Homepage: https://github.com/bewest/insulaudit
This python package provides a toolkit for dealing with data used and created by a "modern," circa 2010, insulin therapy regimen.
We provide a command line text based tool, and a python library to audit therapeutic data from a variety of medical devices widely used.
-
Medtronic Minimed Paradigm Series insulin pumps using the usbstick
- observed working with a 522
-
Lifescan Glucose Meters:
- Onetouch series
- Mini/Profile
Nothing special, my system registers a serial device right away.
In linux, you need to poke the usbserial module with some parameters to make it work. This only needs to be done once::
sudo modprobe usbserial vendor=0x0a21 product=0x8001
# or
sudo ./reset.sh
# which runs ./remove.sh and ./insert.sh, the latter
# of which does the modprobe for you.
I've observed runs working up to 5 times in a row, at which point I needed to reset the usbstick by removing it and re-inserting into the PC. On mac, I can't recall if this is necessary. We just need a generic usb-serial adapter. I haven't tried it, but I suspect COM1 will likely work on MS, although auto-scanning will not detect it. If your mac inserts the device somewhere under /dev/usb.serial* we will likely scan it.
In dmesg, you should see a message like this when you inser the usb stick::
[201197.513266] usb 2-1: new full speed USB device using uhci_hcd and address 3
[201197.919110] usb 2-1: configuration #1 chosen from 1 choice
[201205.729621] usbcore: registered new interface driver usbserial
[201205.730808] USB Serial support registered for generic
[201205.731143] usbcore: registered new interface driver usbserial_generic
[201205.731145] usbserial: USB Serial Driver core
[201205.806220] USB Serial support registered for pl2303
[201205.806248] pl2303 2-1:1.0: pl2303 converter detected
[201208.305166] usb 2-1: pl2303 converter now attached to ttyUSB0
[201208.305187] usbcore: registered new interface driver pl2303
[201208.305189] pl2303: Prolific PL2303 USB to serial adaptor driver
bewest@mimsy:~/Documents/bb/diabetes/src/mock$
There is no release of insulaudit, only somewhat broken pieces of code towards establishing a tool. :::
# Download the source
# https://github.com/bewest/insulaudit
# or fork it on github
git clone http://github.com/bewest/insulaudit.git
# install insulaudit in your python runtime so you can
# hack on it from here
python setup.py develop
We can say hello to the pump, but it's easier to read configuration than historical data. We are not sure how to decode historical data.
Right, as the world goes, is only in question between equals in power, while the strong do what they can and the weak suffer what they must.
When vendors offering medical equipment put their own priorities ahead of safe therapy, and then prevent access to making it safer, it's time to put on the black hat for science.
The commands using PYTHONPATH assume you are in the root directory of the repo. The commands using insulaudit assume you have installed insulaudit on your system (including the develop version).
Uses flaky port scanning feature to test if we are able to talk to a pump. Exchange a few bytes, nothing more::
# fails
PYTHONPATH=src/ python -m insulaudit.main -v clmm hello
insulaudit -v clmm hello
Specifying a port seems to work. If it doesn't, retry a few times. ::
# using the subcommand stuff:::
PYTHONPATH=src/ python -m insulaudit.main -v clmm --port /dev/ttyUSB0 hello
insulaudit -v clmm --port /dev/ttyUSB0 hello
# run the protocol exercise directly
PYTHONPATH=src/ python src/insulaudit/devices/clmm/proto.py /dev/ttyUSB0
python -m insulaudit.devices.clmm.proto.py /dev/ttyUSB0
# read-pump-model.log - protocol exercise to read pump
model number. Log of it running successfully 5 times
before it starts failing. stderr and timestamps were
not capture. :-(
Now that the basic framework is taking shape, the protocol support needs to be stabilized and the framework needs to continue to gel a bit. I need a reliable protocol, but there is a retry bug demonstrated earlier that prevents very clean and repeatable runs.
-
stabilize runs of both proto.py and hello
-
expand protocol: ReadHistoryData 205
-
pyserial in git
-
convert hello to some kind of scan
-
introduce new device flows
-
introduce device profiles/console flows
-
record logs
-
review logs
-
audit logs
- merge logs
- search
- reformat
##cli tool insulaudit
-
init - set up a config, from default
-
checkPort/scan - scan for a port/device
-
device
- profile
- log
Message sizes are always in 64 byte chunks, except outgoing messages. Use the radio command to send a message. Generally write each command twice. This is kind of a "send command" command.
pc usb
| |
write |------>| Hint: code is 14th byte (bytes[13])
read |<------| 3 bytes [ 0x01, 0x85 U, ?? ] == success
| | [ 0x01, 0x85 f, ?? ] == fail
write |------>| code=[ 0x03 ] usb status command
repeat | |< Continually ask for the usb status until
| | the stick indicates that we are done
| | receiving and we have a length.
read |<------| length = bytes[6..8]
read |<------| tx.stats = bytes[5]
format |< | Then use the length to format the flush
| | command, which will give us the
| | contents of radio buffer.
write |------>| command [ 0x0C, 0x00, 0x00, HighByte(length),
| | HighByte(length), LowByte(length) ]
read |<------| read data in 64 byte chunks until we've got
| | the amount of data we expected
| |
::
devices/
SyncCommand
ComLink2/
CMD_READ_STATUS = 3;
CMD_READ_PRODUCT_INFO = 4;
CMD_READ_INTERFACE_STATS = 5;
CMD_READ_SIGNAL_STRENGTH = 6;
CMD_READ_DATA = 12;
LSMeter/
LEN_READ_CLOCK = 50;
IO_DELAY_READ_RETRY_MS = 10000;
LSOneTouchUltraMini
READ_TIMEOUT_MS = 500
LSOneTouchUltraSmart
CMD_READ_CLOCK = "DMF\r";
READ_TO_MS = 1500;
MMMeter/
CMD_READ_CLOCK = 160;
CMD_READ_SETTINGS = 162;
CMD_READ_GLUCOSE_DATA = 128;
LEN_READ_CLOCK = 28;
LEN_READ_SETTINGS = 72;
LEN_READ_GLUCOSE_DATA = 44;
READ_TO_MS = 2500;
READ_DATA_OFFSET = 0;
READ_MEM_DATA_OFFSET = 2;
MAX_READ_BYTES = 250;
MMPump/
WRITE_DELAY_MS = 3;
MMPump508/
CMD_READ_RTC = 32;
CMD_READ_PUMP_ID = 33;
CMD_READ_FIRMWARE_VER = 37;
CMD_READ_ERROR_STATUS = 38;
CMD_READ_REMOTE_CTRL_ID = 46;
REC_SIZE_READ_PUMP_ID = 10;
REC_SIZE_READ_FIRMWARE_VER = 8;
REC_SIZE_READ_RTC = 7;
CMD_READ_BATTERY_STATUS = 34;
CMD_READ_REMAINING_INSULIN = 35;
CMD_READ_BOLUS_HISTORY = 39;
CMD_READ_DAILY_TOTALS = 40;
CMD_READ_PRIME_BOLUSES = 41;
CMD_READ_ALARMS = 42;
CMD_READ_PROFILE_SETS = 43;
CMD_READ_USER_EVENTS = 44;
CMD_READ_128K_MEM = 55;
CMD_READ_256K_MEM = 56;
CMD_READ_TEMP_BASAL = 64;
CMD_READ_TODAYS_TOTALS = 65;
CMD_READ_STD_PROFILES = 66;
CMD_READ_A_PROFILES = 67;
CMD_READ_B_PROFILES = 68;
REC_SIZE_READ_PUMP_ID = 10;
REC_SIZE_READ_FIRMWARE_VER = 8;
REC_SIZE_READ_RTC = 7;
REC_SIZE_READ_TODAYS_TOTAL = 4;
REC_SIZE_READ_TEMP_BASAL = 4;
REC_SIZE_READ_CURR_SETTINGS1 = 28;
REC_SIZE_READ_CURR_SETTINGS2 = 26;
REC_SIZE_READ_CURR_SETTINGS3 = 4;
REC_SIZE_READ_CURR_SETTINGS4 = 2;
MMPump511/
SuspendResume = 77;
PushKeypad = 91;
PowerCTRL = 93;
ReadRTC = 112;
ReadPumpId = 113;
ReadBatteryStatus = 114;
ReadRemainingInsulin = 115;
ReadFirmwareVersion = 116;
ReadErrorStatus = 117;
ReadRadioCtrlACL = 118;
ReadBasalTemp = 120;
ReadTotalsToday = 121;
ReadProfiles_STD = 122;
ReadProfiles_A = 123;
ReadProfiles_B = 124;
ReadSettings = 127;
ReadHistoryData = 128;
ReadPumpStatus = 131;
ReadPumpTrace = 163;
ReadDetailTrace = 164;
ReadNewTraceAlarm = 166;
ReadOldTraceAlarm = 167;
MMPump512/ # test pump is a 512
CMD_READ_SETTINGS = 145;
CMD_READ_TEMP_BASAL = 152;
CMD_READ_STD_PROFILES
CMD_READ_A_PROFILES = 147;
CMD_READ_B_PROFILES = 148;
CMD_READ_BG_ALARM_CLOCKS = 142;
CMD_READ_BG_ALARM_ENABLE = 151;
CMD_READ_BG_REMINDER_ENABLE = 144;
CMD_READ_BG_TARGETS = 140;
CMD_READ_BG_UNITS = 137;
CMD_READ_BOLUS_WIZARD_SETUP_STATUS = 135;
CMD_READ_CARB_RATIOS = 138;
CMD_READ_CARB_UNITS = 136;
CMD_READ_LOGIC_LINK_IDS = 149;
CMD_READ_INSULIN_SENSITIVITIES = 139;
CMD_READ_RESERVOIR_WARNING = 143;
CMD_READ_PUMP_MODEL_NUMBER = 141;
CMD_READ_LANGUAGE = 134;
MMGuardian3/
CMD_READ_SENSOR_SETTINGS = 207;
CMD_READ_SENSOR_ALARM_SILENCE = 211;
CMD_READ_SENSOR_DEMO_AND_GRAPH_TIMEOUT = 210
CMD_READ_SENSOR_PREDICTIVE_ALERTS = 209;
CMD_READ_SENSOR_RATE_OF_CHANGE_ALERTS = 212;
MMX15/
CMD_READ_SETTINGS = 192;
CMD_READ_BG_TARGETS = 159;
CMD_READ_CURRENT_HISTORY_PAGE_NUMBER = 157;
CMD_READ_SAVED_SETTINGS_DATE = 193;
CMD_READ_CONSTRAST = 195;
CMD_READ_BOLUS_REMINDER_ENABLE = 197;
CMD_READ_BOLUS_REMINDERS = 198;
CMD_READ_FACTORY_PARAMETERS = 199;
CMD_READ_CURRENT_PUMP_STATUS = 206;
MMX22/ # production pump is a 522
CMD_WRITE_GLUCOSE_HISTORY_TIMESTAMP = 40;
CMD_READ_CURRENT_GLUCOSE_HISTORY_PAGE_NUMBER = 205;
CMD_READ_GLUCOSE_HISTORY = 154;
CMD_READ_CALIBRATION_FACTOR = 156;
CMD_READ_ISIG_HISTORY = 155;
CMD_READ_SENSOR_SETTINGS = 153;
MMX23/
CMD_READ_VCNTR_HISTORY = 213;
CMD_READ_OTHER_DEVICES_IDS = 240;
::
devices/ lsultramini onetouch2 --TO-- devices/ DeviceApp * get_devices * lsultramini ui.py proto.py * onetouch2 proto.py * clmm/ ui.py - proto.py - provides protocol utitilities, subclassing exports classes to use with a core/link base.py
profile.py * checked_at * created_at * version? insulaudit vs rep/format * serial * model * manufacturer * drift_t * uri
ui.py * username, short user, write_err, interactive, flush, edit, traceback, note, debug, prompt, prompt_choice, getpass, log, label, termwidth, expandpath, plain, config stuff, readconfig, has_section, config, setconfig, configsource, configpath, progress,
commands.py - pulls main.py - main entry point, configure the system, and run the console * subclass application from console * get the list of devices from devices/ * Command Subcommand Flow LinkedCommand
core/ * CommBuffer TODO: rename to SerialLink? * command * exceptions * response device link data/ console/ init.py devices
::
insulaudit [opts] [command] insulaudit [opts] [command] insulaudit [device] [command] [opts]
insulaudit clmm scan
Author Ben West [email protected]
This experimental software is provided under the MIT license
_, so you can do with it whatever you wish except
hold me responsible if it does something you don't like.
.. _MIT license: http://www.opensource.org/licenses/mit-license.php
Patients need open access to all the elements of technology involved in therapy in order to ensure safety.
One of many concrete examples involves generating safe insulin doses. The vendor hard coded the active lifetime of insulin into all models earlier than the 515 series. This guarantees that patients receive the wrong amount of insulin. The only feasible way of getting safer doses of insulin is to buy a pump in the 515 series or newer. Users who do choose to buy a new pump can customize this variable but the variable remains static and mostly incorrectly calibrated until it's manually changed again. In reality, your sensitivity to insulin varies, and the amount of insulin one should receive also varies dramatically throughout the day depending on what life throws your way.
However, the pump has an administrative protocol that allows software to automatically audit logs, reconfigure settings, create and administer dosing schedules. If users had access to this protocol we could use it to work around bugs like incorrect insulin calibrations in order to tune our doses. We can also use the protocol to audit the logs, allowing us to independently verify that pump therapy is safe.
There are many other examples where having direct access to all the technology involved in therapy provides an epistemic certainty integral to basic science. As patients and users of medical technology, we want to believe that it is safe. The only way to do this is to empirically study all the relevant details of vendor technology with our peers and to study it for bugs and safety. In the process of doing this we discovered that the same commands used to audit the native therapeutic logs can also be used to reconfigure the device, and administer insulin in ways that can work around bugs that are currently ensuring unsafe dosing for pump users.
The manufacturer is content to give me inaccurate dosings, but refuses to share information about the protocol needed to quickly, safely and independently manage my therapy. As patients we need access to all the technology in our therapy so that we can have epistemic certainty that it is safe.
We set out to use the protocol in order to audit logs more effectively and found out it's possible to generate safer doses and work around bugs in vendors' therapeutic software. The protocol is actively kept from our use, but we need it in order to secure safe therapy. Without having investigated the technology involved in our therapy, we cannot believe it is safe, and we would not have learned about it's true capabilities.
If a doctor approached you with a syringe, said you needed some of it but wasn't personally sure a.) how much was in the syringe, that b.) the syringe sometimes injects the wrong amount, and c.) what contents of the syringe might due to the way the syringe performs, but that someone told him this would probably be "ok" would you allow yourself to be injected? What if the consequences for refusing the syringe was death? What if the reason for the uncertainty was because someone had wiped off most of the calibration markings before giving it to the doctor to fill? What if the person who had wiped off the markings was the same person insisting it was safe and selling you the syringes, and no one else makes syringes?
For the argument "Most users won't need access to technology to get what they need." This isn't an argument for preventing patients from accessing critical parts of their own therapy. This is like arguing no one would need to do anything more than borrow a book from a library shortly after the printing press because the population was unlettered and homes lacked bookshelves to house the books.
Diabetes therapy is wasteful, unscientific, and dangerous. Despite a variety of companies offering software to manage the condition, very little data is used to drive real time decision making during the course of therapy. Many users take error prone and time consuming handwritten transcriptions of their devices, because the software provided is incapable of communicating or managing therapeutic details in any useful way. Some users actually take pictures, and upload those pictures to websites, finding that the easiest way to share critical therapy data.
Despite all the hard work diabetics undertake in efforts audit and control ongoing therapy, most use a variety of mobile devices that automatically log many details. In 2011, we have a nascent highly connected world where relationships construct a social graphs traversable on the web with enough security to trust these relationships for authentication. Despite all the technical advancement in our world, the medical community asks diabetic patients to live inhumane lives maintaining open wounds while blaming them for lack of control and failing to explain cause and effect.
Insulin is a powerful drug best administered by a pancreas. When we use a syringe to inject a large dose all at once, it is no surprise to see dangerous consequences. However, instead of developing ever increasingly accurate predictions, the use of software in managing diabetes mostly involves entering and massaging lots of data. As a result, many diabetics suffer needlessly, blamed for the effect "their condition" has on them due to their poor control, even though the consequences are likely aggravated or caused by the very therapy they are trying to participate in. This is poor fidelity of care.
The best example for this is the NPR obituary for a baseball hall of famer who died of diabetic complications. While he was praised for his adherence to his regimen, he was also praised his tenacity on the field, despite the terrible shakes attributed to "his condition." However, they failed to mentioned that the shakes he suffered were due to the therapy for his condition; the only way a type 1 diabetic suffers shakes like that is when too much insulin has been delivered, an all too familiar mishap. Poor fidelity of care is not knowing what to expect, despite adhering to a therapy.
By applying the fundamentals of the scientific method to therapy, and to the application of technology to therapy, we get a unique perspective on what the technology should do, and the role people have in therapy. The only data we should be entering are corrections on what we predict will happen. This is be one of the ideal applications of technology to therapy through a lense I call high "fidelity of care." Together, we adjust our expectations to match what is possible so that over time the observations of therapy exactly match the expectations we recorded as predictions earlier.
As we integrate calendar data and predictions along side past observations, we get a better understanding of causes and effects in the outcomes of our own therapy while gaining tools to communicate these understandings with our therapeutic team, composed of any individual we choose. The therapeutic team may well be mostly composed of members outside the medical community, because social support is often important in maintaining habits and lifestyle.
This meta observation of the delta between hypothesis and empirical data is a principle component of the scientific method, but entirely absent from therapeutic software, leading to a dearth in fidelity of care. My hope is that insulaudit can help to increase the fidelity of care. The scientific method involves recording high fidelity observations, making predictions based on that data, performing an experiment, and then analyzing the differences between the observations and the expectations. Therapy should not be any different. However, until we can get transparent access to audit the raw data produced by our therapy, we cannot get an accurate perspective of our own health.
Therefore, the first fundamental principle of high fidelity care is open access to all the intimate details of therapeutic care in as close to the native format as possible. It includes access to the protocols transporting the data, so that novel applications can augment therapeutic fidelity in ways unforeseen by the original makers, for the benefit of the patient, and their caregivers.
The second is peer review. A caregiver may be a friend, or even a good samaritan in a time of need, who needs instructions on what to do next. A caregiver may be a researcher who needs access to data for simulations. It includes access to the firmware, because it is outrageous that the software that governs lives has not gone through open source review for bugs and safety.
With these in place, safe and effective from insulaudit, SMART, DUBS, GCCS, and many other collaborators can help infuse therapeutic practice with high fidelity care. The needs of the patient in the practice of high fidelity care are not unique to diabetics. We believe all patients will benefit from the application of these principles throughout their care.