Human Activity Detection is the problem of predicting what a person is doing based on a trace of their movement using sensors. The "Human Activity Detection Dataset" includes data collected from 34 subjects, each of whom were asked to perform 18 tasks for 3 minutes each. Each subject had a smartwatch placed on his/her dominant hand and a smartphone in their pocket. The data collection was controlled by a custom-made app that ran on the smartphone and smartwatch. The sensor data that was collected was from the accelerometer and gyroscope on both the smartphone and smartwatch, yielding four total sensors. The sensor data was collected at a rate of 20 Hz (i.e., every 50ms). The smartphone was either the Google Nexus 5/5X or Samsung Galaxy S5 running Android 6.0 (Marshmallow). The smartwatch was the LG G Watch running Android Wear 1.5.
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Human Activity Detection is the problem of predicting what a person is doing based on a trace of their movement using sensors. The "Human Activity Detection Dataset" includes data collected from 34 subjects, each of whom were asked to perform 18 tasks for 3 minutes each. Each subject had a smartwatch placed on his/her dominant hand and a smartph…
harshiiash/Human-Activity-Recognition
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Human Activity Detection is the problem of predicting what a person is doing based on a trace of their movement using sensors. The "Human Activity Detection Dataset" includes data collected from 34 subjects, each of whom were asked to perform 18 tasks for 3 minutes each. Each subject had a smartwatch placed on his/her dominant hand and a smartph…
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