We have a big data challenge for a very worthy cause here. The Michael J. Fox foundation has\r\na lot of data and needs your help finding the meaning in it. You're encouraged to start early and ask questions... this isn't a task to take on with Excel the night before the deadline!
\r\nGood luck, and thank you in advance for participating!
", "messages": [ { "id": "20085", "postDate": "02/05/2013 22:45:38", "content": "We have a big data challenge for a very worthy cause here. The Michael J. Fox foundation has\r\na lot of data and needs your help finding the meaning in it. You're encouraged to start early and ask questions... this isn't a task to take on with Excel the night before the deadline!
\r\nGood luck, and thank you in advance for participating!
", "rawMarkdown": "", "votes": null }, { "id": "20131", "postDate": "02/07/2013 04:48:39", "content": "Thanks! Just checking out the data now. Wanted to confirm that the fields First Name and Last Name in UPDRS Part 1 Questionnaire 2 are meant to be posted?
\r\nBen
", "rawMarkdown": "", "votes": null }, { "id": "20132", "postDate": "02/07/2013 04:54:34", "content": "Thanks for catching that, BenM. That file was uploaded by MJFF but I doubt they intended for it to be there. I replaced the file with a version without the names. Let me know if you find anything else.
", "rawMarkdown": "", "votes": null }, { "id": "20152", "postDate": "02/07/2013 19:54:01", "content": "Hi Will,
\r\nIn the submissions page, What does 'upvote this submission' mean?
", "rawMarkdown": "", "votes": null }, { "id": "20153", "postDate": "02/07/2013 19:59:11", "content": "Good question. Here, it can be used for (a) sorting submissions or (b) a nod of appreciation to a fellow Kaggler for a job well done. The judging panel is free to ignore or incorporate upvotes as they see fit.
", "rawMarkdown": "", "votes": null }, { "id": "20154", "postDate": "02/07/2013 20:15:30", "content": "[quote=William Cukierski;20153]
\r\nGood question. Here, it can be used for (a) sorting submissions or (b) a nod of appreciation to a fellow Kaggler for a job well done. The judging panel is free to ignore or incorporate upvotes as they see fit.
\r\n[/quote]
\r\nNext question - in the rules it states
\r\nAccess to submitted print materials is only granted by the Michael J. Fox Foundation to the members of its judging panel.
\r\nI assume this means submissions are not viewable to fellow Kagglers to give this nod of appreciation.
", "rawMarkdown": "", "votes": null }, { "id": "20162", "postDate": "02/08/2013 03:13:25", "content": "Only 16 subjects. I'm already pessimistic about what can be accomplished with such a small sample size.
", "rawMarkdown": "", "votes": null }, { "id": "20163", "postDate": "02/08/2013 03:20:40", "content": "[quote=bittermellon;20162]
\r\nOnly 16 subjects. I'm already pessimistic about what can be accomplished with such a small sample size.
\r\n[/quote]
\r\nAppropriate username! :)
", "rawMarkdown": "", "votes": null }, { "id": "20191", "postDate": "02/08/2013 16:10:01", "content": "Hi from the MJFF!
\r\nAgree that power of analysis might be limited, given the small sample size. Still, we would like to see IF there are some smart ideas out there to use those data! If something is even indicative of a trend, a bigger project\r\n could then be developed.
", "rawMarkdown": "", "votes": null }, { "id": "20194", "postDate": "02/08/2013 17:29:47", "content": "[quote=Sali Mali;20154]
\r\nNext question - in the rules it states
\r\nAccess to submitted print materials is only granted by the Michael J. Fox Foundation to the members of its judging panel.
\r\nI assume this means submissions are not viewable to fellow Kagglers to give this nod of appreciation.
\r\n[/quote]
\r\nThanks for catching this. I spoke with the MJFF and this was a bit of legalese left over from a previous iteration of the contest rules. It has been removed from the rules.
", "rawMarkdown": "", "votes": null }, { "id": "20245", "postDate": "02/09/2013 20:33:45", "content": "How 'dirty' are the sample data? In the description you say there were compliance problems, technology malfunctions, etc. as is expected in early studies. Have these been removed?
\r\n", "rawMarkdown": "", "votes": null }, { "id": "20252", "postDate": "02/10/2013 01:16:35", "content": "
Is it accurate that Cherry did not do a 2nd questionnaire and also none of the control participants did any questionnaires? Thanks.
", "rawMarkdown": "", "votes": null }, { "id": "20254", "postDate": "02/10/2013 03:38:25", "content": "The study design mentions that the patients/ volunteers kept the phones in their pocket or wear them around their neck. Is there any record of this on a per-subject or per-charge-cycle basis?
\r\nAlso, i don't understand what is actually being recorded in "frequency motion energy" for the accelerometry. I understand the recording frequency is 1Hz or less. So how can there be spectral\r\n power of at frequencies of 1, 3 , 6 and 10Hz?
", "rawMarkdown": "", "votes": null }, { "id": "20291", "postDate": "02/11/2013 03:11:41", "content": "Just adding my two cents....
\r\nI did my PhD on a similiar topic; analyzing / segmeneting various subject subgroups using body sensor networks.
\r\nWe gathered a significant amount of accelerometry data.
\r\nAccelerometers are a combination of movement due to gravity, movement due to the body and noise with overlapping spectra. Low Pass / High Pass filters can seperate these components to some extent.
\r\nHowever, unless the location of the sensor is both known and fixed relative to the subjects plane (anterposterior etc) then these data are highly unrealiable. Furthermore, now knowing whether the sensor was in the pocket / chest and a small sample size bias\r\n makes this a very abstract problem.
\r\nPerhaps a more useful approach would be to affix a sensor to a known location (wrist, ankle, lower back near the COM) and calculate various spatio-temporal parameters (gait, balance etc).
\r\nWIth that said, cool project and hats off to the MJFF - very important and genuine.
\r\n", "rawMarkdown": "", "votes": null }, { "id": "20293", "postDate": "02/11/2013 03:42:43", "content": "", "rawMarkdown": "", "votes": null }, { "id": "20294", "postDate": "02/11/2013 03:44:13", "content": "
It seems Cherry is missing from the file. We will locate it and post it.
\r\n
\r\nYes, it is correct that none of the control participants filled out the questionnaire. The questionnaire is just for measuring UPDRS, so it was only applicable to the PD patients.
\r\n
Everyone except one of the participants (Peone) carried them in either a hip pocket or a shirt pocket.
\r\n
\r\nAs for the accelerometer question,this is a standard accelerometer that is in an Android powered smartphone. Actually, the type of phone used for each recording is in the log and meta data files of each packet. So you might have to look and see specifics\r\n for that phone to understand the data collected better, but our basic understanding is yes it is a spectrum of data.
\r\n
\r\nHope that helps.
[quote=FBLLC;20245]
\r\nHow 'dirty' are the sample data? In the description you say there were compliance problems, technology malfunctions, etc. as is expected in early studies. Have these been removed?
\r\n\r\n
[/quote]
\r\nAny malfunctions in terms of data not recording correctly was removed. Technical issues include data storage and transmission primarily.
\r\n
\r\nFor example, you will notice for some of the participants there might be packets that only contain data for a few seconds, but the data is still collected on a streaming basis. This was a bug in the software that we ultimately corrected, but the data that\r\n was collected here, other than not being a 1 hour length packet is still accurate.
\r\n
\r\nAnother example, some of the packets for Sweetpea and Apple might have some meta files in their packets for the other. It is just the meta files and this is because they traded the phone between them at one point without fully resetting the software. It did\r\n not affect the data that was collected, and the name on the packet is the name of the person who's data was being collected.
\r\n
\r\nI would not say the data is super clean or highly organized in its form, but it is all accurate in what was collected via the sensors.
\r\n
\r\nHope that helps.
[quote=AA;20252]
\r\nIs it accurate that Cherry did not do a 2nd questionnaire and also none of the control participants did any questionnaires? Thanks.
\r\n[/quote]
\r\nIt seems Cherry is missing from the file. We will locate it and post it.
\r\n
\r\nYes, it is correct that none of the control participants filled out the questionnaire. The questionnaire is just for measuring UPDRS, so it was only applicable to the PD patients.
[quote=James Teo;20254]
\r\nThe study design mentions that the patients/ volunteers kept the phones in their pocket or wear them around their neck. Is there any record of this on a per-subject or per-charge-cycle basis?
\r\nAlso, i don't understand what is actually being recorded in "frequency motion energy" for the accelerometry. I understand the recording frequency is 1Hz or less. So how can there be spectral\r\n power of at frequencies of 1, 3 , 6 and 10Hz?
\r\n[/quote]
\r\nEveryone except one of the participants (Peone) carried them in either a hip pocket or a shirt pocket.
\r\n
\r\nAs for the accelerometer question,this is a standard accelerometer that is in an Android powered smartphone. Actually, the type of phone used for each recording is in the log and meta data files of each packet. So you might have to look and see specifics\r\n for that phone to understand the data collected better, but our basic understanding is yes it is a spectrum of data.
\r\n
\r\nHope that helps.
Thank you! That is a big help.
\r\nAnother side comment, it would be much easier for me if each line in the CSV files had the subject's code name. Now I have to pull it out of the file name and not the contents. Perhaps I am the only one.
", "rawMarkdown": "", "votes": null }, { "id": "20574", "postDate": "02/18/2013 16:05:04", "content": "I find the MJFF promotional video to be in contrast to this study. The video clains that the research is guided by experts in the field - anyone who works in predicting patient state using data (as I do for stroke) would tell you that the sample needs to\r\n be much larger, and more well controlled.
\r\nWe have a similar study ongoing with 500 participants. We consider it to be a small pilot study. 16 patients will tell you nothing and reflects, imho, a waste of money.
\r\nAdditionally, raw measures of accelerometer data are not hugely useful. It would have been more prudent to validate an algorythm to recognise, for instance, a "bed to chair transfer" or "seat to standing transfer" as these reflect basic activities of daily\r\n living. These kind of metrics are the accepted standard.
\r\nThe noise from a patient forgetting to charge their device, or wear it one day, can only be countered with a very high sample. I would suggest over 200 participants for the kind of procedure you suggest. A pilot should contain a minimum of 30 patients (what\r\n would be required to detect a difference between your control group and patient group assuming a moderate effect).
\r\nFurthermore, unless I have misunderstood, you actually intend to stratify patients using an algorythm. So infact the healthy control group isnt really your comparison. You need a mild, moderate and severe parkinsons group and see if a classifier can appropriately\r\n recognise patients in different groups, as well as the longitudinal progression from one group to another (eg using a multistate space model).
\r\nAs mentioned in the forum, a ankle device measuring precise gait, or a wrist device to measure tremor might have been a more appropriate method of study.
\r\nIf you like, I would happy to consult (probono) on how this research should be run.
\r\nYou may contact me at justin.grace@kcl.ac.uk
\r\nBest,
\r\nJustin Grace
", "rawMarkdown": "", "votes": null }, { "id": "20675", "postDate": "02/21/2013 16:49:00", "content": "[quote=TonyDIrl;20291]
\r\nJust adding my two cents....
\r\nI did my PhD on a similiar topic; analyzing / segmeneting various subject subgroups using body sensor networks.
\r\nWe gathered a significant amount of accelerometry data.
\r\nAccelerometers are a combination of movement due to gravity, movement due to the body and noise with overlapping spectra. Low Pass / High Pass filters can seperate these components to some extent.
\r\nHowever, unless the location of the sensor is both known and fixed relative to the subjects plane (anterposterior etc) then these data are highly unrealiable. Furthermore, now knowing whether the sensor was in the pocket / chest and a small sample size bias\r\n makes this a very abstract problem.
\r\nPerhaps a more useful approach would be to affix a sensor to a known location (wrist, ankle, lower back near the COM) and calculate various spatio-temporal parameters (gait, balance etc).
\r\nWIth that said, cool project and hats off to the MJFF - very important and genuine.
\r\n[/quote]
\r\n\r\n
Thanks for your great suggestions. We're aware of all the limitations but want to make the best out of the data we have. It would be great to think about going beyond "N = number of people" and consider that N can represent actions, hours, events, or any\r\n number of entities with thousands of samples. :)
\r\n
\r\n
Question: Is there any way to get a supplemental data set with location of phone. It seems that whether the phone was worn around the neck or in the pocket may make a large difference in the accelerometer data and would be very helpful to solving this problem.\r\n I bet the data will be clusterable on that parameter anwyay, but it would be easy if we had a refernce! Thanks!
", "rawMarkdown": "", "votes": null }, { "id": "21032", "postDate": "03/04/2013 14:43:50", "content": "HI Will,
\r\nCan you throw some light on the low frequency, low-mid frequency and high-frequency ranges corresponding to the mjff data ?
\r\n
\r\n
Thanks! Just checking out the data now. Wanted to confirm that the fields First Name and Last Name in UPDRS Part 1 Questionnaire 2 are meant to be posted?
\r\nBen
", "votes": null, "replies": [] }, { "id": 20132, "author_name": "wcukierski", "author_url": "", "post_date": "02/07/2013 04:54:34", "content": "Thanks for catching that, BenM. That file was uploaded by MJFF but I doubt they intended for it to be there. I replaced the file with a version without the names. Let me know if you find anything else.
", "votes": null, "replies": [] }, { "id": 20152, "author_name": "salimali", "author_url": "", "post_date": "02/07/2013 19:54:01", "content": "Hi Will,
\r\nIn the submissions page, What does 'upvote this submission' mean?
", "votes": null, "replies": [] }, { "id": 20153, "author_name": "wcukierski", "author_url": "", "post_date": "02/07/2013 19:59:11", "content": "Good question. Here, it can be used for (a) sorting submissions or (b) a nod of appreciation to a fellow Kaggler for a job well done. The judging panel is free to ignore or incorporate upvotes as they see fit.
", "votes": null, "replies": [] }, { "id": 20154, "author_name": "salimali", "author_url": "", "post_date": "02/07/2013 20:15:30", "content": "[quote=William Cukierski;20153]
\r\nGood question. Here, it can be used for (a) sorting submissions or (b) a nod of appreciation to a fellow Kaggler for a job well done. The judging panel is free to ignore or incorporate upvotes as they see fit.
\r\n[/quote]
\r\nNext question - in the rules it states
\r\nAccess to submitted print materials is only granted by the Michael J. Fox Foundation to the members of its judging panel.
\r\nI assume this means submissions are not viewable to fellow Kagglers to give this nod of appreciation.
", "votes": null, "replies": [] }, { "id": 20162, "author_name": "bittermellon", "author_url": "", "post_date": "02/08/2013 03:13:25", "content": "Only 16 subjects. I'm already pessimistic about what can be accomplished with such a small sample size.
", "votes": null, "replies": [] }, { "id": 20163, "author_name": "benm483996", "author_url": "", "post_date": "02/08/2013 03:20:40", "content": "[quote=bittermellon;20162]
\r\nOnly 16 subjects. I'm already pessimistic about what can be accomplished with such a small sample size.
\r\n[/quote]
\r\nAppropriate username! :)
", "votes": null, "replies": [] }, { "id": 20191, "author_name": "mauriziofacheris", "author_url": "", "post_date": "02/08/2013 16:10:01", "content": "Hi from the MJFF!
\r\nAgree that power of analysis might be limited, given the small sample size. Still, we would like to see IF there are some smart ideas out there to use those data! If something is even indicative of a trend, a bigger project\r\n could then be developed.
", "votes": null, "replies": [] }, { "id": 20194, "author_name": "wcukierski", "author_url": "", "post_date": "02/08/2013 17:29:47", "content": "[quote=Sali Mali;20154]
\r\nNext question - in the rules it states
\r\nAccess to submitted print materials is only granted by the Michael J. Fox Foundation to the members of its judging panel.
\r\nI assume this means submissions are not viewable to fellow Kagglers to give this nod of appreciation.
\r\n[/quote]
\r\nThanks for catching this. I spoke with the MJFF and this was a bit of legalese left over from a previous iteration of the contest rules. It has been removed from the rules.
", "votes": null, "replies": [] }, { "id": 20245, "author_name": "forbear", "author_url": "", "post_date": "02/09/2013 20:33:45", "content": "How 'dirty' are the sample data? In the description you say there were compliance problems, technology malfunctions, etc. as is expected in early studies. Have these been removed?
\r\n", "votes": null, "replies": [] }, { "id": 20252, "author_name": "aa84124", "author_url": "", "post_date": "02/10/2013 01:16:35", "content": "
Is it accurate that Cherry did not do a 2nd questionnaire and also none of the control participants did any questionnaires? Thanks.
", "votes": null, "replies": [] }, { "id": 20254, "author_name": "jamesteo0", "author_url": "", "post_date": "02/10/2013 03:38:25", "content": "The study design mentions that the patients/ volunteers kept the phones in their pocket or wear them around their neck. Is there any record of this on a per-subject or per-charge-cycle basis?
\r\nAlso, i don't understand what is actually being recorded in "frequency motion energy" for the accelerometry. I understand the recording frequency is 1Hz or less. So how can there be spectral\r\n power of at frequencies of 1, 3 , 6 and 10Hz?
", "votes": null, "replies": [] }, { "id": 20291, "author_name": "tonydirl", "author_url": "", "post_date": "02/11/2013 03:11:41", "content": "Just adding my two cents....
\r\nI did my PhD on a similiar topic; analyzing / segmeneting various subject subgroups using body sensor networks.
\r\nWe gathered a significant amount of accelerometry data.
\r\nAccelerometers are a combination of movement due to gravity, movement due to the body and noise with overlapping spectra. Low Pass / High Pass filters can seperate these components to some extent.
\r\nHowever, unless the location of the sensor is both known and fixed relative to the subjects plane (anterposterior etc) then these data are highly unrealiable. Furthermore, now knowing whether the sensor was in the pocket / chest and a small sample size bias\r\n makes this a very abstract problem.
\r\nPerhaps a more useful approach would be to affix a sensor to a known location (wrist, ankle, lower back near the COM) and calculate various spatio-temporal parameters (gait, balance etc).
\r\nWIth that said, cool project and hats off to the MJFF - very important and genuine.
\r\n", "votes": null, "replies": [] }, { "id": 20293, "author_name": "mauriziofacheris", "author_url": "", "post_date": "02/11/2013 03:42:43", "content": "", "votes": null, "replies": [] }, { "id": 20294, "author_name": "mauriziofacheris", "author_url": "", "post_date": "02/11/2013 03:44:13", "content": "
It seems Cherry is missing from the file. We will locate it and post it.
\r\n
\r\nYes, it is correct that none of the control participants filled out the questionnaire. The questionnaire is just for measuring UPDRS, so it was only applicable to the PD patients.
\r\n
Everyone except one of the participants (Peone) carried them in either a hip pocket or a shirt pocket.
\r\n
\r\nAs for the accelerometer question,this is a standard accelerometer that is in an Android powered smartphone. Actually, the type of phone used for each recording is in the log and meta data files of each packet. So you might have to look and see specifics\r\n for that phone to understand the data collected better, but our basic understanding is yes it is a spectrum of data.
\r\n
\r\nHope that helps.
[quote=FBLLC;20245]
\r\nHow 'dirty' are the sample data? In the description you say there were compliance problems, technology malfunctions, etc. as is expected in early studies. Have these been removed?
\r\n\r\n
[/quote]
\r\nAny malfunctions in terms of data not recording correctly was removed. Technical issues include data storage and transmission primarily.
\r\n
\r\nFor example, you will notice for some of the participants there might be packets that only contain data for a few seconds, but the data is still collected on a streaming basis. This was a bug in the software that we ultimately corrected, but the data that\r\n was collected here, other than not being a 1 hour length packet is still accurate.
\r\n
\r\nAnother example, some of the packets for Sweetpea and Apple might have some meta files in their packets for the other. It is just the meta files and this is because they traded the phone between them at one point without fully resetting the software. It did\r\n not affect the data that was collected, and the name on the packet is the name of the person who's data was being collected.
\r\n
\r\nI would not say the data is super clean or highly organized in its form, but it is all accurate in what was collected via the sensors.
\r\n
\r\nHope that helps.
[quote=AA;20252]
\r\nIs it accurate that Cherry did not do a 2nd questionnaire and also none of the control participants did any questionnaires? Thanks.
\r\n[/quote]
\r\nIt seems Cherry is missing from the file. We will locate it and post it.
\r\n
\r\nYes, it is correct that none of the control participants filled out the questionnaire. The questionnaire is just for measuring UPDRS, so it was only applicable to the PD patients.
[quote=James Teo;20254]
\r\nThe study design mentions that the patients/ volunteers kept the phones in their pocket or wear them around their neck. Is there any record of this on a per-subject or per-charge-cycle basis?
\r\nAlso, i don't understand what is actually being recorded in "frequency motion energy" for the accelerometry. I understand the recording frequency is 1Hz or less. So how can there be spectral\r\n power of at frequencies of 1, 3 , 6 and 10Hz?
\r\n[/quote]
\r\nEveryone except one of the participants (Peone) carried them in either a hip pocket or a shirt pocket.
\r\n
\r\nAs for the accelerometer question,this is a standard accelerometer that is in an Android powered smartphone. Actually, the type of phone used for each recording is in the log and meta data files of each packet. So you might have to look and see specifics\r\n for that phone to understand the data collected better, but our basic understanding is yes it is a spectrum of data.
\r\n
\r\nHope that helps.
Thank you! That is a big help.
\r\nAnother side comment, it would be much easier for me if each line in the CSV files had the subject's code name. Now I have to pull it out of the file name and not the contents. Perhaps I am the only one.
", "votes": null, "replies": [] }, { "id": 20574, "author_name": "jusjosgra", "author_url": "", "post_date": "02/18/2013 16:05:04", "content": "I find the MJFF promotional video to be in contrast to this study. The video clains that the research is guided by experts in the field - anyone who works in predicting patient state using data (as I do for stroke) would tell you that the sample needs to\r\n be much larger, and more well controlled.
\r\nWe have a similar study ongoing with 500 participants. We consider it to be a small pilot study. 16 patients will tell you nothing and reflects, imho, a waste of money.
\r\nAdditionally, raw measures of accelerometer data are not hugely useful. It would have been more prudent to validate an algorythm to recognise, for instance, a "bed to chair transfer" or "seat to standing transfer" as these reflect basic activities of daily\r\n living. These kind of metrics are the accepted standard.
\r\nThe noise from a patient forgetting to charge their device, or wear it one day, can only be countered with a very high sample. I would suggest over 200 participants for the kind of procedure you suggest. A pilot should contain a minimum of 30 patients (what\r\n would be required to detect a difference between your control group and patient group assuming a moderate effect).
\r\nFurthermore, unless I have misunderstood, you actually intend to stratify patients using an algorythm. So infact the healthy control group isnt really your comparison. You need a mild, moderate and severe parkinsons group and see if a classifier can appropriately\r\n recognise patients in different groups, as well as the longitudinal progression from one group to another (eg using a multistate space model).
\r\nAs mentioned in the forum, a ankle device measuring precise gait, or a wrist device to measure tremor might have been a more appropriate method of study.
\r\nIf you like, I would happy to consult (probono) on how this research should be run.
\r\nYou may contact me at justin.grace@kcl.ac.uk
\r\nBest,
\r\nJustin Grace
", "votes": null, "replies": [] }, { "id": 20675, "author_name": "mauriziofacheris", "author_url": "", "post_date": "02/21/2013 16:49:00", "content": "[quote=TonyDIrl;20291]
\r\nJust adding my two cents....
\r\nI did my PhD on a similiar topic; analyzing / segmeneting various subject subgroups using body sensor networks.
\r\nWe gathered a significant amount of accelerometry data.
\r\nAccelerometers are a combination of movement due to gravity, movement due to the body and noise with overlapping spectra. Low Pass / High Pass filters can seperate these components to some extent.
\r\nHowever, unless the location of the sensor is both known and fixed relative to the subjects plane (anterposterior etc) then these data are highly unrealiable. Furthermore, now knowing whether the sensor was in the pocket / chest and a small sample size bias\r\n makes this a very abstract problem.
\r\nPerhaps a more useful approach would be to affix a sensor to a known location (wrist, ankle, lower back near the COM) and calculate various spatio-temporal parameters (gait, balance etc).
\r\nWIth that said, cool project and hats off to the MJFF - very important and genuine.
\r\n[/quote]
\r\n\r\n
Thanks for your great suggestions. We're aware of all the limitations but want to make the best out of the data we have. It would be great to think about going beyond "N = number of people" and consider that N can represent actions, hours, events, or any\r\n number of entities with thousands of samples. :)
\r\n
\r\n
Question: Is there any way to get a supplemental data set with location of phone. It seems that whether the phone was worn around the neck or in the pocket may make a large difference in the accelerometer data and would be very helpful to solving this problem.\r\n I bet the data will be clusterable on that parameter anwyay, but it would be easy if we had a refernce! Thanks!
", "votes": null, "replies": [] }, { "id": 21032, "author_name": "kuhelee", "author_url": "", "post_date": "03/04/2013 14:43:50", "content": "HI Will,
\r\nCan you throw some light on the low frequency, low-mid frequency and high-frequency ranges corresponding to the mjff data ?
\r\n
\r\n