Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

New activity type: fast-walking.
Timeline visualization plot for Exposures.
Option to fuse activity types into merged exposures.
Initial data quality checks for Activities/Exposures (flags invalid data when combined duration of climbing + walking is less than 10 minutes in a specific window).
Support for custom configuration of activity detection thresholds.
Experimental: Context initialization for Exposures (diary handling).
Initial project documentation.

Renamed package from acti-motus to actimotus.
Updated Exposures generation logic to include fast-walking and other new categories.
Improved feature extraction robustness regarding data gaps (handling missing data in raw accelerometer time series).
Updated default configuration thresholds for activities.
Adjusted orientation correction: Non-wear data is no longer flipped when flipping detection is enabled.
Implemented new custom gravitational calibration algorithm.
Updated docstrings.

Auto-calibration support using the Scikit Digital Health library.
Parser for Sens binary files.
Configuration option to set custom activity thresholds (for thigh and trunk sensors).

Unified terminology: consistently use "compute" instead of generate/extract/etc.
Updated wear-time detection algorithm (ongoing debugging).
Renamed activity "move" → "shuffle".
Updated default activity thresholds based on recent validation studies (use LEGACY_CONFIG for Acti4 threshold compatibility).
Improved flipping detection functions to handle edge cases more robustly by refining detection thresholds.

Corrected bug where non-wear time was not counted properly in the Exposures report.
Added default stairs threshold when no data-based threshold is available.
Fixed return values for inside-out flip detection for trunk sensors.
Corrected chunking procedure: only acceleration axes are propagated (removed unintended overlapping column).
Improved inside-out flipping detection for thigh sensors, reducing false positives and increasing accuracy.