The 6DoF Physiological Dataset is a publicly available collection of electrodermal activity (EDA) and electrocardiogram (ECG) recordings acquired during a 6DoF virtual reality experiment. Participants performed a series of predefined movements to investigate the effects of user motion and sensor placement on physiological signal quality.
The dataset was used in our study, "Signal or Noise? How User Movement and Sensor Placement Impact Physiological Data Collection in 6DoF Virtual Reality."
It includes 430 physiological recordings, categorized according to the sensor placement on the body, and is distributed in CSV format.
The dataset contains two types of physiological data, electrodermal activity (EDA) and electrocardiography (ECG), both provided in CSV format.
For the EDA data, the dataset includes two versions: raw (full-length) signals and pre-segmented signals. The raw signals contain the left-hand and right-hand EDA recordings, together with the corresponding timestamps for a participant under a specific sensor placement condition. Each raw signal is accompanied by an additional CSV file containing the timestamps marking the beginning and end of each movement sequence, allowing the signals to be segmented according to the performed movements.
The pre-segmented signals correspond to the same EDA recordings as the raw signals but have already been segmented and organized according to the sensor placement condition and the movement performed. The letter included in the filename (L or R) indicates the hand performing the movement, with L corresponding to the left hand and R corresponding to the right hand.
For the ECG data, only the raw signals, categorized by sensor placement condition, together with their associated movement markers, are provided.