PhysioWearable

PhysioWearable analyzes free-living tri-axial accelerometry. It covers CSV ingestion, gravity-based calibration, ENMO, non-wear detection, step detection, physical-activity intensity classification, bout summaries, and optional conversion to the common PhysioExperiment model.

Installation

# the containers build on Bioconductor, so its repositories are needed too
install.packages("BiocManager", repos = "https://cloud.r-project.org")
options(repos = c(
  xbiosignal = "https://x-biosignal.r-universe.dev",
  BiocManager::repositories()
))
install.packages("PhysioWearable")

Quick start

library(PhysioWearable)

sampling_rate <- 50
time <- seq(0, 20, by = 1 / sampling_rate)
acceleration <- cbind(
  x = 0,
  y = 0,
  z = 1 + 0.4 * sin(2 * pi * 1.8 * time)
)

enmo <- computeENMO(
  acceleration,
  sampling_rate = sampling_rate,
  epoch_sec = 5,
  unit = "mg"
)
steps <- detectSteps(acceleration, sampling_rate)

enmo
steps$n_steps

Main functions

Stage	Functions
Import and model conversion	readAccelCSV(), accelToPhysioExperiment()
Calibration	autoCalibrateAccel()
Movement metric	computeENMO()
Wear-time handling	detectNonWear()
Ambulation	detectSteps()
Intensity and bouts	paIntensityThresholds(), classifyBouts()

Device placement, units, calibration, sampling rate, non-wear parameters, and population-specific intensity thresholds should be recorded with study methods. Default outputs are research summaries, not clinical classifications.

Ecosystem role

PhysioWearable converts raw free-living acceleration into quality-control and activity summaries. Device-specific multi-signal imports belong in PhysioDevices; downstream statistical and clinical analyses can consume the shared model or returned tables.

Documentation

• Function reference
• Source repository
• Issue tracker

Citation

citation("PhysioWearable")

See the ecosystem governance, support policy, and contribution guide.

Author and license

Author and maintainer: Yusuke Matsui. Licensed under the MIT License.