
Nicholas Cecchi
Ph.D. Student in Bioengineering, admitted Autumn 2020
All Publications
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Piecewise Multivariate Linearity Between Kinematic Features and Cumulative Strain Damage Measure (CSDM) Across Different Types of Head Impacts.
Annals of biomedical engineering
2022
Abstract
In a previous study, we found that the relationship between brain strain and kinematic features cannot be described by a generalized linear model across different types of head impacts. In this study, we investigate if such a linear relationship exists when partitioning head impacts using a data-driven approach. We applied the K-means clustering method to partition 3161 impacts from various sources including simulation, college football, mixed martial arts, and car crashes. We found piecewise multivariate linearity between the cumulative strain damage (CSDM; assessed at the threshold of 0.15) and head kinematic features. Compared with the linear regression models without partition and the partition according to the types of head impacts, K-means-based data-driven partition showed significantly higher CSDM regression accuracy, which suggested the presence of piecewise multivariate linearity across types of head impacts. Additionally, we compared the piecewise linearity with the partitions based on individual features used in clustering. We found that the partition with maximum angular acceleration magnitude at 4706 rad/s2 led to the highest piecewise linearity. This study may contribute to an improved method for the rapid prediction of CSDM in the future.
View details for DOI 10.1007/s10439-022-03020-0
View details for PubMedID 35922726
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Physics-Informed Machine Learning Improves Detection of Head Impacts.
Annals of biomedical engineering
2022
Abstract
In this work we present a new physics-informed machine learning model that can be used to analyze kinematic data from an instrumented mouthguard and detect impacts to the head. Monitoring player impacts is vitally important to understanding and protecting from injuries like concussion. Typically, to analyze this data, a combination of video analysis and sensor data is used to ascertain the recorded events are true impacts and not false positives. In fact, due to the nature of using wearable devices in sports, false positives vastly outnumber the true positives. Yet, manual video analysis is time-consuming. This imbalance leads traditional machine learning approaches to exhibit poor performance in both detecting true positives and preventing false negatives. Here, we show that by simulating head impacts numerically using a standard Finite Element head-neck model, a large dataset of synthetic impacts can be created to augment the gathered, verified, impact data from mouthguards. This combined physics-informed machine learning impact detector reported improved performance on test datasets compared to traditional impact detectors with negative predictive value and positive predictive values of 88 and 87% respectively. Consequently, this model reported the best results to date for an impact detection algorithm for American football, achieving an F1 score of 0.95. In addition, this physics-informed machine learning impact detector was able to accurately detect true and false impacts from a test dataset at a rate of 90% and 100% relative to a purely manual video analysis workflow. Saving over 12 h of manual video analysis for a modest dataset, at an overall accuracy of 92%, these results indicate that this model could be used in place of, or alongside, traditional video analysis to allow for larger scale and more efficient impact detection in sports such as American Football.
View details for DOI 10.1007/s10439-022-02911-6
View details for PubMedID 35303171
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Salivary S100 calcium-binding protein beta (S100B) and neurofilament light (NfL) after acute exposure to repeated head impacts in collegiate water polo players.
Scientific reports
2022; 12 (1): 3439
Abstract
Blood-based biomarkers of brain injury may be useful for monitoring brain health in athletes at risk for concussions. Two putative biomarkers of sport-related concussion, neurofilament light (NfL), an axonal structural protein, and S100 calcium-binding protein beta (S100B), an astrocyte-derived protein, were measured in saliva, a biofluid which can be sampled in an athletic setting without the risks and burdens associated with blood sampled by venipuncture. Samples were collected from men's and women's collegiate water polo players (n=65) before and after a competitive tournament. Head impacts were measured using sensors previously evaluated for use in water polo, and video recordings were independently reviewed for the purpose of validating impacts recorded by the sensors. Athletes sustained a total of 107 head impacts, all of which were asymptomatic (i.e., no athlete was diagnosed with a concussion or more serious). Post-tournament salivary NfL was directly associated with head impact frequency (RR=1.151, p=0.025) and cumulative head impact magnitude (RR=1.008, p=0.014), while controlling for baseline salivary NfL. Change in S100B was not associated with head impact exposure (RR<1.001, p>0.483). These patterns suggest that repeated head impacts may cause axonal injury, even in asymptomatic athletes.
View details for DOI 10.1038/s41598-022-07241-0
View details for PubMedID 35236877
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Identifying Factors Associated with Head Impact Kinematics and Brain Strain in High School American Football via Instrumented Mouthguards.
Annals of biomedical engineering
2021
Abstract
Repeated head impact exposure and concussions are common in American football. Identifying the factors associated with high magnitude impacts aids in informing sport policy changes, improvements to protective equipment, and better understanding of the brain's response to mechanical loading. Recently, the Stanford Instrumented Mouthguard (MiG2.0) has seen several improvements in its accuracy in measuring head kinematics and its ability to correctly differentiate between true head impact events and false positives. Using this device, the present study sought to identify factors (e.g., player position, helmet model, direction of head acceleration, etc.) that are associated with head impact kinematics and brain strain in high school American football athletes. 116 athletes were monitored over a total of 888 athlete exposures. 602 total impacts were captured and verified by the MiG2.0's validated impact detection algorithm. Peak values of linear acceleration, angular velocity, and angular acceleration were obtained from the mouthguard kinematics. The kinematics were also entered into a previously developed finite element model of the human brain to compute the 95th percentile maximum principal strain. Overall, impacts were (mean ± SD) 34.0 ± 24.3 g for peak linear acceleration, 22.2 ± 15.4 rad/s for peak angular velocity, 2979.4 ± 3030.4 rad/s2 for peak angular acceleration, and 0.262 ± 0.241 for 95th percentile maximum principal strain. Statistical analyses revealed that impacts resulting in Forward head accelerations had higher magnitudes of peak kinematics and brain strain than Lateral or Rearward impacts and that athletes in skill positions sustained impacts of greater magnitude than athletes in line positions. 95th percentile maximum principal strain was significantly lower in the observed cohort of high school football athletes than previous reports of collegiate football athletes. No differences in impact magnitude were observed in athletes with or without previous concussion history, in athletes wearing different helmet models, or in junior varsity or varsity athletes. This study presents novel information on head acceleration events and their resulting brain strain in high school American football from our advanced, validated method of measuring head kinematics via instrumented mouthguard technology.
View details for DOI 10.1007/s10439-021-02853-5
View details for PubMedID 34549342
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Predictive Factors of Kinematics in Traumatic Brain Injury from Head Impacts Based on Statistical Interpretation.
Annals of biomedical engineering
2021
Abstract
Brain tissue deformation resulting from head impacts is primarily caused by rotation and can lead to traumatic brain injury. To quantify brain injury risk based on measurements of kinematics on the head, finite element (FE) models and various brain injury criteria based on different factors of these kinematics have been developed, but the contribution of different kinematic factors has not been comprehensively analyzed across different types of head impacts in a data-driven manner. To better design brain injury criteria, the predictive power of rotational kinematics factors, which are different in (1) the derivative order (angular velocity, angular acceleration, angular jerk), (2) the direction and (3) the power (e.g., square-rooted, squared, cubic) of the angular velocity, were analyzed based on different datasets including laboratory impacts, American football, mixed martial arts (MMA), NHTSA automobile crashworthiness tests and NASCAR crash events. Ordinary least squares regressions were built from kinematics factors to the 95% maximum principal strain (MPS95), and we compared zero-order correlation coefficients, structure coefficients, commonality analysis, and dominance analysis. The angular acceleration, the magnitude and the first power factors showed the highest predictive power for the majority of impacts including laboratory impacts, American football impacts, with few exceptions (angular velocity for MMA and NASCAR impacts). The predictive power of rotational kinematics about three directions (x: posterior-to-anterior, y: left-to-right, z: superior-to-inferior) of kinematics varied with different sports and types of head impacts.
View details for DOI 10.1007/s10439-021-02813-z
View details for PubMedID 34244908
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Time Window of Head Impact Kinematics Measurement for Calculation of Brain Strain and Strain Rate in American Football.
Annals of biomedical engineering
2021
Abstract
Wearable devices have been shown to effectively measure the head's movement during impacts in sports like American football. When a head impact occurs, the device is triggered to collect and save the kinematic measurements during a predefined time window. Then, based on the collected kinematics, finite element (FE) head models can calculate brain strain and strain rate, which are used to evaluate the risk of mild traumatic brain injury. To find a time window that can provide a sufficient duration of kinematics for FE analysis, we investigated 118 on-field video-confirmed football head impacts collected by the Stanford Instrumented Mouthguard. The simulation results based on the kinematics truncated to a shorter time window were compared with the original to determine the minimum time window needed for football. Because the individual differences in brain geometry influence these calculations, we included six representative brain geometries and found that larger brains need a longer time window of kinematics for accurate calculation. Among the different sizes of brains, a pre-trigger time of 40ms and a post-trigger time of 70ms were found to yield calculations of brain strain and strain rate that were not significantly different from calculations using the original 200ms time window recorded by the mouthguard. Therefore, approximately 110ms is recommended for complete modeling of impacts for football.
View details for DOI 10.1007/s10439-021-02821-z
View details for PubMedID 34231091
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Head impact exposure and concussion in women's collegiate club lacrosse
RESEARCH IN SPORTS MEDICINE
2021: 1-6
Abstract
This study sought to describe head impact exposure in women's collegiate club lacrosse. Eleven women's collegiate club lacrosse players wore head impact sensors during eight intercollegiate competitions. Video recordings of competitions were used to verify impact data. Athletes completed questionnaires detailing their concussion history and perceived head impact exposure. During the monitored games, no diagnosed concussions were sustained. Three athletes reported sustaining head impacts (median = 0; range: 0-3 impacts per game). Six impacts registered by the sensors were verified on video across a total of 81 athlete-game exposures. Verified impacts had a median peak linear acceleration of 21.0 g (range: 18.3 g - 48.3 g) and peak rotational acceleration of 1.1 krad/s2 (range: 0.7 krad/s2 - 5.7 krad/s2). Women competing in collegiate club lacrosse are at a low risk of sustaining head impacts, comparable to previous reports of the high school and collegiate varsity levels of play.
View details for DOI 10.1080/15438627.2021.1929226
View details for Web of Science ID 000651267000001
View details for PubMedID 33998942
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A new open-access platform for measuring and sharing mTBI data.
Scientific reports
2021; 11 (1): 7501
Abstract
Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between impact severity and brain injury risk through the use of wearable sensors and neurological testing. However, as the number of institutions operating these studies grows, there is a growing need for a platform to share these data to facilitate our understanding of concussion mechanisms and aid in the development of suitable diagnostic tools. To that end, this paper puts forth two contributions: (1) a centralized, open-access platform for storing and sharing head impact data, in collaboration with the Federal Interagency Traumatic Brain Injury Research informatics system (FITBIR), and (2) a deep learning impact detection algorithm (MiGNet) to differentiate between true head impacts and false positives for the previously biomechanically validated instrumented mouthguard sensor (MiG2.0), all of which easily interfaces with FITBIR. We report 96% accuracy using MiGNet, based on a neural network model, improving on previous work based on Support Vector Machines achieving 91% accuracy, on an out of sample dataset of high school and collegiate football head impacts. The integrated MiG2.0 and FITBIR system serve as a collaborative research tool to be disseminated across multiple institutions towards creating a standardized dataset for furthering the knowledge of concussion biomechanics.
View details for DOI 10.1038/s41598-021-87085-2
View details for PubMedID 33820939
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Patterns of head impact exposure in men's and women's collegiate club water polo
JOURNAL OF SCIENCE AND MEDICINE IN SPORT
2020; 23 (10): 927–31
Abstract
Recent reports have demonstrated a risk of concussion and subconcussive head impacts in collegiate varsity and international elite water polo. We sought to characterize patterns of head impact exposure at the collegiate club level of water polo.Prospective cohort study.Head impact sensors (SIM-G, Triax Technologies) were worn by men's (n=16) and women's (n=15) collegiate club water polo players during 11 games. Peak linear acceleration (PLA) and peak rotational acceleration (PRA) of head impacts were recorded by the sensors. Two streams of competition video were used to verify and describe the nature of head impacts.Men's players sustained 52 verified head impacts of magnitude 39.7±16.3g PLA and 5.2±3.2 krad/s2 PRA, and women's players sustained 43 verified head impacts of magnitude 33.7±12.6g PLA and 4.0±2.8krad/s2 PRA. Impacts sustained by men had greater PLA than those sustained by women (p=.045). Athletes were impacted most frequently at the offensive center position, to the back of the head, and by an opponent's torso or limb.Our cohort of male and female athletes sustained relatively infrequent head impacts during water polo competitions played at the collegiate club level. The amount of head impact exposure in our cohort was dependent on player position, with offensive centers prone to sustaining the most impacts. Head impact sensors are subject to large amounts of false positives and should be used in conjunction with video recordings to verify the validity of impact data.
View details for DOI 10.1016/j.jsams.2020.03.008
View details for Web of Science ID 000566905200007
View details for PubMedID 32303477
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Effects of soccer ball inflation pressure and velocity on peak linear and rotational accelerations of ball-to-head impacts
SPORTS ENGINEERING
2020; 23 (1)
View details for DOI 10.1007/s12283-020-00331-0
View details for Web of Science ID 000568564500001
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A Dose Relationship Between Brain Functional Connectivity and Cumulative Head Impact Exposure in Collegiate Water Polo Players
FRONTIERS IN NEUROLOGY
2020; 11: 218
Abstract
A growing body of evidence suggests that chronic, sport-related head impact exposure can impair brain functional integration and brain structure and function. Evidence of a robust inverse relationship between the frequency and magnitude of repeated head impacts and disturbed brain network function is needed to strengthen an argument for causality. In pursuing such a relationship, we used cap-worn inertial sensors to measure the frequency and magnitude of head impacts sustained by eighteen intercollegiate water polo athletes monitored over a single season of play. Participants were evaluated before and after the season using computerized cognitive tests of inhibitory control and resting electroencephalography. Greater head impact exposure was associated with increased phase synchrony [r(16) > 0.626, p < 0.03 corrected], global efficiency [r(16) > 0.601, p < 0.04 corrected], and mean clustering coefficient [r(16) > 0.625, p < 0.03 corrected] in the functional networks formed by slow-wave (delta, theta) oscillations. Head impact exposure was not associated with changes in performance on the inhibitory control tasks. However, those with the greatest impact exposure showed an association between changes in resting-state connectivity and a dissociation between performance on the tasks after the season [r(16) = 0.481, p = 0.043] that could also be attributed to increased slow-wave synchrony [F(4, 135) = 113.546, p < 0.001]. Collectively, our results suggest that athletes sustaining the greatest head impact exposure exhibited changes in whole-brain functional connectivity that were associated with altered information processing and inhibitory control.
View details for DOI 10.3389/fneur.2020.00218
View details for Web of Science ID 000596930200001
View details for PubMedID 32300329
View details for PubMedCentralID PMC7145392
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Laboratory evaluation of a wearable head impact sensor for use in water polo and land sports
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART P-JOURNAL OF SPORTS ENGINEERING AND TECHNOLOGY
2020; 234 (2): 162–69
View details for DOI 10.1177/1754337120901974
View details for Web of Science ID 000513321000001
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Comparison of head impact attenuation capabilities between a standard American football helmet and novel protective equipment that couples a helmet and shoulder pads
SPORTS ENGINEERING
2019; 22 (3-4)
View details for DOI 10.1007/s12283-019-0311-8
View details for Web of Science ID 000484462300001
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Head impacts sustained by male collegiate water polo athletes
PLOS ONE
2019; 14 (5): e0216369
Abstract
Water polo is a contact sport that is gaining popularity in the United States and carries a risk of repeated head impacts and concussion. The frequency and magnitude of sport-related head impacts have not been described for water polo. We aimed to compare patterns of empirically measured head impact exposure of male collegiate water polo players to patterns previously reported by a survey of current and former water polo athletes. Participants wore water polo caps instrumented with head impact sensors during three seasons of collegiate water polo. Peak linear acceleration (PLA) and peak rotational acceleration (PRA) were recorded for head impacts. Athlete positions were recorded by research staff at the occurrence of each head impact. Head impacts were sustained by athletes in offensive positions more frequently than in defensive and transition positions (246, 59.9% vs. 93, 22.6% vs. 72, 17.5%). 37% of all head impacts during gameplay were sustained by athletes playing the offensive center position. Impact magnitude (means ± SD: PLA = 36.1±12.3g, PRA = 5.0±2.9 krads/sec2) did not differ between position or game scenario. Among goalies, impact frequency and magnitude were similar between games (means ± SD: 0.54±.51 hits/game, PLA = 36.9±14.2g, PRA = 4.3±4.2 krads/sec2) and practices (means ± SD: 0.96±1.11 hits/practice, PLA = 43.7±14.5g, PRA = 3.9±2.5 krads/sec2). We report that collegiate water polo athletes are at risk for sport-related head impacts and impact frequency is dependent on game scenario and player position. In contrast, magnitude does not differ between scenarios or across positions.
View details for DOI 10.1371/journal.pone.0216369
View details for Web of Science ID 000466511200077
View details for PubMedID 31048869
View details for PubMedCentralID PMC6497298
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The Effectiveness of Protective Headgear in Attenuating Ball-to-Forehead Impacts in Water Polo.
Frontiers in sports and active living
2019; 1: 2
Abstract
Recent reports have demonstrated that there is a serious risk of head impact and injury in water polo. The use of protective headgear in contact sports is a commonly accepted strategy for reducing the risk of head injury, but there are few available protective headgears for use in water polo. Many of those that are available are banned by the sport's governing bodies due to a lack of published data supporting the effectiveness of those headgears in reducing head impact kinematics. To address this gap in knowledge, we launched a water polo ball at the forehead of an anthropomorphic testing device fitted with either a standard water polo headgear or one of two protective headgears. We selected a range of launch speeds representative of those observed across various athlete ages. Mixed-model ANOVAs revealed that, relative to standard headgear, protective headgears reduced peak linear acceleration (by 10.8-21.6%; p < 0.001), and peak rotational acceleration (by 24.5-48.5%; p < 0.001) induced by the simulated ball-to-forehead impacts. We discuss the possibility of using protective headgears in water polo to attenuate head impact kinematics.
View details for DOI 10.3389/fspor.2019.00002
View details for PubMedID 33344926
View details for PubMedCentralID PMC7739673