chms provides tools for cleaning and summarizing accelerometer data consistent with methods applied to cycle 7 of the Canadian Health Measures Survey (CHMS):
agd$new()initializes an R6 class with fields (data) and methods (functions) for processing Ametris (formerly ActiGraph) accelerometer data.agd$run()executes a pipeline that calls several methods:$load(),$clean(),$classify()and$summarize().agd$sanity_check()renders an html-formatted report of summary statistics per participant.
chms requires:
- two ActiGraph (.agd) files per participant, one processed with the normal filter (for step counts) and the other processed with the low frequency extension filter (for all other movement behaviour variables).
- accelerometer data at the 15-second epoch level for participants ≤ 17 years.
- accelerometer data at the 60-second epoch level or lower for participants ≥ 18 years.
- integer age of each participant.
By default, chms:
- removes incomplete days of data (< 24 hours).
- identifies sleep time, wear time and non-wear time by applying the Barreira algorithm to data at the 60-second epoch level.
- looks for sleep bouts beginning at 6pm (3-5 years) or 7pm (6+ years).
- identifies movement behaviours for eligible epochs (epochs previously classified as wear time and awake time) by applying the following cut-points to axis1 accelerometer counts at age-specific epoch levels:
| Age (years) | Epoch level (seconds) | SB cut-point (counts) | LPA cut-point (counts) | MPA cut-point (counts) | VPA cut-point (counts) |
|---|---|---|---|---|---|
| 3-4 | 15 | 0-24Evenson | 25-419Pate | 420+Pate | – |
| 5-17 | 15 | 0-24Evenson | 25-573Evenson | 574-1,002Evenson | 1,003+Evenson |
| 18-64 | 60 | 0-99Troiano | 100-2,019Troiano | 2,020-5,998Troiano | 5,999+Troiano |
| 65+ | 60 | 0-99Troiano | 100-2,019Troiano | 2,020-5,998Troiano | 5,999+Troiano |
SB: sedentary behaviour; LPA: light-intensity physical activity; MPA: moderate-intensity physical activity; VPA: vigorous-intensity physical activity.
- validates days (≥ 10 hours of wear time and ≥ 100 steps). Invalid days are excluded from waking hours results.
- validates nights of sleep (≥ 160 minutes of sleep). Invalid nights of sleep are excluded from sleeping hours results.
For more details on the methods used in the chms R package, see Clarke J, Gribbon A, St-Laurent M, Ferrao T, Barnes J, Kuzik N, Colley R. Comparison of physical activity and sedentary time measured with the ActiGraph GT3X-BT and Actical accelerometers. Health Rep. 2026 Feb 18;37(2):3-15. doi: 10.25318/82-003-x202600200001-eng. PMID: 41730515.
remotes::install_git(
url = "https://github.com/statcan/chms",
force = TRUE,
upgrade = "never"
)# Load dependencies into current R session
library(chms)
library(dplyr)# Create participant meta (external/non-statcan users)
meta <- tibble(
id = c("jane-canuck", "john-canuck"),
age = c(10, 40),
agd_lfe = c(
system.file("extdata", "jane-canuck-lfe.agd", package = "chms"),
system.file("extdata", "john-canuck-lfe.agd", package = "chms")
),
agd_nml = c(
system.file("extdata", "jane-canuck-nml.agd", package = "chms"),
system.file("extdata", "john-canuck-nml.agd", package = "chms")
),
start_date = c("2021-05-30", "2021-05-27"),
epoch_length = c(15, 60)
)
# Print/examine
glimpse(meta)
#> Rows: 2
#> Columns: 6
#> $ id <chr> "jane-canuck", "john-canuck"
#> $ age <dbl> 10, 40
#> $ agd_lfe <chr> "C:/Users/username/AppData/Local/R/win-library/4.4/chms/ex…
#> $ agd_nml <chr> "C:/Users/username/AppData/Local/R/win-library/4.4/chms/ex…
#> $ start_date <chr> "2021-05-30", "2021-05-27"
#> $ epoch_length <dbl> 15, 60# Create participant meta (statcan users)
meta <- get_chms_meta(
clinic_file = "path/to/clinic/file.sas7bdat",
agd_dir = "path/to/agd/files/site",
clinic_id = "CLINICID",
site = "SITE",
age = "CLC_AGE",
day = "V2_DAY",
month = "V2_MTH",
year = "V2_YEAR"
)# Initialize agd R6 class
agd_data <- agd$new(
id = meta$id,
age = meta$age,
agd_lfe = meta$agd_lfe,
agd_nml = meta$agd_nml,
epoch_length = meta$epoch_length,
day_max = 7,
sleep_algo = "barreira",
non_wear_algo = "barreira",
start_date = meta$start_date,
cpu_max = 8,
dir = getwd()
)
# Print/examine
agd_data
#>
#> ── 🍁chms::agd$print() method ──
#>
#> Settings
#>
#> # A tibble: 2 × 9
#> id age agd_nml agd_lfe epoch_length day_max sleep_algo non_wear_algo
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 jane-canu… 10 C:/Use… C:/Use… 15 7 barreira barreira
#> 2 john-canu… 40 C:/Use… C:/Use… 60 7 barreira barreira
#> # ℹ 1 more variable: start_date <chr>
#>
#> Log
#>
#> # A tibble: 1 × 4
#> method timestamp status message
#> <chr> <dttm> <chr> <chr>
#> 1 new() 2026-07-27 10:20:38 success ""# Run processing pipeline (load, clean, classify and summarize data)
agd_data$run()
#>
#> ── 🍁chms::agd$run() method ──
#>
#> ℹ Crunching data for 2 participants across 2 CPUs.
#>
#> ℹ Exporting results to 'C:/Users/username/Desktop/chms/tools/agd-run-2026-07-27-10-20-46-879816'.
#>
#> ✔ Done!# Export results manually
agd_data$export(paste0(getwd(), "/my-results"))
#>
#> ── 🍁chms::agd$export() method ──
#>
#> ℹ Exporting results to 'C:/Users/username/Desktop/chms/tools/my-results/agd-run-2026-07-27-10-20-47-448933'.
#>
#> ✔ Done!# Export statcan-formatted results manually
agd_data$export(getwd(), stc = TRUE)
#>
#> ── 🍁chms::agd$export() method ──
#>
#> ℹ Exporting `self$results$summary_full_stc` and `self$results$summary_run` to 'C:/Users/username/Desktop/chms/tools'.
#>
#> ✔ Done!# Get settings and pipeline run log
agd_data
#>
#> ── 🍁chms::agd$print() method ──
#>
#> Settings
#>
#> # A tibble: 2 × 9
#> id age agd_nml agd_lfe epoch_length day_max sleep_algo non_wear_algo
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 jane-canu… 10 C:/Use… C:/Use… 15 7 barreira barreira
#> 2 john-canu… 40 C:/Use… C:/Use… 60 7 barreira barreira
#> # ℹ 1 more variable: start_date <chr>
#>
#> Log
#>
#> # A tibble: 2 × 4
#> method timestamp status message
#> <chr> <dttm> <chr> <chr>
#> 1 new() 2026-07-27 10:20:38 success ""
#> 2 run() 2026-07-27 10:20:47 success ""# Plot data
plot(agd_data, id = "jane-canuck")
#>
#> ── 🍁chms::plot(agd) method ──
#>
#> ℹ Rendering scatter plot for participant `jane-canuck`
#> ✔ Done!
# Summarize data
summary(agd_data)
#>
#> ── 🍁chms::summary(agd) method ──
#>
#> Waking hours summary
#> Participant count: 2
#>
#> # A tibble: 2 × 14
#> participant_id device_serial_number wear_time steps lpa mpa vpa mvpa
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 jane-canuck MOS2E26200432 14.7 10659. 251. 35.5 25.8 61.3
#> 2 john-canuck MOS2E26200637 16.4 11166. 309. 32.4 17.9 50.3
#> # ℹ 6 more variables: lmvpa <dbl>, mpa_bouts <dbl>, vpa_bouts <dbl>,
#> # mvpa_bouts <dbl>, sb <dbl>, valid_day <dbl>
#>
#> Sleeping hours summary
#> Participant count: 2
#>
#> # A tibble: 2 × 16
#> participant_id device_serial_number wear_time sleep_period_time sleep_episodes
#> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 jane-canuck MOS2E26200432 9.32 9.63 1
#> 2 john-canuck MOS2E26200637 7.28 7.28 1
#> # ℹ 11 more variables: nocturnal_sleep_midpoint <chr>, wake_episodes <dbl>,
#> # total_wake_episode_time <dbl>, total_sleep_episode_time <dbl>,
#> # sleep_episode_efficiency <dbl>, total_restful_sleep_time <dbl>,
#> # sleep_episode_movements <dbl>, total_disrupted_sleep <dbl>,
#> # restful_sleep_efficiency <dbl>, valid_day <dbl>, sleep_episode_log <chr># View all results in tab
agd_data$view()
# View specific results in tab
agd_data$view("summary_full")
agd_data$view("summary_full_stc")
agd_data$view("summary_run")
agd_data$view("summary_sleeping_hours")
agd_data$view("summary_waking_hours")
# View issues and run log
agd_data$view("issues")
agd_data$view("log")# Store results in stand-alone data frames
summary_full <- agd_data$results$summary_full
summary_full_stc <- agd_data$results$summary_full_stc
summary_run <- agd_data$results$summary_run
summary_sleeping_hours <- agd_data$results$summary_sleeping_hours
summary_waking_hours <- agd_data$results$summary_waking_hours# Render sanity check report
agd_data$sanity_check(
name = "My sanity check report",
dir = getwd()
)?agd