Quality Issues in Kinematic Traces from Three Head Impact Sensors in Boxing: Prevalence, Effects, and Implications for Exposure Assessment.

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Tác giả: Robert Borotkanics, Enora Le Flao, Seth Lenetsky, Gunter P Siegmund

Ngôn ngữ: eng

Ký hiệu phân loại: 271.6 *Passionists and Redemptorists

Thông tin xuất bản: United States : Annals of biomedical engineering , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 188584

 PURPOSE: When used in-vivo or in biofidelic environments, many head impact sensors have shown limitations related to the quality and validity of the kinematics measured. The objectives were to assess the quality of kinematic traces from three head impact sensors, determine the effects of signal quality on peak accelerations, and compare measurements across sensors. METHODS: Head impacts were collected with instrumented mouthguards, skin patches, and headgear patches during boxing sparring. The quality of the raw kinematic traces for 442 events for each sensor was categorized using pre-defined objective criteria into high, questionable, and low-quality classes. The proportion of high-quality recordings was analyzed by participant, type of impact, and impact location. Associations between signal quality and peak kinematics were assessed within each sensor, and peak kinematics (resolved to the head center of gravity) were compared between sensors. RESULTS: High-quality criteria were met in 53%, 20%, and 26% of events for the mouthguard, skin patch, and headgear patch, respectively. High-quality recordings were less frequent for impacts occurring close to the sensor (e.g., 30% vs. 61% for the mouthguard) and showed lower peak kinematics than low-quality recordings (p <
  0.001). Despite careful selection of high-quality simultaneous recordings, there was little to no association between the sensors' measurements (Spearman's p ≥ 0.043). CONCLUSIONS: The kinematic data often reflected the motion of the sensor itself rather than the motion of the head, overestimating head impact magnitude. Researchers should evaluate data quality prior to analyzing kinematics or injury severity metrics. Comparison of data across studies or in relation to injury risk functions needs to be done with caution when data were acquired from different sensors.
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