README.md

In rickeycarter/easyRecg: Simple tools to facilitate reading and writing digital ECG files

easyRecg

easyRecg is designed to host simple tools to facilitate reading and writing digital ECG files.

Installation

You can install the development version of easyRecg from GitHub with:

# install.packages("devtools")
devtools::install_github("rickeycarter/easyRecg")

library(easyRecg)
library(tibble)

Retrieving 12-lead data

A matrix with data for 12-leads can be generated using the function read_muse_xml_ecg:

# Get sample file
file1 <- ecg_example("muse/muse_ecg1.xml")

# Read xml file - return a 2d matrix
ecg1_2d <- read_muse_xml_ecg(file1, numpyformat = F)

dim(ecg1_2d)
#> [1] 5000   12

head(ecg1_2d)
#>        I  II III  aVR aVL aVF V1  V2  V3  V4  V5  V6
#> [1,] 156 214  58 -185  48 136 68 204 390 312 165 126
#> [2,] 156 214  58 -185  48 136 68 204 390 312 165 126
#> [3,] 156 214  58 -185  48 136 68 204 390 312 165 126
#> [4,] 156 214  58 -185  48 136 68 204 390 312 165 126
#> [5,] 165 219  53 -192  56 136 68 219 400 322 175 131
#> [6,] 165 224  58 -195  53 141 68 224 409 331 185 136

# Instead, return a 4d array formatted for AI inputs
ecg1_4d <- read_muse_xml_ecg(file1, numpyformat = T)

dim(ecg1_4d)
#> [1]    1 5000   12    1

A directory of ecg files can be read and returned as an array using the read_muse_xml_directory function:

# Sample directory of muse files
muse_dir <- system.file("extdata", path = "muse", package = "easyRecg")

# Check number of files 
length(dir(muse_dir))
#> [1] 3

# Read xml files
all_muse <- read_muse_xml_directory(muse_dir)
#> A total of  3  ecgs were located.  Preparing to read.
#> ECGs successfully read.  Returned object includes numeric array and listing of files in the order of the array.

names(all_muse)
#> [1] "ecg_array"   "array_order"
dim(all_muse$ecg_array)
#> [1]    3 5000   12    1

Retrieving Meta Data

For more information on how to filter the provided meta data, please see the “Filtering Meta Data” vignette.

meta1 <- read_muse_xml_meta(file1, ids = 1)
meta1
#> $muse_info
#> # A tibble: 1 × 2
#>      id muse_version
#>   <dbl> <chr>       
#> 1     1 9.0.9.18167 
#> 
#> $patient_demographics
#> # A tibble: 1 × 6
#>      id patient_id patient_age age_units gender patient_last_name
#>   <dbl> <chr>      <chr>       <chr>     <chr>  <chr>            
#> 1     1 JAX01234   60          YEARS     MALE   TEST 05          
#> 
#> $test_demographics
#> # A tibble: 1 × 24
#>      id data_type site  site_name acquisition_device status    edit_list_status
#>   <dbl> <chr>     <chr> <chr>     <chr>              <chr>     <chr>           
#> 1     1 RESTING   11    Research  MAC55              CONFIRMED Confirmed       
#> # … with 17 more variables: priority <chr>, location <chr>,
#> #   location_name <chr>, acquisition_time <chr>, acquisition_date <chr>,
#> #   cart_number <chr>, acquisition_software_version <chr>,
#> #   analysis_software_version <chr>, edit_time <chr>, edit_date <chr>,
#> #   overreader_id <chr>, editor_id <chr>, overreader_last_name <chr>,
#> #   overreader_first_name <chr>, editor_last_name <chr>,
#> #   editor_first_name <chr>, his_status <chr>
#> 
#> $resting_ecg_measurements
#> # A tibble: 1 × 19
#>      id ventricular_rate atrial_rate pr_interval qrs_duration qt_interval
#>   <dbl> <chr>            <chr>       <chr>       <chr>        <chr>      
#> 1     1 60               60          158         78           364        
#> # … with 13 more variables: qt_corrected <chr>, p_axis <chr>, r_axis <chr>,
#> #   t_axis <chr>, qrs_count <chr>, q_onset <chr>, q_offset <chr>,
#> #   p_onset <chr>, p_offset <chr>, t_offset <chr>, ecg_sample_base <chr>,
#> #   ecg_sample_exponent <chr>, q_tc_frederica <chr>
#> 
#> $original_resting_ecg_measurements
#> # A tibble: 1 × 19
#>      id ventricular_rate atrial_rate pr_interval qrs_duration qt_interval
#>   <dbl> <chr>            <chr>       <chr>       <chr>        <chr>      
#> 1     1 60               60          158         78           364        
#> # … with 13 more variables: qt_corrected <chr>, p_axis <chr>, r_axis <chr>,
#> #   t_axis <chr>, qrs_count <chr>, q_onset <chr>, q_offset <chr>,
#> #   p_onset <chr>, p_offset <chr>, t_offset <chr>, ecg_sample_base <chr>,
#> #   ecg_sample_exponent <chr>, q_tc_frederica <chr>
#> 
#> $diagnosis
#> # A tibble: 1 × 8
#>      id modality diagnosis_statement_stmt_flag diagnosis_state… diagnosis_state…
#>   <dbl> <chr>    <chr>                         <chr>            <chr>           
#> 1     1 RESTING  ENDSLINE                      Statement Text(… ENDSLINE        
#> # … with 3 more variables: diagnosis_statement_stmt_text_2 <chr>,
#> #   diagnosis_statement_stmt_flag_3 <chr>,
#> #   diagnosis_statement_stmt_text_3 <chr>
#> 
#> $original_diagnosis
#> # A tibble: 1 × 8
#>      id modality diagnosis_statement_stmt_flag diagnosis_state… diagnosis_state…
#>   <dbl> <chr>    <chr>                         <chr>            <chr>           
#> 1     1 RESTING  ENDSLINE                      Statement Text(… ENDSLINE        
#> # … with 3 more variables: diagnosis_statement_stmt_text_2 <chr>,
#> #   diagnosis_statement_stmt_flag_3 <chr>,
#> #   diagnosis_statement_stmt_text_3 <chr>
#> 
#> $qrs_times_types
#> # A tibble: 1 × 33
#>      id qrs_number qrs_type qrs_time qrs_number_2 qrs_type_2 qrs_time_2
#>   <dbl> <chr>      <chr>    <chr>    <chr>        <chr>      <chr>     
#> 1     1 1          0        808      2            0          1810      
#> # … with 26 more variables: qrs_number_3 <chr>, qrs_type_3 <chr>,
#> #   qrs_time_3 <chr>, qrs_number_4 <chr>, qrs_type_4 <chr>, qrs_time_4 <chr>,
#> #   qrs_number_5 <chr>, qrs_type_5 <chr>, qrs_time_5 <chr>, qrs_number_6 <chr>,
#> #   qrs_type_6 <chr>, qrs_time_6 <chr>, qrs_number_7 <chr>, qrs_type_7 <chr>,
#> #   qrs_time_7 <chr>, qrs_number_8 <chr>, qrs_type_8 <chr>, qrs_time_8 <chr>,
#> #   qrs_number_9 <chr>, qrs_type_9 <chr>, qrs_time_9 <chr>,
#> #   qrs_number_10 <chr>, qrs_type_10 <chr>, qrs_time_10 <chr>, …
#> 
#> $pharma_data
#> # A tibble: 1 × 5
#>      id pharma_r_rinterval pharma_unique_ecgid   pharma_p_pinter… pharma_cart_id
#>   <dbl> <chr>              <chr>                 <chr>            <chr>         
#> 1     1 1000               SCD06526477PA1005202… 1000             SCD06526477PA

Data Sources

ECG XML files included in this package are simulated and do not represent actual patient evaluations.

rickeycarter/easyRecg documentation built on Dec. 22, 2021, 4:09 p.m.