PyCollect¶

A Python package for collecting data from the GE patient monitors, for the purpose of conducting research and preparing training materials.

Tested on:

CARESCAPE Monitor B650

CARESCAPE Monitor B450

Navigation¶

Getting started¶

Install¶

From source¶

git clone git clone git@bitbucket.org:gcpds/pycollect.git
cd pycollect
python setup.py install

From PyPi (not available yet)¶

pip install pycollect

Collect data¶

There are two main modules, GEDevice that handle the connection and data recollecting, and GEDecode that parse and sort the received data strings.

from pycollect import GEDevice

Connection¶

device = GEDevice()
device.connect('/dev/ttyUSB0')

Send request¶

A request is an instruction that enable the data transmission from monitor.

Subrecords¶

There are three subrecord types for the actual measurement data:

device.DISPL for the displayed values.
device.TREND_10S for the 10 s trended values.
device.TREND_60S for the 60 s trended values.

When device.DISPL is used, there is an extra argument, interval, that indicate the transmission interval in seconds, this must be possitive and greater or equal to 5.

device.request(subtype=device.DISPL)

device.TREND_10S and device.TREND_60S are used for request trends.

device.request(subtype=device.TREND_10S)

device.request(subtype=device.TREND_60S)

No further transmission requests are needed after this.

Waveforms¶

Depending on the total number of samples per second the monitor sends a waveform packet every 1000 ms, 500 ms or 250 ms. Request up to 8 waveforms but total sample rate should be less than 600 samples/sec, sample rate for ECG is 300, INVP 100, EEG 100, PLETH 100, respiratory (CO2, O2, NO2 …) 25 each.

The waveform options can be consulted with:

from pycollect.modules import WAVEFORMS_DICT

for wave in WAVEFORMS_DICT:
    print("{label}: {samps}".format(**WAVEFORMS_DICT[wave]))

ECG1: 300
ECG2: 300
ECG3: 300
INVP1: 100
INVP2: 100
INVP3: 100
INVP4: 1
INVP5: 100
INVP6: 100
PLETH: 100
CO2: 25
NO2: 25
AA: 25
AWP: 25
FLOW: 1
VOL: 25
RESP: 25
EEG1: 100
EEG2: 100
EEG3: 1
EEG4: 100
TONO_PRESS: 1
SPI_LOOP_STATUS: 1
ENT_100: 1
EEG_BIS: 1

device.request(waveform_set=['PLETH', 'ECG1'])  #400 samp/s

The limit of sample rate can not be exceeded:

try:
    device.request(waveform_set=['ECG1', 'ECG2', 'ECG3'])  #900 samp/s
except Exception as error:
    print(error)

Sample rate must be less or equal to 600.

No further transmission requests are needed after this.

Mixings¶

A combination of Waveforms and Subrecords can be requested at the same time.

device.request(subtype=device.DISPL, waveform_set=['PLETH', 'ECG1'])

Or in a sequence of requests.

device.request(subtype=device.DISPL, interval=10)
device.request(waveform_set=['PLETH', 'ECG1'])

device.request(subtype=device.DISPL, interval=10)
device.request(subtype=device.TREND_60S)
device.request(waveform_set=['PLETH', 'ECG1'])

Read data¶

The transmitted data is recollected asynchronously with a background thread and appended to a BUFFER list.

To activate the data collecting.

device.collect(True)

To clear the buffer input:

device.clear_buffer()

To stop the data collecting:

device.collect(False)

Decode data¶

The GEDecode module is used for parse and sort the received data strings.

from pycollect import GEDecode

decoder = GEDecode(device.BUFFER)
decoder.process(True)

Clear buffers¶

There are a set of methods for clear correctly the stored buffer and recollected data.

device.clear_buffer()  # clear input buffer.
decoder.clear_buffer()  # clear decoded data, breaks the synchrony.
decoder.clear_data()  # clear recollected data.

The above instructions breaks the synchrony between the collector and decoder, in order to decode input data again GEDecode must be reinstantiated:

decoder = GEDecode(device.BUFFER)
decoder.process(True)

Save data¶

The data can be saved in two differents formats csv and edf, each type of data will be saved with their own sufix: .wave for waveforms, .trend10s and .trend60s for trends.

Save data as CSV¶

decoder.save_as_csv('data_out')

Save data as EDF+¶

The edf format need extra patient information.

decoder.set_edf_header(
    admincode = '',
    birthdate = date(1900, 1, 1), #datetime object
    equipment = '',
    gender = 0, #0 for male, 1 for female
    patientcode = '',
    patientname = '',
    patient_additional = '',
    recording_additional = '',
    technician = '',
)

decoder.save_as_edf('data_out')

Measures¶

All measurement data is represented as signed 16-bit values. Some control information is embedded into the measurement data by assigning special meaning to certain values.

As values with special meaning start from -32001 downwards, the smallest valid value is always -32000.

Physiological measures¶

ECG¶

Label	Description	Unit	Range
`ECG HR`	Heart rate	1/min	0 - 32768
`ECG ST1`	St-level	mm
`ECG ST2`	St-level	mm
`ECG ST3`	St-level	mm
`ECG IMP-RR`	Respiration rate	1/min	0 - 32768
`ECG: MOD`	Measurement module existence	bool
`ECG: ACT`	Measurement activity	bool
`ECG: ASY`	Asystole	bool
`ECG HR-SRC`	Heart rate source 0: Not selected 1: ECG 2: Invasive pressure channel 1 3: Invasive pressure channel 2 4: Invasive pressure channel 3 5: Invasive pressure channel 4 6: SpO2 7: Invasive pressure channel 5 8: Invasive pressure channel 6	str
`ECG: NS`	Noise	bool
`ECG: AR`	Artifact	bool
`ECG: LRN`	Learning	bool
`ECG: PCR`	Pacer On	bool
`ECG: CH1`	Channel 1 off	bool
`ECG: CH2`	Channel 2 off	bool
`ECG: CH3`	Channel 3 off	bool
`ECG LEAD-CH1`	Lead configuration for channel 1 0: Not selected 1: ECG I 2: ECG II 3: ECG III 4: ECG AVR 5: ECG AVL 6: ECG AVF 7: ECG V	str
`ECG LEAD-CH2`	Lead configuration for channel 2 0: Not selected 1: ECG I 2: ECG II 3: ECG III 4: ECG AVR 5: ECG AVL 6: ECG AVF 7: ECG V	str
`ECG LEAD-CH3`	Lead configuration for channel 3 0: Not selected 1: ECG I 2: ECG II 3: ECG III 4: ECG AVR 5: ECG AVL 6: ECG AVF 7: ECG V	str

INV-BP¶

Label	Description	Unit
`INV-BP SYS`	Invasive pressure	mmHg
`INV-BP DIA`	Invasive pressure	mmHg
`INV-BP MEAN`	Invasive pressure	mmHg
`INV-BP HR`	Pulse rate	1/min
`INV-BP: MOD`	Measurement module existence	bool
`INV-BP: ACT`	Measurement activity	bool
`INV-BP: ZR`	Zeroing	bool
`INV-BP LBL`	Invasive pressure label 0: Not defined 1: ART 2: CVP 3: PA 4: RAP 5: RVP 6: LAP 7: ICP 8: ABP 9: P1 10: P2 11: P3 12: P4 13: P5 14: P6	str

NIBP¶

Label	Description	Unit	Range
`NIBP SYS`	Invasive pressure	mmHg	0 - 327
`NIBP DIA`	Invasive pressure	mmHg	0 - 327
`NIBP MEAN`	Invasive pressure	mmHg	0 - 327
`NIBP HR`	Pulse rate	1/min
`NIBP: MOD`	Measurement module existence	bool
`NIBP: ACT`	Measurement activity	bool
`NIBP CUFF`	Invasive pressure cuff type 0: Not defined 1: Infant 2: Reserved 3: Adult	str
`NIBP: AUTO`	Invasive pressure: AUTO mode selected	bool
`NIBP: STAT`	Invasive pressure: STAT mode selected	bool
`NIBP: MSR`	Invasive pressure: measuring	bool
`NIBP: STASIS`	Invasive pressure: STASIS ON	bool
`NIBP: CLBR`	Invasive pressure: calibrating	bool
`NIBP: OLD`	Invasive pressure: data is older than 60s	bool

TEMP¶

Label	Description	Unit
`TEMP`	Temperature	°C
`TEMP: MOD`	Measurement module existence	bool
`TEMP: ACT`	Measurement activity	bool
`TEMP LBL`	Temperature label 0: Not used 1: ESO 2: NASO 3: TYMP 4: RECT 5: BLAD 6: AXIL 7: SKIN 8: AIRW 9: ROOM 10: MYO 11: T1 12: T2 13: T3 14: T4 15: CORE 16: SURF	str

SpO2¶

Label	Description	Unit
`SpO2`	Oxygenation percentage	%
`SpO2 PR`	Pulse rate	1/min
`SpO2 IR-AMP`	Modulation	%
`SpO2 [SO2\|SaO2\|SvO2]`	Modulation, value is specified by the label.	%
`SpO2: MOD`	Measurement module existence	bool
`SpO2: ACT`	Measurement activity	bool
`SpO2 LBL`	Measurement module existence 0: SO2 1: SaO2 2: SvO2 3: Not used	str

CO2¶

Label	Description	Unit	Range
`CO2 ET`	Expiratory concentration	%	0 - 100
`CO2 FI`	Inspiratory concentration	%	0 - 100
`CO2 RR`	Respiration rate	1/min
`CO2 PAMB`	Ambient pressure	mmHg
`CO2: MOD`	Measurement module existence	bool
`CO2: ACT`	Measurement activity	bool
`CO2: AP`	Apnea	bool
`CO2: CS`	Calibrating sensor	bool
`CO2: ZS`	Zeroing sensor	bool
`CO2: OC`	Occlusion	bool
`CO2: ALK`	Air leak	bool
`CO2 LBL`	These bits indicate the respiration rate source 0: Not selected 1: CO2 2: ECG, Impedance respiratory	str
`CO2: CLBR`	Caliabrating	bool
`CO2: MNS`	Measurement off	bool

O2¶

Label	Description	Unit
`O2 ET`	Expiratory concentration	%
`O2 FI`	Inspiratory concentration	%
`O2: MOD`	Measurement module existence	bool
`O2: ACT`	Measurement activity	bool

N2O¶

Label	Description	Unit
`N2O ET`	Expiratory concentration	%
`N2O FI`	Inspiratory concentration	%
`N2O: MOD`	Measurement module existence	bool
`N2O: ACT`	Measurement activity	bool
`N2O: CLBR`	Caliabrating	bool
`N2O: MNS`	Measurement off	bool

AA¶

Label	Description	Unit
`AA ET`	Anesthesia Agents ET	%
`AA FI`	Anesthesia Agent FI	%
`AA MAC-SUM`	Anesthesia Agents MAC SUM	%
`AA: MOD`	Measurement module existence	bool
`AA: ACT`	Measurement activity	bool
`AA: CLBR`	Caliabrating	bool
`AA: MNS`	Measurement off	bool
`AA`	Anesthesia Agent 0: Unknow 1: None 2: HAL 3: ENF 4: ISO 5: DES 6: SEV	str

FLOW-VOL¶

Label	Description	Unit
`FLOW-VOL RR`	Respiration rate	1/min
`FLOW-VOL PPEAK`	Peak pressure	cmH2O
`FLOW-VOL PEEP`	Positive end exp. pressure	cmH2O
`FLOW-VOL PPLAT`	Plateau pressure	cmH2O
`FLOW-VOL TV-INSP`	Inspiratory tidal volume	ml
`FLOW-VOL TV-EXP`	Expiratory tidal volume	ml
`FLOW-VOL COMP`	Compliance	ml/cmH2O
`FLOW-VOL MV-EXP`	Expiratory minute volume	l/min
`FLOW-VOL: MOD`	Measurement module existence	bool
`FLOW-VOL: ACT`	Measurement activity	bool
`FLOW-VOL: DIS`	Disconnection	bool
`FLOW-VOL: CLBR`	Calibrating	bool
`FLOW-VOL: ZR`	Zeroing	bool
`FLOW-VOL: OBS`	Obstruction	bool
`FLOW-VOL: LK`	Leak	bool
`FLOW-VOL: MSR`	Measurement off	bool

CO-WEDGE¶

Label	Description	Unit
`CO-WEDGE CO`	Cardiac output	ml/min
`CO-WEDGE TEMP`	Blood temperature	°C
`CO-WEDGE REF`	Right heart ejection fraction	%
`CO-WEDGE PCWP`	Wedge pressure	mmHg
`CO-WEDGE: MOD`	Measurement module existence	bool
`CO-WEDGE: ACT`	Measurement activity	bool
`CO-WEDGE CO-AGE`	Age of CO reading is > 60 s	None
`CO-WEDGE PCWP-AGE`	Age of PCWP reading is > 60 s	None

NMT¶

Label	Description	Unit
`NMT T1`	Wedge pressure	%
`NMT TRATIO`	t4/t1 in TOF mode, t2/t1 in DB mode	%
`NMT PTC-COUNT`	Post tetanic count, max. value 21. Has value 31 if count not available	None
`NMT PTC-TOF-COUNT`	TOF count in TOF mode	None
`NMT PTC-DB-COUNT`	DB count in DB mode	None
`NMT PTC-ST-COUNT`	ST count in ST mode	None
`NMT PTC-STIM`	Stimulus current	mA
`NMT: MOD`	Measurement module existence	bool
`NMT: ACT`	Measurement activity	bool
`NMT STM`	Stimulus mode 0: Train Of Four (TOF mode) 1: Double Burst (DB mode) 2: Single Twitch (ST mode) 3: Post-tetanic count 4: Tetanic 5: Regional block	str
`NMT TIME`	Time 0: Not used 1: 100 us 2: 200 us 3: 300 us	str
`NMT: SUP`	Supramax current found	bool
`NMT: CLBR`	Calibrated	bool

ECG-EXTRA¶

Label	Description	Unit
`ECG-EXTRA: HR`	Heart rate as derived from the ecg signal	bool
`ECG-EXTRA: HR-MAX`	Maximum heart rate	bool
`ECG-EXTRA: HR-MIN`	Minimum heart rate	bool
`ECG-EXTRA: MOD`	Measurement module existence	bool
`ECG-EXTRA: ACT`	Measurement activity	bool

SvO2¶

Label	Description	Unit
`SvO2`	SvO2	%
`SvO2: MOD`	Measurement module existence	bool
`SvO2: ACT`	Measurement activity	bool

ECG-ARRH¶

Label	Description	Unit
`ECG-ARRH HR`	Heart rate	1/min
`ECG-ARRH RR`	The RR interval	1/min
`ECG-ARRH PVC`	Premature Ventricular Contractions	?
`ECG-ARRH: MOD`	Measurement module existence	bool
`ECG-ARRH: ACT`	Measurement activity	bool

ECG-12¶

Label	Description	Unit
`ECG-12 STI`	St-level	mm
`ECG-12 STII`	St-level	mm
`ECG-12 STIII`	St-level	mm
`ECG-12 STAVL`	St-level	mm
`ECG-12 STAVR`	St-level	mm
`ECG-12 STAVF`	St-level	mm
`ECG-12 STV1`	St-level	mm
`ECG-12 STV2`	St-level	mm
`ECG-12 STV3`	St-level	mm
`ECG-12 STV4`	St-level	mm
`ECG-12 STV5`	St-level	mm
`ECG-12 STV6`	St-level	mm
`ECG-12: MOD`	Measurement module existence	bool
`ECG-12: ACT`	Measurement activity	bool
`ECG-12 LEAD-CH1`	Lead configuration for channel 1 0: Not selected 1: ECG I 2: ECG II 3: ECG III 4: ECG AVR 5: ECG AVL 6: ECG AVF 7: ECG V	str
`ECG-12 LEAD-CH2`	Lead configuration for channel 2 0: Not selected 1: ECG I 2: ECG II 3: ECG III 4: ECG AVR 5: ECG AVL 6: ECG AVF 7: ECG V	str
`ECG-12 LEAD-CH3`	Lead configuration for channel 3 0: Not selected 1: ECG I 2: ECG II 3: ECG III 4: ECG AVR 5: ECG AVL 6: ECG AVF 7: ECG V	str

NMT2¶

Label	Description	Unit
`NMT2 T1`	T1 absolute value	None
`NMT2 T2`	T2 absolute value	None
`NMT2 T3`	T3 absolute value	None
`NMT2 T4`	T4 absolute value	None
`NMT2: MOD`	Measurement module existence	bool
`NMT2: ACT`	Measurement activity	bool

EEG¶

Label	Description	Unit
`EEG FEMG`	Frontal electro-myography	uv
`EEG EEG1-AMPL`	RMS amplitude	uv
`EEG EEG1-SFR`	Spectral edge frequency	Hz
`EEG EEG1-MNF`	Median frequency	Hz
`EEG EEG1-DELTA`	Relative power spectral content in delta band	%
`EEG EEG1-THETA`	Relative power spectral content in theta band	%
`EEG EEG1-ALPHA`	Relative power spectral content in alpha band	%
`EEG EEG1-BETA`	Relative power spectral content in beta band	%
`EEG EEG1-BSR`	Burst suppression ratio	%
`EEG EEG2-AMPL`	RMS amplitude	uv
`EEG EEG2-SFR`	Spectral edge frequency	Hz
`EEG EEG2-MF`	Median frequency	Hz
`EEG EEG2-DELTA`	Relative power spectral content in delta band	%
`EEG EEG2-THETA`	Relative power spectral content in theta band	%
`EEG EEG2-ALPHA`	Relative power spectral content in alpha band	%
`EEG EEG2-BETA`	Relative power spectral content in beta band	%
`EEG EEG2-BSR`	Burst suppression ratio	%
`EEG EEG3-AMPL`	RMS amplitude	uv
`EEG EEG3-SEF`	Spectral edge frequency	Hz
`EEG EEG3-MF`	Median frequency	Hz
`EEG EEG3-DELTA`	Relative power spectral content in delta band	%
`EEG EEG3-THETA`	Relative power spectral content in theta band	%
`EEG EEG3-ALPHA`	Relative power spectral content in alpha band	%
`EEG EEG3-BETA`	Relative power spectral content in beta band	%
`EEG EEG3 BSR`	Burst suppression ratio	%
`EEG EEG4-AMPL`	RMS amplitude	uv
`EEG EEG4-SEF`	Spectral edge frequency	Hz
`EEG EEG4-MF`	Median frequency	Hz
`EEG EEG4-DELTA`	Relative power spectral content in delta band	%
`EEG EEG4-THETA`	Relative power spectral content in theta band	%
`EEG EEG4-ALPHA`	Relative power spectral content in alpha band	%
`EEG EEG4-BETA`	Relative power spectral content in beta band	%
`EEG EEG4-BSR`	Burst suppression ratio	%
`EEG: MOD`	Measurement module existence	bool
`EEG: ACT`	Measurement activity	bool
`EEG: MSN`	Measurement type 0: referential 1: bipolar	bool
`EEG: MONTAGE`	Montage (in use: 0…7)	bool
`EEG: HEAD`	Headbox off	bool
`EEG: SSEP`	SSEP cable off	bool
`EEG: CH1-LEADS`	Channel 1 leads off	bool
`EEG: CH2-LEADS`	Channel 2 leads off	bool
`EEG: CH3-LEADS`	Channel 3 leads off	bool
`EEG: CH4-LEADS`	Channel 4 leads off	bool
`EEG: CH1-ARTF`	Channel 1 artefact	bool
`EEG: CH2-ARTF`	Channel 2 artefact	bool
`EEG: CH3-ARTF`	Channel 3 artefact	bool
`EEG: CH4-ARTF`	Channel 4 artefact	bool
`EEG: CH1-NS`	Channel 1 noise	bool
`EEG: CH2-NS`	Channel 2 noise	bool
`EEG: CH3-NS`	Channel 3 noise	bool
`EEG: CH4-NS`	Channel 4 noise	bool
`EEG: EP`	EP selection 0: AEP 1: SSEP	bool
`EEG: MSN`	Measurement type 0: referential 1: bipolar	bool

EEG-BIS¶

Label	Description	Unit
`EEG-BIS`		?
`EEG-BIS SQI`		?
`EEG-BIS EMG`		?
`EEG-BIS SR`		?
`EEG-BIS: MOD`	Measurement module existence	bool
`EEG-BIS: ACT`	Measurement activity	bool

ENTROPY¶

Label	Description	Unit	Range
`ENTROPY SE`	State entropy	%	0 - 100
`ENTROPY RE`	Response entropy	%	0 - 100
`ENTROPY BSR`	Burst suppression rate	%	0 - 100
`ENTROPY: MOD`	Measurement module existence	bool
`ENTROPY: ACT`	Measurement activity	bool

EEG2¶

Label	Description	Unit
`EEG2 COMMON`		?
`EEG2 CH1M`		?
`EEG2 CH1P`		?
`EEG2 CH2M`		?
`EEG2 CH2P`		?
`EEG2 CH3M`		?
`EEG2 CH3P`		?
`EEG2 CH4M`		?
`EEG2 CH4P`		?
`EEG2: MOD`	Measurement module existence	bool
`EEG2: ACT`	Measurement activity	bool

GASEX¶

Label	Description	Unit
`GASEX VO2`	Oxygen consumption	ml/min
`GASEX VCO2`	Carbon dioxide consumption	ml/min
`GASEX EE`	Energy expenditure	kcal/24h
`GASEX RQ`	Respiratory quotient	None
`GASEX: MOD`	Measurement module existence	bool
`GASEX: ACT`	Measurement activity	bool

FLOW-VOL2¶

Label	Description	Unit
`FLOW-VOL2 IPEEP`	Intrinsic PEEP	cmH2O
`FLOW-VOL2 Pmean`	Mean pressure	cmH2O
`FLOW-VOL2 RAW`	Airway resistance	cmH2O
`FLOW-VOL2 MVINSP`	Inspired minute volume	L/min
`FLOW-VOL2 EPEEP`	Extrinsic PEEP	cmH2O
`FLOW-VOL2 MVESEX`	Spontaneous expired minute volume	L/min
`FLOW-VOL2 IERATIO`		None
`FLOW-VOL2 ISPTIME`		None
`FLOW-VOL2 EXPTIME`		None
`FLOW-VOL2 STCCOMP`		None
`FLOW-VOL2 STCPPLAT`		None
`FLOW-VOL2 STCPEEPE`		None
`FLOW-VOL2 STCPEEPI`		None
`FLOW-VOL2: MOD`	Measurement module existence	bool
`FLOW-VOL2: ACT`	Measurement activity	bool

BAL-GAS¶

Label	Description	Unit
`BAL-GAS ET`	Expiratory concentration	%
`BAL-GAS FI`	Inspiratory concentration	%
`BAL-GAS: MOD`	Measurement module existence	bool
`BAL-GAS: ACT`	Measurement activity	bool

TONO¶

Label	Description	Unit
`TONO PrCO2`	PrCO2 concentration	kPa
`TONO P(r-Et)CO2`	P(r-Et)CO2 gap	kPa
`TONO P(r-a)CO2`	P(r-a)CO2 gap	kPa
`TONO PADELAY`	PaCO2 delay	min
`TONO PHI`	pHi value	None
`TONO PHIDELAY`	pHi delay	min
`TONO PAMB`	Ambient pressure	mmHg
`TONO CMPA`	Research data	None
`TONO: MOD`	Measurement module existence	bool
`TONO: ACT`	Measurement activity	bool
`TONO: LEAK`	Leak	bool
`TONO: VOLDR`	volume dropped in catheter	bool
`TONO: TECHFAIL`	Technical failure	bool
`TONO: UNFILL`	Unable to fill catheter	bool
`TONO: OVER`	PrCO2 over limit	bool

AA2¶

Label	Description	Unit
`AA2 MAC-AGE-SUM`		?
`AA2: MOD`	Measurement module existence	bool
`AA2: ACT`	Measurement activity	bool

Waveform measures¶

Label	Description	Unit	Samps
`ECG1`		mV	300
`ECG2`		mV	300
`ECG3`		mV	300
`INVP1`	Invasive blood pressure	mmHg	100
`INVP2`	Invasive blood pressure	mmHg	100
`INVP3`	Invasive blood pressure	mmHg	100
`INVP4`	Invasive blood pressure	mmHg	100
`INVP5`	Invasive blood pressure	mmHg	100
`INVP6`	Invasive blood pressure	mmHg	100
`PLETH`	Plethysmograph: modulation	%	100
`CO2`	CO2 concentration	%	25
`N2O`	N2O concentration	%	25
`AA_WAVE`	Anaesthesia agent	%	25
`AWP`	Airway pressure	cmH2O	25
`FLOW`	Airway flow	l/min	25
`VOL`	Airway volume	?	25
`RESP`	ECG impedance	Ω	25
`EEG1`		uV	100
`EEG2`		uV	100
`EEG3`		uV	100
`EEG4`		uV	100
`TONO_PRESS`		?	?
`SPI_LOOP_STATUS`		?	?
`ENT_100`	EEG channel from ENT100 module.	uV	300
`EEG_BIS`		?	?

Headers¶

Datex Header¶

All requests use this header:

Byte No	Description
1	Start flag: FRAMECHAR
2	(start of header) Total length = 0031h = 49d bytes (word r_len)
3
4	Reserved, set to zero (byte res1)
5	Ignored by monitor, set to zero (byte r_dri_level)
6	Reserved = 0000H (byte res2[2])
7	Reserved = 0000H (byte res2[2])
8	Transmission time = 0x00000000, ignored by monitor when sending transmission request (dword r_time). However, time can be meaningful in outputted messages, which use the header of the same structure (dword r_time).
9
10
11
12	Reserved = 00000000H (dword res3)
13
14
15
16	Main type of record = DRI_MT_PHDB = 0 (r_maintype)
17	Main type of record = DRI_MT_PHDB = 0 (r_maintype)
18	Offset to the first subrecord = 0000H (sr_desc[0].offset)
19	Offset to the first subrecord = 0000H (sr_desc[0].offset)
20	Type of first subrecord, DRI_PH_XMIT_REQ = 0 (sr_desc[0].sr_type)
21	Offset to the second subrecord = 0000H, calculated from the beginning of the data area after the header part. Value is not meaningful, since there is only one subrecord in the request (sr_desc[1].offset).
22
23	“No more subrecords” (sr_desc[1].sr_type)
24	sr_desc[2].offset = 000, no meaning since only one subrecord transmitted. sr_desc[2].sr_type, no meaning
25
26
27	sr_desc[3].offset = 000, no meaning sr_desc[3].sr_type, no meaning
28
29
30	sr_desc[4].offset = 000, no meaning sr_desc[4].sr_type, no meaning
31
32
33	sr_desc[5].offset = 000, no meaning sr_desc[5].sr_type, no meaning
34
35
36	sr_desc[6].offset = 000, no meaning sr_desc[6].sr_type, no meaning
37
38
39	sr_desc[7].offset = 000, no meaning sr_desc[7].sr_type = 0, no meaning
40
41

class pycollect.headers.DatexHeaderRequest(*args, **kwargs)[source]¶

Bases: pycollect.headers.HeaderHandler

Header for request transfer.

This header is the combination of Datex Header and the follow header:

Byte No	Description
42	Request current values of physiological database = DRI_PH_DISPL (field phdb_rcrd_type of struct phdb_req)
43	Transmission interval in seconds = 00A, i.e., send current values of physiological database every 10 seconds (field tx_interval of struct phdb_req)
44
45	reserved[0] of struct phdb_req, must be zeroed
46	reserved[0] of struct phdb_req, must be zeroed
47	reserved[1] of struct phdb_req, must be zeroed
48	reserved[1] of struct phdb_req, must be zeroed
49	reserved[2] of struct phdb_req, must be zeroed
50	reserved[2] of struct phdb_req, must be zeroed
51	Checksum
52	End flag: FRAMECHAR

class pycollect.headers.DatexHeaderResponse(*args, **kwargs)[source]¶

Bases: pycollect.headers.HeaderHandler

The data transmitted from monitor is writed in this header.

This header is the combination of Datex Header and the follow header, is used for store the waveforms inputs.

Byte No	Description
42-1491	Data
1492	Checksum
1493	End flag: FRAMECHAR

class pycollect.headers.DatexHeaderWaveRequest(*args, **kwargs)[source]¶

Bases: pycollect.headers.HeaderHandler

Header for request wave transfer.

This header is the combination of Datex Header and the follow header, is user for create the recuest of waveforms.

Byte No	Description
42	Request type: one of WF_REQ_CONT_START, WF_REQ_CONT_STOP or WF_REQ_TIMED_START.
43
44	Duration of snapshot
45	Duration of snapshot
46-53	An array of the requested waveform subrecords. There is room for up to 8 waveforms, but the monitor sends only the waveforms that fit within the 600 samples/s limitation and ignores the rest. The type array must be terminated using the DRI_EOL_SUBR_LIST constant (0xFF), unless there are 8 waveforms is the request.
54-73	Reserved
74	Checksum
75	End flag: FRAMECHAR

class pycollect.headers.HeaderHandler(data=None, init=None, size=None)[source]¶

Bases: object

Header Handler.

Establish a way to read and write GE protocol headers.

__getitem__(element)[source]¶

Return value from header.

Parameters:	element (str) – Define de index and the format of requested value.
Returns:	Target element, could be of many types due to the nested suported format.
Return type:	int, list, HeaderHandler

Note

recursive format:: header[‘basic:ecg:hr’]
reverse the byte array before to read:: header[‘-basic:ecg:hr’]
return the byte array without convert to integer:: header[‘basic:ecg:hr,’]
return the boolean for the bit 4:: header[‘basic:ecg:hr:4]
return the integer generated with the bits 0 to 5:: header[‘basic:ecg:hr:0-5]

__init__(data=None, init=None, size=None)[source]¶

Parameters:	data (array) – Load an array to build the header. init (OrderedDict) – Initialize the the data header with this values. size (str) – Define the size in bytes of the current header.

__length__(header)[source]¶

Calculate the bytes length of the current header.

Parameters:	header (dict) – Target header in dict format for calculate the size.
Returns:	Number of bytes used by the header.
Return type:	int

array()[source]¶

Return the sorted byte array with the correct size.

If one element is defined as 2 bytes length, this must be splitted and completed (if necessary) with an empty byte.

Returns:	Single array with data header values, linke in C, C++, C#.
Return type:	list

load(data)[source]¶

Load the data into the current header values.

Parameters:	data (array) – Load an array to build the header.

request()[source]¶

Generate the final header.

Returns:	The main data with start-flag, checksum and end-flag.
Return type:	list

set(element, value)[source]¶

Modify the value of one header element.

Parameters:	element (str) – Header element. value (str) – New value for element.

to32bits(value)[source]¶

Convert a value into a 32 bits array.

Parameters:	value (array, int) – A length 4 array or integer value, if integer then it will be converted to [0, 0, 0, value].
Returns:	List of 32 bits that represents the input value.
Return type:	list

class pycollect.headers.PhysiologicalData(*args, **kwargs)[source]¶

Bases: pycollect.headers.HeaderHandler

The data transmitted from monitor is writed in this header.

This header is the combination of Datex Header and the follow header, is used for store the requested subrecords.

Byte No	Description
0-4	Time
5-274	basic subclass
275-544	ext1 subclass
545-814	ext2 subclass
815-1084	ext3 subclass
1085	Marker, contains the number of latest entered mark.
1086	contains control information for patient data management functions, used internally by the monitor.
1087-1088	The last word of the subrecord, contains The physiological data record class. The current D-O Record Interface level. The subrecord type.

GE Decode¶

Synchronize in decoder with a buffer reference, decoder GEDecode will attempt to process new data added to the buffer.

decoder = GEDecode(device.BUFFER)
decoder.process(True)

There are a set of methods for clear correctly the stored buffer and recollected data.

device.clear_buffer()  # clear input buffer.
decoder.clear_buffer()  # clear decoded data, breaks the synchrony.
decoder.clear_data()  # clear recollected data.

class pycollect.decode.FormatSubrecord(date_, header)[source]¶

Bases: object

Parse raw data into Pandas DataFrames.

__init__(date_, header)[source]¶

Parameters:	date (Datetime object) – Datetime of the current set. header (PhysiologicalData object) – Header with raw data.

check_module(label, replace=None)[source]¶

Check the status module from determinate group.

Parameters:

label (str) – Group for check their respective module.
replace (dict) – Some groups are indexed for multiples modules, in that case, the indexes must be removed.

Returns:

bool – Module exist.
bool – Module is active.

format(active, filters=None)[source]¶

Process a subrecord (their raw header), aply shifts and get references.

Parameters:	active (array) – List of groups to parse. filters (array, optional) – A sub list of desired subrecords.
Returns:	DataFrame with single row that contains all measures with label as headers.
Return type:	DataFrame

get_short(key)[source]¶

From index in header, convert data to integer, validates and return it.

Parameters:	key (Header index) – Location if header of target value.
Returns:	Int if valus is a signed 16 bits, None if the value is over range and bytearray in other cases.
Return type:	int, None, bytearray

module_status()[source]¶

Return the list of present and active modules.

Based in the status bits is possible determine the state of the respective module.

Returns:	list – List of groups with modules availables. list – List of groups with modules availables and actives. list – List of measures availables and actives.

class pycollect.decode.GEDecode(buffer, filter_subrecords=None, filter_waveforms=None)[source]¶

Bases: object

Decode raw data into Pandas DataFrames.

There are two main objects:

DATA_SUBRECORD: Pandas DataFrame with the subrecords data.

DATA_WAVE: Dictionary with waveform name as key with the

Pandas DataFrame with the waveform data.

__continuous_processing__(delay=0.25)[source]¶

Continuous processing.

Parameters:	delay (integer in seconds) – Delay in seconds between each attempted processing.

__create_framelist__(byte)[source]¶

Search for a complete and validated header.

Parameters:	byte (byte) – Byte readed from serial raw data.

__create_recordlist__()[source]¶

Complete the raw header with the correct/full size.

Returns:	Full sized DatexHeaderResponse.
Return type:	list

__init__(buffer, filter_subrecords=None, filter_waveforms=None)[source]¶

Parameters:	buffer (array reference) – Reference with raw data, the processer will attempt to decoded new data added to this object. filter_subrecords (array, optional) – Sublist with desired subrecords, if empty then will process all available measures. filter_waveforms (array, optional) – List of desired waveforms, if emty then will process all requested waveforms.

__processing__()[source]¶

Process the input buffer one byte at a time.

Process the input buffer until a header is completed.

clear_buffer()[source]¶

Clear the processed buffer.

This action brake the synchrony with GEDevice.

clear_data()[source]¶: Clear the processed data.

process(flag=True, delay=1)[source]¶

Enable or disable the continuous data processing.

Parameters:	flag (bool, True) – Enable or disable the continuous data processing. delay (integer in seconds) – Delay in seconds between each process attempt.

read_shorts(buffer)[source]¶

Convert an array if bytes from signed 16 bits to integer.

Parameters:	buffer (array) – Array with raw bytes, It will be processed in pairs (for complete 16 bits).

read_subrecords(record_list)[source]¶

Update the DataFrame of subrecords with new decoded data.

Parameters:	record_list (array) – Raw DatexHeaderResponse.

read_waveforms(record_list, ignore_missging=False)[source]¶

Update the dictionary of waveforms with new decoded data.

Parameters:	record_list (array) – List of raw headers.

save_as_csv(filename)[source]¶

Save the decoded data into a set of CSV files.

Parameters:	filename (str) – Absolute or realtive path for CSV file.
Returns:	A list with filenames generated.
Return type:	list

save_as_edf(filename, edf_header=None, annotations=None)[source]¶

Save the decoded data into a set of EDF+ files.

Parameters:	filename (str) – Absolute or realtive path for EDF+ file. edf_header (dict) – Declare the EDF+ patient header.
Returns:	A list with filenames genrated.
Return type:	list

save_as_raw(filename)[source]¶

Save the decoded data into a RAW file.

Parameters:	filename (str) – Absolute or realtive path for RAW file.
Returns:	A list with filenames generated.
Return type:	list

set_edf_header(**header)[source]¶

Set the EDF+ patient header.

Parameters:

admincode (str) – Sets the admincode.
birthdate (date object from datetime) – Sets the birthdate.
equipment (str) – Describes the measurement equpipment.
gender (int) – Sets the gender, 1 is male, 0 is female.
patientcode (str) – Sets the patient code.
patientname (str) – Sets the patient name.
patient_additional (str) – Sets the additional patient info.
recording_additional (str) – Sets the additional recordinginfo.
startdate (datetime object) – Sets the recording start Time.
technician (str) – Sets the technicians name.

GE Device¶

Connect and request Subrecord and Waveform:

device = GEDevice()
device.connect('/dev/ttyUSB0')

device.request(subtype=device.DISPL, waveform_set=['PLETH', 'ECG1'])

device.collect(True)

To clear the buffer input:

device.clear_buffer()

To stop the data collecting:

device.collect(False)

class pycollect.device.FakeDevice(raw_file)[source]¶

Bases: object

Debugger class for simulate the input data.

__init__(raw_file)[source]¶

Establish the connection and handle the data input from monitor.

Parameters:	raw_file (str, optional) – Input file with raw data.

__read_raw__()[source]¶

Return generator with the input raw data.

Returns:	Generator for single bytes.
Return type:	Generator

close()[source]¶: Close the serial port.

connect(port, timeout)[source]¶

Establish the connection and debug an unrelated serial device.

Parameters:	port (str) – Serial port. timeout (integer) – Timeout for serial comunication.

read(size)[source]¶

Return the input raw file one byte at time.

Parameters:	size (int) – Buffer input size to read.
Returns:	Array with raw data.
Return type:	list

writable()[source]¶

Check if serial port is writable..

Returns:	Port writable.
Return type:	bool

write(data)[source]¶

Write on serial port if available.

Parameters:	data (bytes) – Desired object to write in serial port.

class pycollect.device.GEDevice(raw_file=None)[source]¶

Bases: object

Establish the connection and handle the data input from monitor.

__init__(raw_file=None)[source]¶

Establish the connection and handle the data input from monitor.

Parameters:	raw_file (str, optional) – Read from local file, no serial.

clear_buffer()[source]¶: Crear the data buffer, not the serial input buffer.

close()[source]¶: Close serial port

collect(flag=True, size=4096)[source]¶

Enable or disable the continuous data reading.

Parameters:	flag (bool, True) – Enable or disable the continuous data reading. size (integer, 212) – Input buffer size.

connect(port, timeout=1)[source]¶

Establish the connection with the CARESCAPE Monitor Bx50.

Baudrate: 19200

Parity: even

Stop bits: 1

bytesize: 8 bits

rtscts: True

Parameters:	port (str) – Serial port address. timeout (int, in secods) – Serial port read and write timeout.

create_waveform_set(waveform_set)[source]¶

Generate Waveform set.

Parameters:	waveform_set (array) – List of waveform types.
Returns:	A list of integer that represent the waveforms desired.
Return type:	list

on_connection_loss()[source]¶: Overwritable method.

read(size=4096)[source]¶

Write into the data buffer the bytes readed from serial port.

Parameters:	size (integer, 212) – Input buffer size.

request(subtype=None, waveform_set=None, interval=1)[source]¶

Create and send a data request of Subrecord or/and Waveform type.

Parameters:	subtype (subrecord type object) – DISPL, TREND_10S or TREND_60S waveform_set (array) – List of waveform types. interval (int, in seconds) – If subtype is DISPL interval is accepted and must be an integer equal or greater to 1.

request_multiple_wave_transfer(wave_set, transmission_type)[source]¶

Create and send header of Waveform type.

Parameters:	wave_set (array) – List of constants that represents each waveform type requested, if list lenghth is less than 8, the last integer must be 255. transmission_type (transmission type object) – WF_REQ_CONT_START for start start transmission, WF_REQ_CONT_STOP for stop it and WF_REQ_TIMED_START for request a timed transmission.

request_transfer(subtype, interval)[source]¶

Create and send header of Subrecord type.

Parameters:	subtype (subrecord type object) – DISPL, TREND_10S or TREND_60S interval (int, in seconds) – If subtype is DISPL interval is accepted and must be an integer equal or greater to 5

stop()[source]¶: Send the request for stop the Subrecords and Waveform transmission.

stop_transfer()[source]¶: Send the request for stop the Subrecords transmission.

stop_wave_transfer()[source]¶: Send the request for stop the Waveform transmission.

write_buffer(data)[source]¶

Check if device is writeble and send the data.

Parameters:	data (bytes array) – Bytes with the header that bust sent to the device.

class pycollect.edfwriter.EDF(filename)[source]¶

Bases: object

Create an EDF+ file format.

__init__(filename)[source]¶

Create an EDF+ file format.

Parameters:	filename (str) – Filename for new EDF+ file.

add_channel(channel)[source]¶

Add new chanel to current EDF+.

Parameters:	chanel (EDFChannel object) –

save()[source]¶: Save as EDF+ file.

set_header(**kwargs)[source]¶

Sets the file header.

Parameters:

admincode (str) – Sets the admincode.
birthdate (date object from datetime) – Sets the birthdate.
equipment (str) – Describes the measurement equpipment.
gender (int) – Sets the gender, 1 is male, 0 is female.
patientcode (str) – Sets the patient code.
patientname (str) – Sets the patient name.
patient_additional (str) – Sets the additional patient info.
recording_additional (str) – Sets the additional recordinginfo.
startdate (datetime object) – Sets the recording start Time.
technician (str) – Sets the technicians name.

write_annotation(onset, description, duration=-1)[source]¶

Writes an annotation/event to the file.

Parameters:	onset (int) – Second, where happened the annotation duration (int, optional) – Duration of event anotated description (str) – Description of event

class pycollect.edfwriter.EDFChannel(data, **kwargs)[source]¶

Bases: object

New EDF+ channel.

__init__(data, **kwargs)[source]¶

New channel.

Parameters:

data (array, required) –
label (str, recommended) – channel label (string, <= 16 characters, must be unique
dimension (str, recommended) – physical dimension (e.g., mV) (string, <= 8 characters)
sample_rate (int, required) – sample frequency in hertz
physical_max (float, required) – maximum physical value
physical_min (float, required) – minimum physical value
digital_max (int, optional) – maximum digital value (int, -2**15 <= x < 2**15)
digital_min (int, optional) – minimum digital value (int, -2**15 <= x < 2**15)
transducer (str, optional) – sets the transducer used in this channel
prefilter (str, optional) – sets the prefilter used in this chanel (“HP:0.1Hz”, “LP:75Hz N:50Hz”, etc.)

Examples¶

import numpy
from matplotlib import pyplot
from pycollect import GEDevice, GEDecode, database, measures

Read RAW file¶

The PyCollect library include a set of prerecorded database for debug purposes.

for raw in database.RAWS_ABSPATH:
    print("RAW file path: {}".format(raw))

RAW file path: /usr/lib/python3.6/site-packages/pycollect-1.0-py3.6.egg/pycollect/database/db02.raw
RAW file path: /usr/lib/python3.6/site-packages/pycollect-1.0-py3.6.egg/pycollect/database/db00.raw
RAW file path: /usr/lib/python3.6/site-packages/pycollect-1.0-py3.6.egg/pycollect/database/db01.raw

# Read the file
file = open(database.RAWS_ABSPATH[1], 'rb')
data = file.read()
data = data[:int(4e4)]
file.close()

decoder = GEDecode(data)

# Buffer and modules
print("Buffer size: {} bytes".format(len(decoder.BUFFER)))
print("Modules detected: {}".format(decoder.MODULES))
print("Modules active: {}".format(decoder.MODULES_ACTIVE))

# Available labels
print("Trends: {}".format(decoder.DATA_SUBRECORD.columns.tolist()))
print("Waves: {}".format(list(decoder.DATA_WAVE.keys())))

pyplot.figure(figsize=(12,6), dpi=200)
pyplot.plot(decoder.DATA_SUBRECORD['ENTROPY RE'])
pyplot.legend(['ENTROPY RE'])

pyplot.figure(figsize=(12,6), dpi=200)
pyplot.plot(decoder.DATA_WAVE['ENT_100']['values'][:500])
pyplot.legend(['ENT_100'])

pyplot.figure(figsize=(12,6), dpi=200)
pyplot.plot(decoder.DATA_WAVE['PLETH']['values'][:500])
pyplot.legend(['PLETH'])

Buffer size: 40000 bytes
Modules detected: ['INV-BP (p1)', 'INV-BP (p2)', 'ECG', 'NIBP', 'SpO2', 'NMT', 'ECG-EXTRA', 'ECG-ARRH', 'ECG-12', 'NMT2', 'ENTROPY']
Modules active: ['ECG', 'NIBP', 'SpO2', 'NMT', 'ECG-EXTRA', 'ECG-ARRH', 'ECG-12', 'NMT2', 'ENTROPY']
Trends: ['AA', 'AA ET', 'AA FI', 'AA MAC-SUM', 'AA2 MAC-AGE-SUM', 'AA: CLBR', 'AA: MNS', 'BAL-GAS ET', 'BAL-GAS FI', 'CO-WEDGE CO', 'CO-WEDGE CO-AGE', 'CO-WEDGE PCWP', 'CO-WEDGE PCWP-AGE', 'CO-WEDGE REF', 'CO-WEDGE TEMP', 'CO2 ET', 'CO2 FI', 'CO2 LBL', 'CO2 PAMB', 'CO2 RR', 'CO2: ALK', 'CO2: AP', 'CO2: CLBR', 'CO2: CS', 'CO2: MNS', 'CO2: OC', 'CO2: ZS', 'ECG HR', 'ECG HR-SRC', 'ECG IMP-RR', 'ECG LEAD-CH1', 'ECG LEAD-CH2', 'ECG LEAD-CH3', 'ECG ST1', 'ECG ST2', 'ECG ST3', 'ECG-12 LEAD-CH1', 'ECG-12 LEAD-CH2', 'ECG-12 LEAD-CH3', 'ECG-12 STAVF', 'ECG-12 STAVL', 'ECG-12 STAVR', 'ECG-12 STI', 'ECG-12 STII', 'ECG-12 STIII', 'ECG-12 STV1', 'ECG-12 STV2', 'ECG-12 STV3', 'ECG-12 STV4', 'ECG-12 STV5', 'ECG-12 STV6', 'ECG-ARRH HR', 'ECG-ARRH PVC', 'ECG-ARRH RR', 'ECG-EXTRA: HR', 'ECG-EXTRA: HR-MAX', 'ECG-EXTRA: HR-MIN', 'ECG: AR', 'ECG: ASY', 'ECG: CH1', 'ECG: CH2', 'ECG: CH3', 'ECG: LRN', 'ECG: NS', 'ECG: PCR', 'EEG EEG1-ALPHA', 'EEG EEG1-AMPL', 'EEG EEG1-BETA', 'EEG EEG1-BSR', 'EEG EEG1-DELTA', 'EEG EEG1-MNF', 'EEG EEG1-SFR', 'EEG EEG1-THETA', 'EEG EEG2-ALPHA', 'EEG EEG2-AMPL', 'EEG EEG2-BETA', 'EEG EEG2-BSR', 'EEG EEG2-DELTA', 'EEG EEG2-MF', 'EEG EEG2-SFR', 'EEG EEG2-THETA', 'EEG EEG3 BSR', 'EEG EEG3-ALPHA', 'EEG EEG3-AMPL', 'EEG EEG3-BETA', 'EEG EEG3-DELTA', 'EEG EEG3-MF', 'EEG EEG3-SEF', 'EEG EEG3-THETA', 'EEG EEG4-ALPHA', 'EEG EEG4-AMPL', 'EEG EEG4-BETA', 'EEG EEG4-BSR', 'EEG EEG4-DELTA', 'EEG EEG4-MF', 'EEG EEG4-SEF', 'EEG EEG4-THETA', 'EEG FEMG', 'EEG-BIS', 'EEG-BIS EMG', 'EEG-BIS SQI', 'EEG-BIS SR', 'EEG2 CH1M', 'EEG2 CH1P', 'EEG2 CH2M', 'EEG2 CH2P', 'EEG2 CH3M', 'EEG2 CH3P', 'EEG2 CH4M', 'EEG2 CH4P', 'EEG2 COMMON', 'EEG: CH1-ARTF', 'EEG: CH1-LEADS', 'EEG: CH1-NS', 'EEG: CH2-ARTF', 'EEG: CH2-LEADS', 'EEG: CH2-NS', 'EEG: CH3-ARTF', 'EEG: CH3-LEADS', 'EEG: CH3-NS', 'EEG: CH4-ARTF', 'EEG: CH4-LEADS', 'EEG: CH4-NS', 'EEG: EP', 'EEG: HEAD', 'EEG: MONTAGE', 'EEG: MSN', 'EEG: SSEP', 'ENTROPY BSR', 'ENTROPY RE', 'ENTROPY SE', 'FLOW-VOL COMP', 'FLOW-VOL MV-EXP', 'FLOW-VOL PEEP', 'FLOW-VOL PPEAK', 'FLOW-VOL PPLAT', 'FLOW-VOL RR', 'FLOW-VOL TV-EXP', 'FLOW-VOL TV-INSP', 'FLOW-VOL2 EPEEP', 'FLOW-VOL2 EXPTIME', 'FLOW-VOL2 IERATIO', 'FLOW-VOL2 IPEEP', 'FLOW-VOL2 ISPTIME', 'FLOW-VOL2 MVESEX', 'FLOW-VOL2 MVINSP', 'FLOW-VOL2 Pmean', 'FLOW-VOL2 RAW', 'FLOW-VOL2 STCCOMP', 'FLOW-VOL2 STCPEEPE', 'FLOW-VOL2 STCPEEPI', 'FLOW-VOL2 STCPPLAT', 'FLOW-VOL: CLBR', 'FLOW-VOL: DIS', 'FLOW-VOL: LK', 'FLOW-VOL: MSR', 'FLOW-VOL: OBS', 'FLOW-VOL: ZR', 'GASEX EE', 'GASEX RQ', 'GASEX VCO2', 'GASEX VO2', 'INV-BP DIA (p1)', 'INV-BP DIA (p2)', 'INV-BP DIA (p3)', 'INV-BP DIA (p4)', 'INV-BP DIA (p5)', 'INV-BP DIA (p6)', 'INV-BP HR (p1)', 'INV-BP HR (p2)', 'INV-BP HR (p3)', 'INV-BP HR (p4)', 'INV-BP HR (p5)', 'INV-BP HR (p6)', 'INV-BP LBL (p1)', 'INV-BP LBL (p2)', 'INV-BP LBL (p3)', 'INV-BP LBL (p4)', 'INV-BP LBL (p5)', 'INV-BP LBL (p6)', 'INV-BP MEAN (p1)', 'INV-BP MEAN (p2)', 'INV-BP MEAN (p3)', 'INV-BP MEAN (p4)', 'INV-BP MEAN (p5)', 'INV-BP MEAN (p6)', 'INV-BP SYS (p1)', 'INV-BP SYS (p2)', 'INV-BP SYS (p3)', 'INV-BP SYS (p4)', 'INV-BP SYS (p5)', 'INV-BP SYS (p6)', 'INV-BP: ZR (p1)', 'INV-BP: ZR (p2)', 'INV-BP: ZR (p3)', 'INV-BP: ZR (p4)', 'INV-BP: ZR (p5)', 'INV-BP: ZR (p6)', 'N2O ET', 'N2O FI', 'N2O: CLBR', 'N2O: MNS', 'NIBP CUFF', 'NIBP DIA', 'NIBP HR', 'NIBP MEAN', 'NIBP SYS', 'NIBP: AUTO', 'NIBP: CLBR', 'NIBP: MSR', 'NIBP: OLD', 'NIBP: STASIS', 'NIBP: STAT', 'NMT PTC-COUNT', 'NMT PTC-DB-COUNT', 'NMT PTC-ST-COUNT', 'NMT PTC-STIM', 'NMT PTC-TOF-COUNT', 'NMT STM', 'NMT T1', 'NMT TIME', 'NMT TRATIO', 'NMT2 T1', 'NMT2 T2', 'NMT2 T3', 'NMT2 T4', 'NMT: CLBR', 'NMT: SUP', 'O2 ET', 'O2 FI', 'SpO2', 'SpO2 IR-AMP', 'SpO2 LBL', 'SpO2 PR', 'SpO2 [SO2|SaO2|SvO2]', 'SvO2', 'TEMP (t1)', 'TEMP (t2)', 'TEMP (t3)', 'TEMP (t4)', 'TEMP LBL (t1)', 'TEMP LBL (t2)', 'TEMP LBL (t3)', 'TEMP LBL (t4)', 'TONO CMPA', 'TONO P(r-Et)CO2', 'TONO P(r-a)CO2', 'TONO PADELAY', 'TONO PAMB', 'TONO PHI', 'TONO PHIDELAY', 'TONO PrCO2', 'TONO: LEAK', 'TONO: OVER', 'TONO: TECHFAIL', 'TONO: UNFILL', 'TONO: VOLDR', 'datetime']
Waves: ['PLETH', 'ENT_100']

<matplotlib.legend.Legend at 0x7f4442e442b0>

Read from monitor¶

device = GEDevice(database.RAWS_ABSPATH[0])
decoder = GEDecode(device.BUFFER)
# device.connect('/dev/ttyUSB0')

The monitor will send all subrecords data but the waves need an explicit request.

default = device.DEFAULT_REQUEST
print("Default data requested: {}".format(default))

# Activate the trends transmission
device.request(subtype=device.DISPL)

# Activate the waves transmission
device.request(waveform_set=['ENT_100', 'PLETH'])

Default data requested: ['date', 'ENTROPY RE', 'ENTROPY SE', 'ENTROPY BSR', 'NIBP SYS', 'NIBP DIA', 'NIBP MEAN', 'ECG IMP-RR', 'ECG HR', 'TEMP (t1)', 'CO2 FI', 'CO2 ET', 'ECG1', 'ENT_100', 'PLETH']

# Start the asynchronous data collecting and process
device.collect(True)
decoder.process(True)

import time
time.sleep(20)

# Buffer and modules
print("Buffer size: {} bytes".format(len(decoder.BUFFER)))
print("Modules detected: {}".format(decoder.MODULES))
print("Modules active: {}".format(decoder.MODULES_ACTIVE))

# Available labels
print("Trends: {}".format(decoder.DATA_SUBRECORD.columns.tolist()))
print("Waves: {}".format(list(decoder.DATA_WAVE.keys())))

Buffer size: 17432 bytes
Modules detected: ['INV-BP (p1)', 'INV-BP (p2)', 'ECG', 'NIBP', 'SpO2', 'CO2', 'O2', 'N2O', 'AA', 'FLOW-VOL', 'ECG-EXTRA', 'ECG-ARRH', 'ECG-12', 'ENTROPY', 'FLOW-VOL2', 'BAL-GAS', 'AA2']
Modules active: ['ECG', 'NIBP', 'SpO2', 'CO2', 'O2', 'N2O', 'AA', 'FLOW-VOL', 'ECG-EXTRA', 'ECG-ARRH', 'ECG-12', 'ENTROPY', 'FLOW-VOL2', 'BAL-GAS', 'AA2']
Trends: ['AA', 'AA ET', 'AA FI', 'AA MAC-SUM', 'AA2 MAC-AGE-SUM', 'AA: CLBR', 'AA: MNS', 'BAL-GAS ET', 'BAL-GAS FI', 'CO-WEDGE CO', 'CO-WEDGE CO-AGE', 'CO-WEDGE PCWP', 'CO-WEDGE PCWP-AGE', 'CO-WEDGE REF', 'CO-WEDGE TEMP', 'CO2 ET', 'CO2 FI', 'CO2 LBL', 'CO2 PAMB', 'CO2 RR', 'CO2: ALK', 'CO2: AP', 'CO2: CLBR', 'CO2: CS', 'CO2: MNS', 'CO2: OC', 'CO2: ZS', 'ECG HR', 'ECG HR-SRC', 'ECG IMP-RR', 'ECG LEAD-CH1', 'ECG LEAD-CH2', 'ECG LEAD-CH3', 'ECG ST1', 'ECG ST2', 'ECG ST3', 'ECG-12 LEAD-CH1', 'ECG-12 LEAD-CH2', 'ECG-12 LEAD-CH3', 'ECG-12 STAVF', 'ECG-12 STAVL', 'ECG-12 STAVR', 'ECG-12 STI', 'ECG-12 STII', 'ECG-12 STIII', 'ECG-12 STV1', 'ECG-12 STV2', 'ECG-12 STV3', 'ECG-12 STV4', 'ECG-12 STV5', 'ECG-12 STV6', 'ECG-ARRH HR', 'ECG-ARRH PVC', 'ECG-ARRH RR', 'ECG-EXTRA: HR', 'ECG-EXTRA: HR-MAX', 'ECG-EXTRA: HR-MIN', 'ECG: AR', 'ECG: ASY', 'ECG: CH1', 'ECG: CH2', 'ECG: CH3', 'ECG: LRN', 'ECG: NS', 'ECG: PCR', 'EEG EEG1-ALPHA', 'EEG EEG1-AMPL', 'EEG EEG1-BETA', 'EEG EEG1-BSR', 'EEG EEG1-DELTA', 'EEG EEG1-MNF', 'EEG EEG1-SFR', 'EEG EEG1-THETA', 'EEG EEG2-ALPHA', 'EEG EEG2-AMPL', 'EEG EEG2-BETA', 'EEG EEG2-BSR', 'EEG EEG2-DELTA', 'EEG EEG2-MF', 'EEG EEG2-SFR', 'EEG EEG2-THETA', 'EEG EEG3 BSR', 'EEG EEG3-ALPHA', 'EEG EEG3-AMPL', 'EEG EEG3-BETA', 'EEG EEG3-DELTA', 'EEG EEG3-MF', 'EEG EEG3-SEF', 'EEG EEG3-THETA', 'EEG EEG4-ALPHA', 'EEG EEG4-AMPL', 'EEG EEG4-BETA', 'EEG EEG4-BSR', 'EEG EEG4-DELTA', 'EEG EEG4-MF', 'EEG EEG4-SEF', 'EEG EEG4-THETA', 'EEG FEMG', 'EEG-BIS', 'EEG-BIS EMG', 'EEG-BIS SQI', 'EEG-BIS SR', 'EEG2 CH1M', 'EEG2 CH1P', 'EEG2 CH2M', 'EEG2 CH2P', 'EEG2 CH3M', 'EEG2 CH3P', 'EEG2 CH4M', 'EEG2 CH4P', 'EEG2 COMMON', 'EEG: CH1-ARTF', 'EEG: CH1-LEADS', 'EEG: CH1-NS', 'EEG: CH2-ARTF', 'EEG: CH2-LEADS', 'EEG: CH2-NS', 'EEG: CH3-ARTF', 'EEG: CH3-LEADS', 'EEG: CH3-NS', 'EEG: CH4-ARTF', 'EEG: CH4-LEADS', 'EEG: CH4-NS', 'EEG: EP', 'EEG: HEAD', 'EEG: MONTAGE', 'EEG: MSN', 'EEG: SSEP', 'ENTROPY BSR', 'ENTROPY RE', 'ENTROPY SE', 'FLOW-VOL COMP', 'FLOW-VOL MV-EXP', 'FLOW-VOL PEEP', 'FLOW-VOL PPEAK', 'FLOW-VOL PPLAT', 'FLOW-VOL RR', 'FLOW-VOL TV-EXP', 'FLOW-VOL TV-INSP', 'FLOW-VOL2 EPEEP', 'FLOW-VOL2 EXPTIME', 'FLOW-VOL2 IERATIO', 'FLOW-VOL2 IPEEP', 'FLOW-VOL2 ISPTIME', 'FLOW-VOL2 MVESEX', 'FLOW-VOL2 MVINSP', 'FLOW-VOL2 Pmean', 'FLOW-VOL2 RAW', 'FLOW-VOL2 STCCOMP', 'FLOW-VOL2 STCPEEPE', 'FLOW-VOL2 STCPEEPI', 'FLOW-VOL2 STCPPLAT', 'FLOW-VOL: CLBR', 'FLOW-VOL: DIS', 'FLOW-VOL: LK', 'FLOW-VOL: MSR', 'FLOW-VOL: OBS', 'FLOW-VOL: ZR', 'GASEX EE', 'GASEX RQ', 'GASEX VCO2', 'GASEX VO2', 'INV-BP DIA (p1)', 'INV-BP DIA (p2)', 'INV-BP DIA (p3)', 'INV-BP DIA (p4)', 'INV-BP DIA (p5)', 'INV-BP DIA (p6)', 'INV-BP HR (p1)', 'INV-BP HR (p2)', 'INV-BP HR (p3)', 'INV-BP HR (p4)', 'INV-BP HR (p5)', 'INV-BP HR (p6)', 'INV-BP LBL (p1)', 'INV-BP LBL (p2)', 'INV-BP LBL (p3)', 'INV-BP LBL (p4)', 'INV-BP LBL (p5)', 'INV-BP LBL (p6)', 'INV-BP MEAN (p1)', 'INV-BP MEAN (p2)', 'INV-BP MEAN (p3)', 'INV-BP MEAN (p4)', 'INV-BP MEAN (p5)', 'INV-BP MEAN (p6)', 'INV-BP SYS (p1)', 'INV-BP SYS (p2)', 'INV-BP SYS (p3)', 'INV-BP SYS (p4)', 'INV-BP SYS (p5)', 'INV-BP SYS (p6)', 'INV-BP: ZR (p1)', 'INV-BP: ZR (p2)', 'INV-BP: ZR (p3)', 'INV-BP: ZR (p4)', 'INV-BP: ZR (p5)', 'INV-BP: ZR (p6)', 'N2O ET', 'N2O FI', 'N2O: CLBR', 'N2O: MNS', 'NIBP CUFF', 'NIBP DIA', 'NIBP HR', 'NIBP MEAN', 'NIBP SYS', 'NIBP: AUTO', 'NIBP: CLBR', 'NIBP: MSR', 'NIBP: OLD', 'NIBP: STASIS', 'NIBP: STAT', 'NMT PTC-COUNT', 'NMT PTC-DB-COUNT', 'NMT PTC-ST-COUNT', 'NMT PTC-STIM', 'NMT PTC-TOF-COUNT', 'NMT STM', 'NMT T1', 'NMT TIME', 'NMT TRATIO', 'NMT2 T1', 'NMT2 T2', 'NMT2 T3', 'NMT2 T4', 'NMT: CLBR', 'NMT: SUP', 'O2 ET', 'O2 FI', 'SpO2', 'SpO2 IR-AMP', 'SpO2 LBL', 'SpO2 PR', 'SpO2 [SO2|SaO2|SvO2]', 'SvO2', 'TEMP (t1)', 'TEMP (t2)', 'TEMP (t3)', 'TEMP (t4)', 'TEMP LBL (t1)', 'TEMP LBL (t2)', 'TEMP LBL (t3)', 'TEMP LBL (t4)', 'TONO CMPA', 'TONO P(r-Et)CO2', 'TONO P(r-a)CO2', 'TONO PADELAY', 'TONO PAMB', 'TONO PHI', 'TONO PHIDELAY', 'TONO PrCO2', 'TONO: LEAK', 'TONO: OVER', 'TONO: TECHFAIL', 'TONO: UNFILL', 'TONO: VOLDR', 'datetime']
Waves: ['PLETH', 'ENT_100']

# pyplot.figure(figsize=(18,9), dpi=90)
# pyplot.plot(decoder.DATA_SUBRECORD['ENTROPY RE'])
# pyplot.legend(['ENTROPY RE'])

pyplot.figure(figsize=(12,6), dpi=200)
pyplot.plot(numpy.linspace(0, 5, 5*measures.WAVEFORMS_DICT['ENT_100']['samps']), decoder.DATA_WAVE['ENT_100']['values'][:500])
pyplot.title(measures.WAVEFORMS_DICT['ENT_100']['desc'])
pyplot.xlabel('time [s]')
pyplot.ylabel(measures.WAVEFORMS_DICT['ENT_100']['unit'])
pyplot.legend(['ENT_100'])

pyplot.figure(figsize=(12,6), dpi=200)
pyplot.plot(numpy.linspace(0, 5, 5*measures.WAVEFORMS_DICT['PLETH']['samps']), decoder.DATA_WAVE['PLETH']['values'][:500])
pyplot.title(measures.WAVEFORMS_DICT['PLETH']['desc'])
pyplot.xlabel('time [s]')
pyplot.ylabel(measures.WAVEFORMS_DICT['PLETH']['unit'])
pyplot.legend(['PLETH'])

<matplotlib.legend.Legend at 0x7f44425c3d30>

Save data¶

The data can be saved in two differents formats RAW, SCV and EDF+.

Save data as CSV¶

decoder.save_as_csv('data_out');

Save data as EDF+¶

The edf format need extra patient information.

from datetime import datetime

decoder.set_edf_header(
    admincode = '',
    birthdate = datetime(1900, 1, 1).timestamp(), #datetime object
    equipment = '',
    gender = 0, #0 for male, 1 for female
    patientcode = '',
    patientname = '',
    patient_additional = '',
    recording_additional = '',
    technician = '',
)

decoder.save_as_edf('data_out');

Save RAW data¶

decoder.save_as_raw('raw');

Channels information¶

List all labels.

subrecords = [g['label'] for g in measures.GROUPS]
print('All subrecords: {}'.format(subrecords))

waves = [g['label'] for g in measures.WAVEFORMS]
print('All waveforms: {}'.format(waves))

All subrecords: ['ECG HR', 'ECG ST1', 'ECG ST2', 'ECG ST3', 'ECG IMP-RR', 'ECG: MOD', 'ECG: ACT', 'ECG: ASY', 'ECG HR-SRC', 'ECG: NS', 'ECG: AR', 'ECG: LRN', 'ECG: PCR', 'ECG: CH1', 'ECG: CH2', 'ECG: CH3', 'ECG LEAD-CH1', 'ECG LEAD-CH2', 'ECG LEAD-CH3', 'INV-BP SYS', 'INV-BP DIA', 'INV-BP MEAN', 'INV-BP HR', 'INV-BP: MOD', 'INV-BP: ACT', 'INV-BP: ZR', 'INV-BP LBL', 'NIBP SYS', 'NIBP DIA', 'NIBP MEAN', 'NIBP HR', 'NIBP: MOD', 'NIBP: ACT', 'NIBP CUFF', 'NIBP: AUTO', 'NIBP: STAT', 'NIBP: MSR', 'NIBP: STASIS', 'NIBP: CLBR', 'NIBP: OLD', 'TEMP', 'TEMP: MOD', 'TEMP: ACT', 'TEMP LBL', 'SpO2', 'SpO2 PR', 'SpO2 IR-AMP', 'SpO2 [SO2|SaO2|SvO2]', 'SpO2: MOD', 'SpO2: ACT', 'SpO2 LBL', 'CO2 ET', 'CO2 FI', 'CO2 RR', 'CO2 PAMB', 'CO2: MOD', 'CO2: ACT', 'CO2: AP', 'CO2: CS', 'CO2: ZS', 'CO2: OC', 'CO2: ALK', 'CO2 LBL', 'O2 ET', 'O2 FI', 'O2: MOD', 'O2: ACT', 'CO2: CLBR', 'CO2: MNS', 'N2O ET', 'N2O FI', 'N2O: MOD', 'N2O: ACT', 'N2O: CLBR', 'N2O: MNS', 'AA ET', 'AA FI', 'AA MAC-SUM', 'AA: MOD', 'AA: ACT', 'AA: CLBR', 'AA: MNS', 'AA', 'FLOW-VOL RR', 'FLOW-VOL PPEAK', 'FLOW-VOL PEEP', 'FLOW-VOL PPLAT', 'FLOW-VOL TV-INSP', 'FLOW-VOL TV-EXP', 'FLOW-VOL COMP', 'FLOW-VOL MV-EXP', 'FLOW-VOL: MOD', 'FLOW-VOL: ACT', 'FLOW-VOL: DIS', 'FLOW-VOL: CLBR', 'FLOW-VOL: ZR', 'FLOW-VOL: OBS', 'FLOW-VOL: LK', 'FLOW-VOL: MSR', 'CO-WEDGE CO', 'CO-WEDGE TEMP', 'CO-WEDGE REF', 'CO-WEDGE PCWP', 'CO-WEDGE: MOD', 'CO-WEDGE: ACT', 'CO-WEDGE CO-AGE', 'CO-WEDGE PCWP-AGE', 'NMT T1', 'NMT TRATIO', 'NMT PTC-COUNT', 'NMT PTC-TOF-COUNT', 'NMT PTC-DB-COUNT', 'NMT PTC-ST-COUNT', 'NMT PTC-STIM', 'NMT: MOD', 'NMT: ACT', 'NMT STM', 'NMT TIME', 'NMT: SUP', 'NMT: CLBR', 'ECG-EXTRA: HR', 'ECG-EXTRA: HR-MAX', 'ECG-EXTRA: HR-MIN', 'ECG-EXTRA: MOD', 'ECG-EXTRA: ACT', 'SvO2', 'SvO2: MOD', 'SvO2: ACT', 'ECG-ARRH HR', 'ECG-ARRH RR', 'ECG-ARRH PVC', 'ECG-ARRH: MOD', 'ECG-ARRH: ACT', 'ECG-12 STI', 'ECG-12 STII', 'ECG-12 STIII', 'ECG-12 STAVL', 'ECG-12 STAVR', 'ECG-12 STAVF', 'ECG-12 STV1', 'ECG-12 STV2', 'ECG-12 STV3', 'ECG-12 STV4', 'ECG-12 STV5', 'ECG-12 STV6', 'ECG-12: MOD', 'ECG-12: ACT', 'ECG-12 LEAD-CH1', 'ECG-12 LEAD-CH2', 'ECG-12 LEAD-CH3', 'NMT2 T1', 'NMT2 T2', 'NMT2 T3', 'NMT2 T4', 'NMT2: MOD', 'NMT2: ACT', 'EEG FEMG', 'EEG EEG1-AMPL', 'EEG EEG1-SFR', 'EEG EEG1-MNF', 'EEG EEG1-DELTA', 'EEG EEG1-THETA', 'EEG EEG1-ALPHA', 'EEG EEG1-BETA', 'EEG EEG1-BSR', 'EEG EEG2-AMPL', 'EEG EEG2-SFR', 'EEG EEG2-MF', 'EEG EEG2-DELTA', 'EEG EEG2-THETA', 'EEG EEG2-ALPHA', 'EEG EEG2-BETA', 'EEG EEG2-BSR', 'EEG EEG3-AMPL', 'EEG EEG3-SEF', 'EEG EEG3-MF', 'EEG EEG3-DELTA', 'EEG EEG3-THETA', 'EEG EEG3-ALPHA', 'EEG EEG3-BETA', 'EEG EEG3 BSR', 'EEG EEG4-AMPL', 'EEG EEG4-SEF', 'EEG EEG4-MF', 'EEG EEG4-DELTA', 'EEG EEG4-THETA', 'EEG EEG4-ALPHA', 'EEG EEG4-BETA', 'EEG EEG4-BSR', 'EEG: MOD', 'EEG: ACT', 'EEG: MSN', 'EEG: MONTAGE', 'EEG: HEAD', 'EEG: SSEP', 'EEG: CH1-LEADS', 'EEG: CH2-LEADS', 'EEG: CH3-LEADS', 'EEG: CH4-LEADS', 'EEG: CH1-ARTF', 'EEG: CH2-ARTF', 'EEG: CH3-ARTF', 'EEG: CH4-ARTF', 'EEG: CH1-NS', 'EEG: CH2-NS', 'EEG: CH3-NS', 'EEG: CH4-NS', 'EEG: EP', 'EEG: MSN', 'EEG-BIS', 'EEG-BIS SQI', 'EEG-BIS EMG', 'EEG-BIS SR', 'EEG-BIS: MOD', 'EEG-BIS: ACT', 'ENTROPY SE', 'ENTROPY RE', 'ENTROPY BSR', 'ENTROPY: MOD', 'ENTROPY: ACT', 'EEG2 COMMON', 'EEG2 CH1M', 'EEG2 CH1P', 'EEG2 CH2M', 'EEG2 CH2P', 'EEG2 CH3M', 'EEG2 CH3P', 'EEG2 CH4M', 'EEG2 CH4P', 'EEG2: MOD', 'EEG2: ACT', 'GASEX VO2', 'GASEX VCO2', 'GASEX EE', 'GASEX RQ', 'GASEX: MOD', 'GASEX: ACT', 'FLOW-VOL2 IPEEP', 'FLOW-VOL2 Pmean', 'FLOW-VOL2 RAW', 'FLOW-VOL2 MVINSP', 'FLOW-VOL2 EPEEP', 'FLOW-VOL2 MVESEX', 'FLOW-VOL2 IERATIO', 'FLOW-VOL2 ISPTIME', 'FLOW-VOL2 EXPTIME', 'FLOW-VOL2 STCCOMP', 'FLOW-VOL2 STCPPLAT', 'FLOW-VOL2 STCPEEPE', 'FLOW-VOL2 STCPEEPI', 'FLOW-VOL2: MOD', 'FLOW-VOL2: ACT', 'BAL-GAS ET', 'BAL-GAS FI', 'BAL-GAS: MOD', 'BAL-GAS: ACT', 'TONO PrCO2', 'TONO P(r-Et)CO2', 'TONO P(r-a)CO2', 'TONO PADELAY', 'TONO PHI', 'TONO PHIDELAY', 'TONO PAMB', 'TONO CMPA', 'TONO: MOD', 'TONO: ACT', 'TONO: LEAK', 'TONO: VOLDR', 'TONO: TECHFAIL', 'TONO: UNFILL', 'TONO: OVER', 'AA2 MAC-AGE-SUM', 'AA2: MOD', 'AA2: ACT']
All waveforms: ['ECG1', 'ECG2', 'ECG3', 'INVP1', 'INVP2', 'INVP3', 'INVP4', 'INVP5', 'INVP6', 'PLETH', 'CO2', 'N2O', 'AA_WAVE', 'AWP', 'FLOW', 'VOL', 'RESP', 'EEG1', 'EEG2', 'EEG3', 'EEG4', 'TONO_PRESS', 'SPI_LOOP_STATUS', 'ENT_100', 'EEG_BIS']

Get all measures from desired group.

group_aa = [g['label'] for g in measures.GROUPS_DICT['AA']]
print('All measures from group AA: {}'.format(group_aa))

All measures from group AA: ['AA ET', 'AA FI', 'AA MAC-SUM', 'AA: MOD', 'AA: ACT', 'AA: CLBR', 'AA: MNS', 'AA']

Inspect a single measure from subrecord or waveform.

# Information about ``AA ET`` (Subrecord)
print('AA ET: {}'.format(measures.LABEL_TO_DICT['AA ET']))

# Information about ``ECG1`` (Waveforms)
print('ECG1: {}'.format(measures.WAVEFORMS_DICT['ECG1']))

AA ET: {'label': 'AA ET', 'name': 'FeAA', 'desc': 'Anesthesia Agents ET', 'key': 'aa:et', 'unit': '%', 'shift': 0.01, 'subclass': 'basic'}
ECG1: {'label': 'ECG1', 'desc': '', 'unit': 'mV', 'shift_': 0.001, 'samps': 300, 'transducer': '', 'prefilter': '', 'physical_min': -0.001, 'physical_max': 0.001}

Other control funtions¶

# Stop data tranfer from monitor
device.stop()

# Close serial port
device.close()

# Stop internal asynchronous process
device.collect(False)
decoder.process(False)

# Restart decode process
device.collect(True)
decoder.BUFFER = device.BUFFER  #Force reference
decoder.process(True)

# Clear buffer, will require 'restart decode process'
device.clear_buffer()
decoder.clear_data()
decoder.clear_buffer()

PyCollect¶

Navigation¶

Getting started¶

Install¶

From source¶

From PyPi (not available yet)¶

Collect data¶

Connection¶

Send request¶

Subrecords¶

Waveforms¶

Mixings¶

Read data¶

Decode data¶

Clear buffers¶

Save data¶

Save data as CSV¶

Save data as EDF+¶

Measures¶

Physiological measures¶

ECG¶

INV-BP¶

NIBP¶

TEMP¶

SpO2¶

CO2¶

O2¶

N2O¶

AA¶

FLOW-VOL¶

CO-WEDGE¶

NMT¶

ECG-EXTRA¶

SvO2¶

ECG-ARRH¶

ECG-12¶

NMT2¶

EEG¶

EEG-BIS¶

ENTROPY¶

EEG2¶

GASEX¶

FLOW-VOL2¶

BAL-GAS¶

TONO¶

AA2¶

Waveform measures¶

Headers¶

Datex Header¶

GE Decode¶

GE Device¶

Examples¶

Read RAW file¶

Read from monitor¶

Save data¶

Save data as CSV¶

Save data as EDF+¶

Save RAW data¶

Channels information¶

Other control funtions¶

Indices and tables¶

References¶