{
  "_id": "6adb470d1206290b6ab76a93",
  "Package": "zeitR",
  "Title": "Actigraphy Data Parsing and Analysis for R",
  "Version": "0.1.8",
  "Authors@R": "c(\nperson(\"Lucas\", \"França\",\nemail = \"lucas.franca@northumbria.ac.uk\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-0853-1319\")),\nperson(\"Mario\", \"Leocadio-Miguel\",\nemail = \"mario.miguel@northumbria.ac.uk\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-7248-3529\")),\nperson(\"Julia Ribeiro da Silva\", \"Vallim\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0001-8708-8479\"))\n)",
  "Description": "Provides tools for importing, parsing, and analysing raw\nactigraphy data from wrist-worn devices. Implements a full\nsleep analysis pipeline — off-wrist detection, main sleep\nperiod detection, nap detection, and WASO computation —\nvalidated epoch-for-epoch against the Condor circadiaBase\nPython reference pipeline using ActTrust hardware. Also\ncomputes standard non-parametric circadian rhythm variables\n(interdaily stability, intradaily variability, relative\namplitude, L5, M10). Device-specific parameter presets can be\nswapped to adapt the pipeline to other actigraph models.\nDesigned to complement slumbR in the Circadia Lab ecosystem.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
  "VignetteBuilder": "knitr",
  "Config/testthat/edition": "3",
  "Additional_repositories": "https://circadia-bio.r-universe.dev",
  "URL": "https://zeitr.circadia-lab.uk,\nhttps://github.com/circadia-bio/zeitR",
  "BugReports": "https://github.com/circadia-bio/zeitR/issues",
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  "Repository": "https://circadia-bio.r-universe.dev",
  "Date/Publication": "2026-08-24 13:34:53 UTC",
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  "Packaged": {
    "Date": "2026-10-23 11:18:52 UTC",
    "User": "root"
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  "Author": "Lucas França [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-0853-1319>),\nMario Leocadio-Miguel [aut] (ORCID:\n<https://orcid.org/0000-0002-7248-3529>),\nJulia Ribeiro da Silva Vallim [aut] (ORCID:\n<https://orcid.org/0000-0001-8708-8479>)",
  "Maintainer": "Lucas França <lucas.franca@northumbria.ac.uk>",
  "_user": "circadia-bio",
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  "_expires": "2027-01-31T11:37:47.000Z",
  "_created": "2026-10-23T11:18:52.000Z",
  "_published": "2026-10-23T11:37:49.770Z",
  "_upstream": "https://github.com/circadia-bio/zeitR",
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    "name": "Lucas França",
    "email": "lucas.franca@northumbria.ac.uk",
    "login": "lucasfr",
    "description": "Immigrant, physicist, neuroscientist, open source and data science enthusiast.",
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  "_exports": [
    "actogram_colours",
    "acttrust_params",
    "check_consistency",
    "circ_mean_h",
    "circ_sd_h",
    "classify_pa_counts",
    "classify_pa_intensity",
    "classify_sleep_episodes",
    "compute_activity_counts",
    "compute_cosinor",
    "compute_cpd_metrics",
    "compute_lids",
    "compute_lri",
    "compute_npcra",
    "compute_sleep_metrics",
    "compute_sri",
    "compute_waso",
    "detect_lids_bouts",
    "detect_naps_crespo",
    "detect_offwrist_bimodal",
    "detect_sleep_crespo",
    "estimate_ee",
    "export_hypnogram",
    "extract_sleep_episodes",
    "fit_lids",
    "label_states",
    "lids_transform",
    "pa_equations",
    "plot_actogram",
    "plot_actogram_activity",
    "plot_actogram_double",
    "prepare_actigraphy",
    "read_actigraphy",
    "read_actigraphy_dir",
    "read_acttrust",
    "read_axivity",
    "run_pipeline",
    "run_pipeline_batch",
    "run_pipeline_native",
    "run_pipeline_native_batch",
    "score_epochs_cole_kripke",
    "study_lids_metrics",
    "study_sleep_metrics",
    "study_summary"
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  "_help": [
    {
      "page": "actogram_colours",
      "title": "Default state colour palette for actogram plots",
      "topics": [
        "actogram_colours"
      ]
    },
    {
      "page": "acttrust_params",
      "title": "ActTrust device parameter preset",
      "topics": [
        "acttrust_params"
      ]
    },
    {
      "page": "check_consistency",
      "title": "Check actigraphy timestamps for consistency issues",
      "topics": [
        "check_consistency"
      ]
    },
    {
      "page": "circ_mean_h",
      "title": "Circular mean of clock times in decimal hours",
      "topics": [
        "circ_mean_h"
      ]
    },
    {
      "page": "circ_sd_h",
      "title": "Circular standard deviation of clock times in decimal hours",
      "topics": [
        "circ_sd_h"
      ]
    },
    {
      "page": "classify_pa_counts",
      "title": "Classify physical activity intensity directly from activity counts",
      "topics": [
        "classify_pa_counts"
      ]
    },
    {
      "page": "classify_pa_intensity",
      "title": "Classify physical activity intensity from METs",
      "topics": [
        "classify_pa_intensity"
      ]
    },
    {
      "page": "classify_sleep_episodes",
      "title": "Classify sleep episodes as main or secondary (native pipeline)",
      "topics": [
        "classify_sleep_episodes"
      ]
    },
    {
      "page": "compute_activity_counts",
      "title": "Compute PIM, TAT, and ZCM activity counts from raw triaxial acceleration",
      "topics": [
        "compute_activity_counts"
      ]
    },
    {
      "page": "compute_cosinor",
      "title": "Cosinor rhythmometry (Cornelissen 2014)",
      "topics": [
        "compute_cosinor"
      ]
    },
    {
      "page": "compute_cpd_metrics",
      "title": "Compute CPD, MSF, MSW, MSFsc, SJL, and SJLa",
      "topics": [
        "compute_cpd_metrics",
        "compute_cpd_metrics.default",
        "compute_cpd_metrics.zeitr_result"
      ]
    },
    {
      "page": "compute_lids",
      "title": "Compute LIDS ultradian-rhythm parameters for every sleep bout",
      "topics": [
        "compute_lids"
      ]
    },
    {
      "page": "compute_lri",
      "title": "Light Regularity Index (LRI)",
      "topics": [
        "compute_lri"
      ]
    },
    {
      "page": "compute_npcra",
      "title": "Non-parametric circadian rhythm analysis (NPCRA)",
      "topics": [
        "compute_npcra"
      ]
    },
    {
      "page": "compute_sleep_metrics",
      "title": "Compute sleep metrics split by day type",
      "topics": [
        "compute_sleep_metrics",
        "compute_sleep_metrics.default",
        "compute_sleep_metrics.zeitr_result"
      ]
    },
    {
      "page": "compute_sri",
      "title": "Sleep Regularity Index (SRI)",
      "topics": [
        "compute_sri"
      ]
    },
    {
      "page": "compute_waso",
      "title": "Compute WASO and nightly sleep statistics",
      "topics": [
        "compute_waso"
      ]
    },
    {
      "page": "detect_lids_bouts",
      "title": "Detect nighttime sleep bouts via the Roenneberg relative-immobility method",
      "topics": [
        "detect_lids_bouts"
      ]
    },
    {
      "page": "detect_naps_crespo",
      "title": "Detect secondary sleep periods (naps) using the Crespo nap algorithm",
      "topics": [
        "detect_naps_crespo"
      ]
    },
    {
      "page": "detect_offwrist_bimodal",
      "title": "Off-wrist detection using the Condor bimodal activity/temperature model",
      "topics": [
        "detect_offwrist_bimodal"
      ]
    },
    {
      "page": "detect_sleep_crespo",
      "title": "Detect main sleep periods using the Crespo algorithm",
      "topics": [
        "detect_sleep_crespo"
      ]
    },
    {
      "page": "estimate_ee",
      "title": "Estimate energy expenditure (METs) from activity counts",
      "topics": [
        "estimate_ee"
      ]
    },
    {
      "page": "export_hypnogram",
      "title": "Export a zeitR pipeline result as a hypnoR-compatible hypnogram",
      "topics": [
        "export_hypnogram"
      ]
    },
    {
      "page": "extract_sleep_episodes",
      "title": "Extract sleep episodes from a CSPD-scored epoch table",
      "topics": [
        "extract_sleep_episodes"
      ]
    },
    {
      "page": "fit_lids",
      "title": "Fit a sloped cosine to a LIDS profile, scanning candidate periods",
      "topics": [
        "fit_lids"
      ]
    },
    {
      "page": "label_states",
      "title": "Convert integer epoch states to a labelled factor",
      "topics": [
        "label_states"
      ]
    },
    {
      "page": "lids_transform",
      "title": "Apply the LIDS (Locomotor Inactivity During Sleep) transform",
      "topics": [
        "lids_transform"
      ]
    },
    {
      "page": "pa_equations",
      "title": "Published activity-count equations for estimating METs and PA intensity",
      "topics": [
        "pa_equations"
      ]
    },
    {
      "page": "plot_actogram",
      "title": "Plot a single-column actogram",
      "topics": [
        "plot_actogram"
      ]
    },
    {
      "page": "plot_actogram_activity",
      "title": "Plot a double-plotted actogram with activity bars",
      "topics": [
        "plot_actogram_activity"
      ]
    },
    {
      "page": "plot_actogram_double",
      "title": "Plot a double-plotted actogram",
      "topics": [
        "plot_actogram_double"
      ]
    },
    {
      "page": "prepare_actigraphy",
      "title": "Prepare a raw actigraphy tibble for analysis",
      "topics": [
        "prepare_actigraphy"
      ]
    },
    {
      "page": "read_actigraphy",
      "title": "Read an actigraphy file into a zeitr_recording object",
      "topics": [
        "read_actigraphy"
      ]
    },
    {
      "page": "read_actigraphy_dir",
      "title": "Read all actigraphy files in a directory",
      "topics": [
        "read_actigraphy_dir"
      ]
    },
    {
      "page": "read_acttrust",
      "title": "Read a Condor Instruments ActTrust actigraphy file",
      "topics": [
        "read_acttrust"
      ]
    },
    {
      "page": "read_axivity",
      "title": "Read an Axivity AX3/AX6 .cwa file into a zeitR-standard epoch tibble",
      "topics": [
        "read_axivity"
      ]
    },
    {
      "page": "run_pipeline",
      "title": "Run the full actigraphy sleep analysis pipeline",
      "topics": [
        "run_pipeline"
      ]
    },
    {
      "page": "run_pipeline_batch",
      "title": "Run the pipeline on all files in a directory",
      "topics": [
        "run_pipeline_batch"
      ]
    },
    {
      "page": "run_pipeline_native",
      "title": "Run the Vallim native actigraphy sleep analysis pipeline",
      "topics": [
        "run_pipeline_native"
      ]
    },
    {
      "page": "run_pipeline_native_batch",
      "title": "Run the native pipeline on all files in a directory",
      "topics": [
        "run_pipeline_native_batch"
      ]
    },
    {
      "page": "score_epochs_cole_kripke",
      "title": "Score actigraphy epochs as wake or sleep using the Cole-Kripke algorithm",
      "topics": [
        "score_epochs_cole_kripke"
      ]
    },
    {
      "page": "study_lids_metrics",
      "title": "Batch LIDS ultradian-rhythm summary across a study",
      "topics": [
        "study_lids_metrics"
      ]
    },
    {
      "page": "study_sleep_metrics",
      "title": "Batch sleep-timing and chronotype metrics across a study",
      "topics": [
        "study_sleep_metrics"
      ]
    },
    {
      "page": "study_summary",
      "title": "Summarise a zeitr_study across participants",
      "topics": [
        "study_summary"
      ]
    }
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