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      Consensus Head Acceleration Measurement Practices (CHAMP): Laboratory Validation of Wearable Head Kinematic Devices

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          Abstract

          Wearable devices are increasingly used to measure real-world head impacts and study brain injury mechanisms. These devices must undergo validation testing to ensure they provide reliable and accurate information for head impact sensing, and controlled laboratory testing should be the first step of validation. Past validation studies have applied varying methodologies, and some devices have been deployed for on-field use without validation. This paper presents best practices recommendations for validating wearable head kinematic devices in the laboratory, with the goal of standardizing validation test methods and data reporting. Key considerations, recommended approaches, and specific considerations were developed for four main aspects of laboratory validation, including surrogate selection, test conditions, data collection, and data analysis. Recommendations were generated by a group with expertise in head kinematic sensing and laboratory validation methods and reviewed by a larger group to achieve consensus on best practices. We recommend that these best practices are followed by manufacturers, users, and reviewers to conduct and/or review laboratory validation of wearable devices, which is a minimum initial step prior to on-field validation and deployment. We anticipate that the best practices recommendations will lead to more rigorous validation of wearable head kinematic devices and higher accuracy in head impact data, which can subsequently advance brain injury research and management.

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          Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs)

          Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, as well as cases where multiple terms are used to describe essentially the same concept. Our intent is to clarify core terminology and best practices for the evaluation of Biometric Monitoring Technologies (BioMeTs), without unnecessarily introducing new terms. We focus on the evaluation of BioMeTs as fit-for-purpose for use in clinical trials. However, our intent is for this framework to be instructional to all users of digital measurement tools, regardless of setting or intended use. We propose and describe a three-component framework intended to provide a foundational evaluation framework for BioMeTs. This framework includes (1) verification, (2) analytical validation, and (3) clinical validation. We aim for this common vocabulary to enable more effective communication and collaboration, generate a common and meaningful evidence base for BioMeTs, and improve the accessibility of the digital medicine field.
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            MECHANICS OF HEAD INJURIES

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              Concussion in professional football: reconstruction of game impacts and injuries.

              Concussion in professional football was studied with respect to impact types and injury biomechanics. A combination of video surveillance and laboratory reconstruction of game impacts was used to evaluate concussion biomechanics. Between 1996 and 2001, videotapes of concussions and significant head impacts were collected from National Football League games. There were clear views of the direction and location of the helmet impact for 182 cases. In 31 cases, the speed of impact could be determined with analysis of multiple videos. Those cases were reconstructed in laboratory tests using helmeted Hybrid III dummies and the same impact velocity, direction, and head kinematics as in the game. Translational and rotational accelerations were measured, to define concussion biomechanics. Several studies were performed to ensure the accuracy and reproducibility of the video analysis and laboratory methods used. Concussed players experienced head impacts of 9.3 +/- 1.9 m/s (20.8 +/- 4.2 miles/h). There was a rapid change in head velocity of 7.2 +/- 1.8 m/s (16.1 +/- 4.0 miles/h), which was significantly greater than that for uninjured struck players (5.0 +/- 1.1 m/s, 11.2 +/- 2.5 miles/h; t = 2.9, P < 0.005) or striking players (4.0 +/- 1.2 m/s, 8.9 +/- 2.7 miles/h; t = 7.6, P < 0.001). The peak head acceleration in concussion was 98 +/- 28 g with a 15-millisecond half-sine duration, which was statistically greater than the 60 +/- 24 g for uninjured struck players (t = 3.1, P < 0.005). Concussion was primarily related to translational acceleration resulting from impacts on the facemask or side, or falls on the back of the helmet. Concussion could be assessed with the severity index or head injury criterion (the conventional measures of head injury risk). Nominal tolerance levels for concussion were a severity index of 300 and a head injury criterion of 250. Concussion occurs with considerable head impact velocity and velocity changes in professional football. Current National Operating Committee on Standards for Athletic Equipment standards primarily address impacts to the periphery and crown of the helmet, whereas players are experiencing injuries in impacts to the facemask, side, and back of the helmet. New tests are needed to assess the performance of helmets in reducing concussion risks involving high-velocity and long-duration injury biomechanics.
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                Author and article information

                Contributors
                lwu@mech.ubc.ca
                Journal
                Ann Biomed Eng
                Ann Biomed Eng
                Annals of Biomedical Engineering
                Springer International Publishing (Cham )
                0090-6964
                1573-9686
                14 September 2022
                14 September 2022
                2022
                : 50
                : 11
                : 1356-1371
                Affiliations
                [1 ]Biomechanics Consulting and Research, LLC, Charlottesville, VA USA
                [2 ]GRID grid.239552.a, ISNI 0000 0001 0680 8770, Center for Injury Research and Prevention, , Children’s Hospital of Philadelphia, ; Philadelphia, PA USA
                [3 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Department of Biomedical Engineering and Mechanics, , Virginia Tech, ; Blacksburg, VA USA
                [4 ]GRID grid.420168.9, ISNI 0000 0001 2160 2738, United States Army Aeromedical Research Laboratory, ; Fort Rucker, AL USA
                [5 ]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, Department of Mechanical Engineering, , The University of British Columbia, ; Vancouver, BC Canada
                [6 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Department of Bioengineering, , University of Pennsylvania, ; Philadelphia, PA USA
                [7 ]MEA Forensic Engineers & Scientists, Richmond, BC Canada
                [8 ]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, School of Kinesiology, , University of British Columbia, ; Vancouver, BC Canada
                Author notes

                Associate Editor Stefan M. Duma oversaw the review of this article

                Author information
                http://orcid.org/0000-0002-8236-032X
                Article
                3066
                10.1007/s10439-022-03066-0
                9652295
                36104642
                234c04cb-6901-42b6-a052-ea50d1c679f2
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 14 June 2022
                : 25 August 2022
                Categories
                S.I. : Concussions
                Custom metadata
                © The Author(s) under exclusive licence to Biomedical Engineering Society 2022

                Biomedical engineering
                accuracy,best practices,head impact kinematics,recommendations,validation
                Biomedical engineering
                accuracy, best practices, head impact kinematics, recommendations, validation

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