やりたいこと

Turi Create / Create MLでActivity ClassificationのCore MLモデルを学習してwatchOSで動かしたい。

Heterogeneity Activity Recognition Data Set

The Heterogeneity Dataset for Human Activity Recognition from Smartphone and Smartwatch sensors consists of two datasets devised to investigate sensor heterogeneities' impacts on human activity recognition algorithms (classification, automatic data segmentation, sensor fusion, feature extraction, etc). 

Activity recognition data set
The dataset contains the readings of two motion sensors commonly found in smartphones. Reading were recorded while users executed activities scripted in no specific order carrying smartwatches and smartphones.
Activities: ‘Biking’, ‘Sitting’, ‘Standing’, ‘Walking’, ‘Stair Up’ and ‘Stair down’.
Sensors: Sensors: Two embedded sensors, i.e., Accelerometer and Gyroscope, sampled at the highest frequency the respective device allows.
Devices: 4 smartwatches (2 LG watches, 2 Samsung Galaxy Gears)
8 smartphones (2 Samsung Galaxy S3 mini, 2 Samsung Galaxy S3, 2 LG Nexus 4, 2 Samsung Galaxy S+)
Recordings: 9 users

Still experiment data set
Accelerometer recordings as above but with devices lying still, in 6 different orientations. Devices used comprise 31 smartphones, 4 smartwatches and 1 tablet, representing 13 different models from 4 manufacturers, running variants of Android and iOS.

Human Activity Recognition

いくつかデータセットがダウンロードできる

CrowdSignals.io

The Largest Smartphone and Smartwatch Dataset Available

CrowdSignals.io is a campaign to build the largest and most comprehensive smartphone and smartwatche data set available. The data include high-quality, labeled mobile and sensor data collected by demographically diverse volunteers.

サンプルデータセットは無料でDLできる。

スマートフォン向け

今回の用途とは違うが、スマホベースで収集したActivities and Postural Transitionsのデータセットもある。

以下の12種類のActivitiesのデータがある。（activity_labels.txtより）

1 WALKING
2 WALKING_UPSTAIRS
3 WALKING_DOWNSTAIRS
4 SITTING
5 STANDING
6 LAYING
7 STAND_TO_SIT
8 SIT_TO_STAND
9 SIT_TO_LIE
10 LIE_TO_SIT
11 STAND_TO_LIE
12 LIE_TO_STAND