Activity recognition from in-the-wild smartwatches (ArWISE)

The Activity recognition from in-the-WIld SmartwatchEs (ArWISE) dataset is based on sensor data and activity labels collected from smart watches as part of several studies for a total of 854 participants across 20 cohorts. The sensor data consisted of 10Hz accelerometer, gyroscope, and location information that has been processed into anonymized features computed from one minute windows of data: local time, date, and day of week; mean and standard deviation of yaw, pitch, roll, x/y/z/total rotation rate, x/y/z/total acceleration, speed, course, distance from home, and bearing from home. The activity label is one of eat, errands, exercise, hobby, housework, hygiene, relax, sleep, socialize, travel, work, other. There are 470M data points total, of which 37M are labeled., We introduce ArWISE (Activity recognition from in-the-Wild SmartwatchEs), a dataset containing labeled and unlabeled data collected by Apple Watches. ArWISE represents readings collected from 20 studies in 2 countries over 8 years.
Data Collection
Data collection followed a consistent protocol for each study. Participants were given an Apple Watch to wear each day on their non-dominant arm. While they wore the watch, a custom app collected 3d accelerometer and gyroscope readings at 10Hz. Additionally, the app collected the person’s location every minute or when the magnitude of the acceleration vector exceeded a threshold.
At random times throughout each day, the smartwatch prompted the participant to select an activity from a scroll-down list that best described their current activity. The distribution of user-provided labels across 12 activity categories are Eat (6.5%), Errands (3.7%), Exercise (4.7%), Hobby (1.1%), Housework (19.7%), Hygiene (1.9%), Other (3.1%), Relax (37.7%), Sleep..., , # Activity recognition from in-the-wild smartwatches (ArWISE)

[https://doi.org/10.5061/dryad.jdfn2z3nm](https://doi.org/10.5061/dryad.jdfn2z3nm)

## Description of the data and file structure

CSV files for each participant's data are organized into zip files by cohort (c01-c20). Cohorts c02, c03, and c20 are split into multiple parts to adhere to the 10G limit per file. For cohorts c03 and c05, participants alternated between two watches (day and night); these are split across two files with w1 and w2 designations (note that file `c03.p053.w2.csv` is missing; no data was collected for that watch). The CSV files all include a header with feature names. All features are floats, except for the two time stamps that define the start and end times of the window used to generate each point, and the activity label.

### Features

`stamp_start`, `stamp_end` Timestamps indicating the start and end of time window for computing features. The timestamp follows the ISO 8601 standard, but without th...,