easyRecg is designed to host simple tools to facilitate reading and
writing digital ECG files.
You can install the development version of easyRecg from
GitHub with:
# install.packages("devtools")
devtools::install_github("rickeycarter/easyRecg")library(easyRecg)
library(tibble)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 1A 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 1For 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_diagnos
6A36
is
#> # 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 SCD06526477PAECG XML files included in this package are simulated and do not represent actual patient evaluations.