage breakdown as an actual printed copy and then photocopy it. http://archive.org/stream/beitrgezurkenn00hein#page/n55/mode/2up has some examples of data collected later in the 19th century from dogs and cats. ___ time-nuts mailing list -- time-nuts@febo.com To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.