The analyzed sample of N = 24 included 14 women and 10 men with an average age of 24.3 years (between 19 and 34), average height 173 cm ± 9 cm (standard deviation), average body mass 68 kg ± 15 kg and average leg length 94 cm ± 6 cm. These biometric measurements were required for modeling motion tracking. For participation, participants received either course credit or a monetary reimbursement of 8€/h. All experimental procedures were approved by the Chemnitz University of Technology, Faculty of Behavioral and Social Sciences ethics committee (case no.: V-314-PHKP-WETGRAIL01-17012019). Participant data were protected following the guidelines for data management and data sharing of the German DGPs (Gollwitzer et al. 2020 ).
Gait and Eye Tracking in Healthy Adults
The analyzed sample of N = 24 included 14 women and 10 men with an average age of 24.3 years (between 19 and 34), average height 173 cm ± 9 cm (standard deviation), average body mass 68 kg ± 15 kg and average leg length 94 cm ± 6 cm. These biometric measurements were required for modeling motion tracking. For participation, participants received either course credit or a monetary reimbursement of 8€/h. All experimental procedures were approved by the Chemnitz University of Technology, Faculty of Behavioral and Social Sciences ethics committee (case no.: V-314-PHKP-WETGRAIL01-17012019). Participant data were protected following the guidelines for data management and data sharing of the German DGPs (Gollwitzer et al. 2020 ).
Corresponding Organization : Chemnitz University of Technology
Variable analysis
- None explicitly mentioned
- Eye tracking data (proportion of missing values)
- Normal or corrected-to-normal vision (≤ ± 7 dpt when uncorrected, contact lenses permitted)
- No neurological or walking impairments
- Body mass of 130 kg or less
- Participants being sufficiently rested and focused (self-reported in a questionnaire prior to the experiment)
- Participants being naïve to the hypotheses
- None explicitly mentioned
- None explicitly mentioned
Annotations
Based on most similar protocols
As authors may omit details in methods from publication, our AI will look for missing critical information across the 5 most similar protocols.
About PubCompare
Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.
We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.
However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.
Ready to get started?
Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required
Revolutionizing how scientists
search and build protocols!