Designed for studies where animals tagged with acoustic tags are expected
    to move through receiver arrays. This package combines the advantages of automatic sorting and checking 
    of animal movements with the possibility for user intervention on tags that deviate from expected 
    behaviour. The three analysis functions (explore(), migration() and residency()) 
    allow the users to analyse their data in a systematic way, making it easy to compare results from 
    different studies.
    CJS calculations are based on Perry et al. (2012) <https://www.researchgate.net/publication/256443823_Using_mark-recapture_models_to_estimate_survival_from_telemetry_data>.

Recent studies haven shown that, on top of total daily active/sedentary volumes, the time 
  accumulation strategies provide more sensitive information. This package provides functions to extract 
  commonly used fragmentation metrics to quantify such time accumulation strategies based on minute level 
  actigraphy-measured activity counts data.

A tool to obtain activity counts, originally a translation of the 
  'python' package 'agcounts' <https://github.com/actigraph/agcounts>. This tool
  allows the processing of data from any accelerometer brand, with a more flexible 
  approach to handle different sampling frequencies.

Provides sleep duration estimates using a Pruned Dynamic
  Programming (PDP) algorithm that efficiently identifies
  change-points. PDP applied to physical activity data can identify
  transitions from wakefulness to sleep and vice versa. Baek, Jonggyu, Banker,
  Margaret, Jansen, Erica C., She, Xichen, Peterson, Karen E., Pitchford,
  E. Andrew, Song, Peter X. K. (2021) An Efficient Segmentation Algorithm to
  Estimate Sleep Duration from Actigraphy Data <doi:10.1007/s12561-021-09309-3>.

A tool to analyse 'ActiGraph' accelerometer data and to implement 
    the use of the PROactive Physical Activity in COPD (chronic obstructive pulmonary disease) instruments. Once analysis
    is completed, the app allows to export results to .csv files and to generate
    a report of the measurement. All the configured inputs relevant for interpreting
    the results are recorded in the report. In addition to the existing 'R' packages 
    that are fully integrated with the app, the app uses some functions from the 
    'actigraph.sleepr' package developed by Petkova (2021) <https://github.com/dipetkov/actigraph.sleepr/>.