Abstract
Head impact measurement devices enable opportunities to collect impact data directly from humans to study topics like concussion biomechanics, head impact exposure and its effects, and concussion risk reduction techniques in sports when paired with other relevant data. With recent advances in head impact measurement devices and cost-effective price points, more and more investigators are using them to study brain health questions. However, as the field's literature grows, the variance in study quality is apparent. This brief paper aims to provide a high-level set of key considerations for the design and analysis of head impact measurement studies that can help avoid flaws introduced by sampling biases, false data, missing data, and confounding factors. We discuss key points through four overarching themes: study design, operational management, data quality, and data analysis.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.