MPI Summary

Description

MPI Summary

Usage

MPI_summary(input, recursive = TRUE, identifier_mapping_record = NULL)

Arguments

Details

Wrapper function that calls create_summary for MPI only.

Value

Data frame of MPI summary.

Write MPI to JSON

Description

Write MPI to JSON

Usage

MPI_toJSON(MPI, mpi_path)

Arguments

Details

Restructures the MPI and writes it out to a JSON for ActivInsights internal use.

Value

MPI JSON file written to the same directory as the MPI RDS.

Aggregate Epochs

Description

Aggregate Epochs

Usage

aggregate_epochs(
  time_series,
  measure = "AGSA",
  time = "timestamp",
  sample_frequency,
  duration = NA,
  first_epoch_timestamp = NA,
  fun = mean
)

aggregateEpochs(...)

Arguments

Details

Wrapper function that calls aggregate_periods for epochs (duration of fixed length).

Value

Data frame of aggregated epochs.

Examples

timestamp <- c(
  1619424004, 1619424005, 1619424006, 1619424007,
  1619424008, 1619424009, 1619424010, 1619424011,
  1619424012, 1619424013, 1619424014, 1619424015
)
value <- c(
  0.729614366, 1.729115871, 0.804973546, 2.510181118,
  2.23764038, 0.613203747, 0.681953275, 0.089566943,
  0.021042388, 2.4780338, 2.437488989, 2.632635727
)
data <- data.frame(timestamp, value)
aggregated <- aggregate_epochs(data,
  duration = 5,
  measure = "value",
  sample_frequency = 1,
  first_epoch_timestamp = 1619424005,
  time = "timestamp"
)

Aggregate Events

Description

Aggregate Events

Usage

aggregate_events(
  time_series,
  measure = "AGSA",
  time = "timestamp",
  sample_frequency,
  events = NA,
  start_time = "start",
  end_time = "end",
  fun = mean
)

aggregateEvents(...)

aggregatePeriods(...)

createEventMapping(...)

Arguments

Details

Wrapper function that calls aggregate_periods for events (duration of variable length).

Value

Data frame of aggregated events.

Examples

timestamp <- c(
  1619424004, 1619424005, 1619424006, 1619424007,
  1619424008, 1619424009, 1619424010, 1619424011,
  1619424012, 1619424013, 1619424014, 1619424015
)
value <- c(
  0.729614366, 1.729115871, 0.804973546, 2.510181118,
  2.23764038, 0.613203747, 0.681953275, 0.089566943,
  0.021042388, 2.4780338, 2.437488989, 2.632635727
)
data <- data.frame(timestamp, value)
event_start <- c(1, 5, 10)
event_end <- c(4, 9, 12)
aggregated_events <- aggregate_events(data,
  events = data.frame(start = event_start, end = event_end),
  measure = "value",
  time = "timestamp",
  start_time = "start",
  end_time = "end",
  sample_frequency = 1,
  fun = sum
)

Aggregate Periods

Description

Generalised aggregation function generates distinct epochs or events outputs based on the initial parameters provided.

Usage

aggregate_periods(
  time_series,
  measure = "AGSA",
  time = "timestamp",
  sample_frequency,
  duration = NA,
  first_epoch_timestamp = NA,
  events = NA,
  start_time = "start",
  end_time = "end",
  fun = mean
)

Arguments

Value

Data frame of aggregated epochs or events.

Apply Absolute Gravity-Subtracted Acceleration (AGSA)

Description

Apply Absolute Gravity-Subtracted Acceleration (AGSA)

Usage

apply_AGSA(x)

Arguments

Value

Measure column appended to end of calibrated data frame.

Examples

x <- c(0.14268, 0.21757, -0.529, -0.36383)
y <- c(0.26385, 0.27295, 0.29220, 0.79510)
z <- c(0.27722, 0.20296, 0.35092, 0.27459)
calibrated <- data.frame(x, y, z)
calibrated <- apply_AGSA(calibrated)

Apply Euclidean Norm Minus One (ENMO)

Description

Apply Euclidean Norm Minus One (ENMO)

Usage

apply_ENMO(x)

Arguments

Value

Measure column appended to end of calibrated data frame.

Examples

x <- c(0.14268, 0.21757, -0.529, -0.36383)
y <- c(0.26385, 0.27295, 0.29220, 0.79510)
z <- c(0.27722, 0.20296, 0.35092, 0.27459)
calibrated <- data.frame(x, y, z)
calibrated <- apply_ENMO(calibrated)

Apply AGSA, ENMO, UpDown and Degrees

Description

Single function that combines calculations for acceleration, elevation and rotation measures.

Usage

apply_all(x)

Arguments

Value

Measures columns appended to end of calibrated data frame.

Examples

x <- c(0.14268, 0.21757, -0.529, -0.36383)
y <- c(0.26385, 0.27295, 0.29220, 0.79510)
z <- c(0.27722, 0.20296, 0.35092, 0.27459)
calibrated <- data.frame(x, y, z)
calibrated <- apply_all(calibrated)

Apply Calibration

Description

Apply Calibration

Usage

apply_calibration(sensor_data, cal_params, measurement_device, use_temp = TRUE)

Arguments

Details

Function to apply calibration to sensor-level data from a bin file.

Value

Data frame of calibrated sensor data.

Examples

cal_params <- list(
  scale = c(1.015, 1.017, 1.027),
  offset = c(0.00128, 0.0383, 0.0138),
  temperature_offset = c(0, 0, 0),
  error = NA,
  light_denominator = 48,
  light_numerator = 911
)

rawdata <- data.frame(
  time = c(rep(1726650857, 5)),
  x = c(0.2421875, 0.24609375, 0.25390625, 0.24609375, 0.23828125),
  y = c(-0.04296875, -0.04687500, -0.03515625, -0.03125000, -0.04296875),
  z = c(-0.9453125, -0.9453125, -0.9531250, -0.9531250, -0.9609375),
  light = c(rep(22, 5)),
  button = c(rep(0, 5)),
  temp = c(rep(21.3, 5)),
  volts = c(rep(4.0896, 5))
)
calibrated <- apply_calibration(rawdata, cal_params, "GENEActiv 1.1")

Apply Rotation (Degrees)

Description

Apply Rotation (Degrees)

Usage

apply_degrees(x)

Arguments

Value

Measure column appended to end of calibrated data frame.

Examples

x <- c(0.14268, 0.21757, -0.529, -0.36383)
y <- c(0.26385, 0.27295, 0.29220, 0.79510)
z <- c(0.27722, 0.20296, 0.35092, 0.27459)
calibrated <- data.frame(x, y, z)
calibrated <- apply_degrees(calibrated)

Apply Rotation (radians)

Description

Apply Rotation (radians)

Usage

apply_radians(x)

Arguments

Value

Measure column appended to end of calibrated data frame.

Examples

x <- c(0.14268, 0.21757, -0.529, -0.36383)
y <- c(0.26385, 0.27295, 0.29220, 0.79510)
z <- c(0.27722, 0.20296, 0.35092, 0.27459)
calibrated <- data.frame(x, y, z)
calibrated <- apply_radians(calibrated)

Apply Elevation (UpDown)

Description

Apply Elevation (UpDown)

Usage

apply_updown(x)

Arguments

Value

Measure column appended to end of calibrated data frame.

Examples

x <- c(0.14268, 0.21757, -0.529, -0.36383)
y <- c(0.26385, 0.27295, 0.29220, 0.79510)
z <- c(0.27722, 0.20296, 0.35092, 0.27459)
calibrated <- data.frame(x, y, z)
calibrated <- apply_updown(calibrated)

Bin File Summary

Description

Bin File Summary

Usage

binfile_summary(input, recursive = TRUE, identifier_mapping_record = NULL)

Arguments

Details

Wrapper function that calls create_summary for bin files only.

Value

Data frame of bin file or MPI summary.

Bouts Decision Tree

Description

Bouts Decision Tree

Usage

bouts_decision_tree(
  bouts,
  SDduration_threshold = 5.7e-05,
  AGSA_threshold = 0.0625,
  running_threshold = 0.407
)

Arguments

Value

Classified bouts

Calculate Auto-calibration Parameters

Description

Function to calculate auto-calibration parameters from known still points from a bin file that create a unitary sphere.

Usage

calc_autocalparams(
  binfile,
  binfile_path,
  output_folder,
  sphere_points,
  use_temp = TRUE,
  spherecrit = 0.3,
  maxiter = 500,
  tol = 1e-13
)

Arguments

Value

List of auto-calibration parameters within the measurement period information (MPI).

Examples

binfile_path <- system.file("extdata/10Hz_calibration_file_20Nov25.bin", package = "GENEAcore")
output_folder <- tempdir()
con <- file(binfile_path, "r")
binfile <- readLines(con, skipNul = TRUE)
close(con)
MPI <- create_MPI(binfile, binfile_path, output_folder)
nonmovement_list <- detect_nonmovement(binfile, binfile_path, output_folder)
MPI <- calc_autocalparams(
  binfile, binfile_path, output_folder,
  nonmovement_list$non_movement$sphere_points
)

Calculate Daily Activity Measures

Description

Calculate Daily Activity Measures

Usage

calculate_daily_activity_measures(
  MPI,
  daily_bouts,
  minimum_valid_hours = 22,
  include_participant_info = FALSE
)

Arguments

Details

Function that calculates the daily activity measures only

Value

Activity measures data frame for all days

Calculate Daily Sleep Measures

Description

Calculate Daily Sleep Measures

Usage

calculate_daily_sleep_measures(
  MPI,
  daily_bouts,
  minimum_valid_hours = 22,
  include_participant_info = FALSE
)

Arguments

Details

Function that calculates the daily sleep measures only

Value

Sleep measures data frame for all days

Print out a summary of MPI file(s)

Description

Function to print out a summary of an MPI (Measurement Process Information) file, or all MPI files found if a directory path is supplied.

Usage

check_MPI(input, print_output = TRUE)

Arguments

Examples

## Not run: 
check_MPI("fully qualified path to a directory structure containing MPI files")
check_MPI("fully qualified path to a MPI file")

## End(Not run)

Check Time Format

Description

Check Time Format

Usage

check_time_format(time_str)

Arguments

Details

Internal function to parse and check validity of time string passed as parameter.

Value

Valid time string or error.

Create Measurement Period Information

Description

Create Measurement Period Information

Usage

create_MPI(binfile, binfile_path, output_folder, out_rds = TRUE)

Arguments

Details

Function to create measurement period information (MPI) from a GENEActiv bin file

Value

List of measurement period information.

Examples

binfile_path <- system.file("extdata/10Hz_calibration_file_20Nov25.bin", package = "GENEAcore")
con <- file(binfile_path, "r")
binfile <- readLines(con, skipNul = TRUE)
close(con)
output_folder <- tempdir()
MPI <- create_MPI(binfile, binfile_path, output_folder, out_rds = FALSE)

Create COEL Behavioural Atoms JSON

Description

Creates per-participant rest activity and behavioural bout atoms and a payload

Usage

create_coel_atoms_json(data_folder)

Arguments

Create Event Mapping

Description

Create Event Mapping

Usage

create_event_mapping(events, start_time, end_time, max_row_number)

Arguments

Details

Enumerate a vector to identify which event each measurement belongs to.

Value

List of mapped events.

Examples

events <- data.frame(
  "start" = c(1, 5, 10, 15),
  "end" = c(4, 9, 14, 19)
)
time_series <- rnorm(25)
period_number <- create_event_mapping(events, "start", "end", length(time_series))

Create Summary

Description

Create Summary

Usage

create_summary(
  input,
  path_type,
  recursive = TRUE,
  identifier_mapping_record = NULL
)

Arguments

Details

Function to create a summary of key information of a bin file or MPI path.

Value

Data frame of bin file or MPI summary.

Compute Cx percentile

Description

Compute Cx percentile

Usage

cx_percentile(
  bouts,
  percentile = 95,
  value_col = "StepMean",
  duration_col = "Duration"
)

Arguments

Details

Calculates the xth percentile of cadence for a given percentile.

Value

A single numeric value or NA if percentile cannot be calculated

Detect Non-movement

Description

Detect Non-movement

Usage

detect_nonmovement(
  binfile,
  binfile_path,
  output_folder,
  still_seconds = 120,
  sd_threshold = 0.013,
  temp_seconds = 240,
  border_seconds = 300,
  long_still_seconds = 120 * 60,
  delta_temp_threshold = -0.7,
  posture_changes_max = 2,
  non_move_duration_max = 12 * 60 * 60
)

Arguments

Details

Function to detect non-movement events, non-wear events and sphere points from a 1Hz downsampled bin file.

Value

List of sphere points, non-movement events and non-wear events.

Examples

binfile_path <- system.file("extdata/10Hz_calibration_file_20Nov25.bin", package = "GENEAcore")
con <- file(binfile_path, "r")
binfile <- readLines(con, skipNul = TRUE)
close(con)
output_folder <- tempdir()
MPI <- create_MPI(binfile, binfile_path, output_folder)
MPI <- detect_nonmovement(binfile, binfile_path, output_folder)

Detect Transitions

Description

Detect Transitions

Usage

detect_transitions(
  measurements,
  minimum_event_duration = 5,
  x_cpt_penalty = 18,
  y_cpt_penalty = 25,
  z_cpt_penalty = 16,
  cut_time_24hr = "15:00"
)

Arguments

Details

Function to detect mean and variance changepoints in 1Hz acceleration data from a bin file.

Value

List of time and index of each transition.

Calculate Expected Last Timestamp

Description

Calculate Expected Last Timestamp

Usage

expected_last_timestamp(measurement_frequency, page_count, first_timestamp)

Arguments

Details

Calculates the expected last timestamp of a file based on measurement frequency, page count and first timestamp of file.

Value

Expected last timestamp

Determine Daily Recommended Primary Rest Interval

Description

Determine Daily Recommended Primary Rest Interval

Usage

find_rest_intervals(
  start_expansion_percent,
  end_expansion_percent,
  cut_time_24hr,
  MPI
)

Arguments

Details

Twice the expansion before than after.

Daily Measures for Data Folder

Description

Daily Measures for Data Folder

Usage

folder_measures(
  data_folder,
  measure_type = c("activity", "sleep", "both"),
  minimum_valid_hours = 22,
  include_participant_info = FALSE,
  identifier_mapping_record = NULL
)

Arguments

Details

Wrapper to process and output daily activity measures aggregate for all bin files in the data folder

Value

Daily aggregated activity measures (.csv)

Compute Fx metrics

Description

Compute Fx metrics

Usage

fx_count(bouts, AGSA_threshold = 0.0625, duration = 3600)

Arguments

Details

Calculates frequency of bouts for each x duration window.

Value

A list containing the maximum and minimum bout counts and their corresponding start times for the supplied bouts data at a given window.

GENEAbout

Description

GENEAbout function which performs the following tasks for each available day:

• Assign bout classifications to events only

• Reports aggregated daily activity and sleep measures

• Creates COEL v2.0 Behavioural Atoms JSON

Usage

geneabout(data_folder = data_folder, control = list())

Arguments

Details

Control options (all optional):

timer

Logical. Default FALSE. Print elapsed times of each processing step.

minimum_valid_hours

Integer. Default 22. Minimum hours of wear time in a 24-hour day to be considered a valid day for reported measures.

save_daily_bouts

Logical. Default FALSE. If TRUE,daily bouts are saved as RDS files and CSV files (if output_csv is set to TRUE). If FALSE, only a single RDS file containing bouts for all processed days is saved.

coel_json

Logical. Default FALSE. Exports bouts as COEL behavioural atoms in JSON format. For each bin file in the data folder, behavioural bout atoms and rest activity atoms are produced. Additionally, aggregated JSON files are created in the ⁠Batch JSON outputs⁠ subfolder.

identifier_mapping_record

String. Default NULL. If a file path to the exported identifier_mapping_record.csv is provided, encrypted participant IDs in the activity and sleep measures will be replaced with their corresponding mapped identifiers.

Examples

## Not run: 
controls <- list(minimum_valid_hours = 4, timer = TRUE, coel_json = TRUE)
geneabout("path/to/folder", controls)

## End(Not run)

GENEAcore Main Wrapper

Description

GENEAcore function that wraps the functionalities of geneacore_part1 to geneacore_part4. GENEAcore function which performs the following tasks for each valid day:

• Checks and reads the data file and creates the Measurement Period Information (MPI)

• Downsamples the file to 1Hz and detects periods of non movement

• Calculates auto calibration parameters for the device

• Samples daily raw bin file data and saves as daily RDS files

• Reads and saves button press timestamps to the Measurement Period Information (MPI)

• Applies calibration parameters to raw data

• Identifies transitions for events processing only

• Performs aggregation by event and/or epoch

• Calculate steps, if option selected

• Calculate non-wear coverage and rest coverage of events and/or epochs

• Assign bout classifications to events only

• Reports aggregated daily activity and sleep measures

• Consolidates daily epochs or bouts outputs into a single file

Usage

geneacore(data_folder = data_folder, control = list())

Arguments

Details

Control options (all optional):

cut_time_24hr

String. Default "15:00". Time in 24h to split days up by.

output_epochs

Logical. Default FALSE. Create epoch outputs.

epoch_duration

Integer. Default 1. Specify duration of fixed epochs.

output_events

Logical. Default TRUE. Create event outputs.

output_steps

Logical. Default FALSE. Calculate step counts and stepping rate during epoch processing. Steps are always calculated during events processing.

output_csv

Logical. Default FALSE. Allows CSV output to be saved during epoch and event processing.

timer

Logical. Default FALSE. Print elapsed times of each processing step.

multisession

Integer vector of length 2. Default c(1,1). Controls day split when running function across multiple R sessions. The first value is the current session number and the second is the total number of sessions. The default processes all days in a single session.

required_processing_hours

Integer. Default 0. Hours of wear time in a 24-hour day to be considered a valid day to be processed.

Examples

## Not run: 
controls <- list(output_csv = TRUE, required_processing_hours = 4, timer = TRUE)
geneacore("path/to/folder", controls)

## End(Not run)

GENEAcore Part 1

Description

GENEAcore function which performs the following tasks:

• Checks and reads the data file and creates the Measurement Period Information (MPI)

• Downsamples the file to 1Hz and detects periods of non movement

• Calculates auto calibration parameters for the device

Usage

geneacore_part1(data_folder = data_folder, control = list())

Arguments

Details

Control options (all optional):

cut_time_24hr

String. Default "15:00". Time in 24h to split days up by.

timer

Logical. Default FALSE. Print elapsed times of each processing step.

Value

Measurement Period Information (.rds, .json) and 1Hz downsampled data (.rds)

Examples

## Not run: 
controls <- list(output_csv = TRUE, required_processing_hours = 4, timer = TRUE)
geneacore_part1("path/to/folder", controls)

## End(Not run)

GENEAcore Part 2

Description

GENEAcore function which performs the following tasks for each valid day:

• Samples daily raw bin file data and saves as daily RDS files

• Reads and saves button press timestamps to the Measurement Period Information (MPI)

Usage

geneacore_part2(data_folder = data_folder, control = list())

Arguments

Details

Control options (all optional):

required_processing_hours

Integer. Default 0. Hours of wear time in a 24-hour day to be considered a valid day to be processed.

timer

Logical. Default FALSE. Print elapsed times of each processing step.

Value

Daily raw data sample of x, y, z, Light, Button, Temperature and Voltage (.rds)

Examples

## Not run: 
controls <- list(output_csv = TRUE, required_processing_hours = 4, timer = TRUE)
geneacore_part2("path/to/folder", controls)

## End(Not run)

GENEAcore Part 3

Description

GENEAcore function which performs the following tasks for each valid day:

• Applies calibration parameters to raw data

• Identifies transitions for events processing only

• Performs aggregation by event and/or epoch

• Calculate steps, if option selected

• Calculate non-wear coverage and rest coverage of events and/or epochs

Usage

geneacore_part3(data_folder = data_folder, control = list())

Arguments

Details

Control options (all optional):

output_epochs

Logical. Default FALSE. Create epoch outputs.

epoch_duration

Integer. Default 1. Specify duration of fixed epochs.

output_events

Logical. Default TRUE. Create event outputs.

output_steps

Logical. Default FALSE. Calculate step counts and stepping rate during epoch processing. Steps are always calculated during events processing.

output_csv

Logical. Default FALSE. Allows CSV output to be saved during epoch and event processing.

timer

Logical. Default FALSE. Print elapsed times of each processing step.

multisession

Integer vector of length 2. Default c(1,1). Controls day split when running function across multiple R sessions. The first value is the current session number and the second is the total number of sessions. The default processes all days in a single session.

required_processing_hours

Integer. Default 0. Hours of wear time in a 24-hour day to be considered a valid day to be processed.

Examples

## Not run: 
controls <- list(output_csv = TRUE, required_processing_hours = 4, timer = TRUE)
geneacore_part3("path/to/folder", controls)

## End(Not run)

GENEAcore Part 4

Description

GENEAcore function which performs the following tasks:

• Consolidates daily epochs or bouts outputs into a single file

Usage

geneacore_part4(data_folder = data_folder, control = list())

Arguments

Details

Control options (all optional):

output_epochs

Logical. Default TRUE. Create epoch outputs.

epoch_duration

Integer. Default 1. Specify duration of fixed epochs.

output_events

Logical. Default TRUE. Create event outputs.

output_csv

Logical. Default FALSE. Allows CSV output to be saved during epoch and event processing.

Value

Consolidated epochs and/or bouts output (.rds/.csv)

Examples

## Not run: 
controls <- list(output_csv = TRUE, minimum_valid_hours = 4, timer = TRUE)
geneacore_part4("path/to/folder", controls)

## End(Not run)

Generate Unique Bin File Identifier

Description

Generate Unique Bin File Identifier

Usage

get_UniqueBinFileIdentifier(binfile)

Arguments

Details

Function to create a UniqueBinFileIdentifier from a GENEActiv bin file.

Value

Single string identifier.

Examples

binfile_path <- system.file("extdata/10Hz_calibration_file_20Nov25.bin", package = "GENEAcore")
con <- file(binfile_path, "r")
binfile <- readLines(con, skipNul = TRUE)
close(con)
UniqueBinFileIdentifier <- get_UniqueBinFileIdentifier(binfile)

Generate Unique Bin File Identifier for each bin file within a directory path

Description

Generate Unique Bin File Identifier for each bin file within a directory path

Usage

get_UniqueBinFileIdentifier.dir(binfile_directory)

Arguments

Details

Function to create a UniqueBinFileIdentifier from a GENEActiv bin file.

Value

Named vector, the vector name is the filename and the value the identifier.

Examples

binfile_directory <- system.file("extdata", package = "GENEAcore")
UniqueBinFileIdentifiers <- get_UniqueBinFileIdentifier.dir(binfile_directory)

Generate Unique Bin File Identifier from a file path

Description

Generate Unique Bin File Identifier from a file path

Usage

get_UniqueBinFileIdentifier.filepath(binfile_path)

Arguments

Details

Function to create a UniqueBinFileIdentifier from a GENEActiv bin file.

Value

Single string identifier.

Examples

binfile_path <- system.file("extdata/10Hz_calibration_file_20Nov25.bin", package = "GENEAcore")
UniqueBinFileIdentifier <- get_UniqueBinFileIdentifier.filepath(binfile_path)

Generate Unique Bin File Identifier

Description

Generate Unique Bin File Identifier

Usage

get_UniqueBinFileIdentifier.vector(binfile)

Arguments

Details

Function to create a UniqueBinFileIdentifier from a GENEActiv bin file.

Value

Single string identifier.

Examples

binfile_path <- system.file("extdata/10Hz_calibration_file_20Nov25.bin", package = "GENEAcore")
con <- file(binfile_path, "r")
binfile <- readLines(con, skipNul = TRUE)
close(con)
UniqueBinFileIdentifier <- get_UniqueBinFileIdentifier(binfile)

Get Cut Times

Description

Get Cut Times

Usage

get_cut_times(cut_time_24hr, MPI)

Arguments

Details

Internal function to determine the daily cut times based on 24Hr Cut Time specified.

Value

List of cut times in Unix UTC.

Get Decimal Places

Description

Get Decimal Places

Usage

get_decimal_places(column)

Arguments

Details

Internal function to determine the number of decimal places based on column name.

Value

Decimal place integer.

Get events from transitions for aggregation and step counter

Description

Get events from transitions for aggregation and step counter

Usage

get_events(time_series, transitions, sample_frequency)

Arguments

Map Study Management Hub Identifiers

Description

Map Study Management Hub Identifiers

Usage

identifier_mapping(x, cols_to_map, identifier_mapping_record)

Arguments

Compute Mx and Lx metrics

Description

Compute Mx and Lx metrics

Usage

mx_lx_window(bouts, window, low = TRUE)

Arguments

Details

Calculates intensity for each x duration window.

Value

A list containing the maximum and minimum mean intensity and their corresponding start times for the supplied bouts data at a given window.

Non-wear and Rest Coverage for Epochs/Events

Description

Non-wear and Rest Coverage for Epochs/Events

Usage

nonwear_rest_coverage(
  MPI,
  aggregated_data,
  start_time = NULL,
  end_time = NULL,
  nonwear_day
)

Arguments

Remove Short Transitions

Description

Remove Short Transitions

Usage

remove_short_transitions(cpts_var_df, cut_times, minimum_event_duration)

Arguments

Details

Identify and remove transitions shorter than the minimum event duration.

Value

Data frame of all transitions including start of day with short transitions removed.

Examples

changepoints <- data.frame(
  time = c(1677855218, 1677855598, 1677855661, 1677855679),
  index = c(86019, 86399, 62, 80))
cut_times <- data.frame(time = 1677855600, index = 1)
transitions <- remove_short_transitions(changepoints, cut_times, 5)

Reorder Data Frame

Description

Reorder Data Frame

Usage

reorder_df(df)

Arguments

Details

Internal function to remove the epoch_number or event_number columns and move duration column forward.

Value

Reordered data frame.

Round Columns

Description

Round Columns

Usage

round_columns(df)

Arguments

Details

Internal function to round columns based on column names or variability of data in column.

Value

Epochs or events data frame with rounded columns.

Sample Bin File

Description

Sample Bin File

Usage

sample_binfile(
  binfile,
  binfile_path,
  output_folder,
  start_time = NULL,
  end_time = NULL,
  downsample = TRUE,
  output_csv = FALSE,
  save_raw = FALSE
)

Arguments

Details

Function to read in a GENEActiv bin file with option to downsample to 1Hz. This can read the whole of the file or just a portion of it by setting the start_time and end_time parameters.

Value

List of 1Hz downsampled data or raw sample data.

Examples

binfile_path <- system.file("extdata/10Hz_calibration_file_20Nov25.bin", package = "GENEAcore")
output_folder <- tempdir()
con <- file(binfile_path, "r")
binfile <- readLines(con, skipNul = TRUE)
close(con)
measurements <- sample_binfile(binfile, binfile_path, output_folder)

Daily Measures for Single Bin File

Description

Daily Measures for Single Bin File

Usage

single_file_measures(
  output_folder,
  UniqueBinFileIdentifier,
  measure_type = c("activity", "sleep", "both"),
  minimum_valid_hours = 22,
  include_participant_info = FALSE,
  identifier_mapping_record = NULL
)

Arguments

Details

Wrapper to process and output daily activity measures aggregate for a single bin file

Value

Daily aggregated activity measures (.csv)

Step Counter

Description

Function to calculate the number and variance of the steps in the data.

Usage

step_counter(
  step_data,
  sample_frequency = 100,
  filter_order = 2,
  boundaries = c(0.5, 5),
  Rp = 3,
  step_hysteresis = 0.05,
  fun = c("GENEAcount", "mean", "sd", "stepdiff")
)

stepCounter(...)

Arguments

Value

Returns a vector with length fun.

Examples

d1 <- sin(seq(0.1, 100, 0.1)) / 2 + rnorm(1000) / 10 + 1
Steps4 <- step_counter(d1)
length(Steps4)
mean(Steps4)
sd(Steps4)
plot(Steps4)

Determine Valid Days

Description

Determine Valid Days

Usage

valid_day_nonwear(
  MPI_nonwear,
  date_range,
  required_processing_hours = 0,
  cut_time_24hr = "15:00"
)

Arguments

Details

Determine which days of data are valid days to process based on non-wear calculated in MPI and a minimum valid day duration.

Value

List of 2 data objects:

• valid_day provides information on the wear and non-wear duration for each day and its Boolean validity based on minimum_valid_day.

• nonwear_day provides the start and end time of each non-wear period and the day in which it occurs.

Weighted mean with logical index

Description

Computes the weighted mean of x using weights w, where idx is TRUE.

Usage

weighted_mean(x, w, idx)

Arguments

Value

A single numeric value. Returns NA if the sum of weights is 0.

Examples

idx_active <- c(TRUE, TRUE, FALSE, FALSE, FALSE, TRUE)
AGSA <- c(0.1, 0.2, 0.03, 0.04, 0.05, 0.6)
Duration <- c(100, 90, 80, 70, 60, 50)
ActiveIntensity <- weighted_mean(AGSA, Duration, idx_active)

Weighted sum with logical index

Description

Computes the weighted sum of x using weights w, where idx is TRUE.

Usage

weighted_sum(x, w, idx)

Arguments

Value

A single numeric value. Returns 0 if no TRUE values in idx.

Examples

idx_active <- c(TRUE, TRUE, FALSE, FALSE, FALSE, TRUE)
AGSA <- c(0.1, 0.2, 0.03, 0.04, 0.05, 0.6)
Duration <- c(100, 90, 80, 70, 60, 50)
ActiveVolume <- weighted_sum(AGSA, Duration, idx_active)