In this competition you will use sensor data to classify body-focused repetitive behaviors (BFRBs) and other gestures.

This dataset contains sensor recordings taken while participants performed 8 BFRB-like gestures and 10 non-BFRB-like gestures while wearing the Helios device on the wrist of their dominant arm. The Helios device contains three sensor types:

1. 1x Inertial Measurement Unit (IMU; BNO080/BNO085): An integrated sensor that combines accelerometer, gyroscope, and magnetometer measurements with onboard processing to provide orientation and motion data.
2. 5x Thermopile Sensor (MLX90632): A non-contact temperature sensor that measures infrared radiation.
3. 5x Time-of-Flight Sensor (VL53L7CX): A sensor that measures distance by detecting how long it takes for emitted infrared light to bounce back from objects.
   You must submit to this competition using the provided Python evaluation API, which serves test set data one sequence at a time. To use the API, follow the example in this notebook.

Expect approximately 3,500 sequences in the hidden test set.
Half of the hidden-test sequences are recorded with IMU only; the thermopile (thm_) and time-of-flight (tof__v*) columns are still present but contain null values for those sequences.
This will allow us to determine whether adding the time-of-flight and thermopile sensors improves our ability to detect BFRBs. Note also that there is known sensor communication failure in this dataset, resulting in missing data from some sensors in some sequences.

Files:

[train/test].csv

• row_id
• sequence_id - An ID for the batch of sensor data. Each sequence includes one Transition, one Pause, and one Gesture.
• sequence_type - If the gesture is a target or non-target type. Train only.
• sequence_counter - A counter of the row within each sequence.
• subject - A unique ID for the subject who provided the data.
• gesture - The target column. Description of sequence Gesture. Train only.
• orientation - Description of the subject's orientation during the sequence. Train only.
• behavior - A description of the subject's behavior during the current phase of the sequence.
• acc_[x/y/z] - Measure linear acceleration along three axes in meters per second squared from the IMU sensor.
• rot_[w/x/y/z] - Orientation data which combines information from the IMU's gyroscope, accelerometer, and magnetometer to describe the device's orientation in 3D space.
• thm_[1-5] - There are five thermopile sensors on the watch which record temperature in degrees Celsius. Note that the index/number for each corresponds to the index in the photo on the Overview tab.
• tof_[1-5]_v[0-63] - There are five time-of-flight sensors on the watch that measure distance. In the dataset, the 0th pixel for the first time-of-flight sensor can be found with column name tof_1_v0, whereas the final pixel in the grid can be found under column tof_1_v63. This data is collected row-wise, where the first pixel could be considered in the top-left of the grid, with the second to its right, ultimately wrapping so the final value is in the bottom right (see image above). The particular time-of-flight sensor is denoted by the number at the start of the column name (e.g., 1_v0 is the first pixel for the first time-of-flight sensor while 5_v0 is the first pixel for the fifth time-of-flight sensor). If there is no sensor response (e.g., if there is no nearby object causing a signal reflection), a -1 is present in this field. Units are uncalibrated sensor values in the range 0-254. Each sensor contains 64 pixels arranged in an 8x8 grid, visualized in the figure below.

[train/test]_demographics.csv

These tabular files contain demographic and physical characteristics of the participants.

• subject
• adult_child: Indicates whether the participant is a child (0) or an adult (1). Adults are defined as individuals aged 18 years or older.
• age: Participant's age in years at time of data collection.
• sex: Participants sex assigned at birth, 0= female, 1 = male.
• handedness: Dominant hand used by the participant, 0 = left-handed, 1 = right-handed.
• height_cm: Height of the participant in centimeters.
• shoulder_to_wrist_cm: Distance from shoulder to wrist in centimeters.
• elbow_to_wrist_cm: Distance from elbow to wrist in centimeters.

sample_submission.csv

• sequence_id
• gesture
  kaggle_evaluation/ The files that implement the evaluation API. You can run the API locally on a Unix machine for testing purposes.