Impacts to the head are common in collision sports such as football. Emerging research has begun to elucidate concussion tolerance levels, but sub-concussive impacts that do not result in clinical signs or symptoms of concussion are much more common, and are speculated to lead to alterations in cerebral structure and function later in life. We investigated the cumulative number of head impacts and their associated acceleration burden in 95 high school football players across four seasons of play using the Head Impact Telemetry System (HITS). The 4-year investigation resulted in 101,994 impacts collected across 190 practice sessions and 50 games. The number of impacts per 14-week season varied by playing position and starting status, with the average player sustaining 652 impacts. Linemen sustained the highest number of impacts per season (868); followed by tight ends, running backs, and linebackers (619); then quarterbacks (467); and receivers, cornerbacks, and safeties (372). Post-impact accelerations of the head also varied by playing position and starting status, with a seasonal linear acceleration burden of 16,746.1 g , while the rotational acceleration and HIT severity profile burdens were 1,090,697.7 rad/sec ² and 10,021, respectively. The adolescent athletes in this study clearly sustained a large number of impacts to the head, with an impressive associated acceleration burden as a direct result of football participation. These findings raise concern about the relationship between sub-concussive head impacts incurred during football participation and late-life cerebral pathogenesis, and justify consideration of ways to best minimize impacts and mitigate cognitive declines.

Little is known about the impact biomechanics sustained by players during interscholastic football.Context: To characterize the location and magnitude of impacts sustained by players during an interscholastic football season.Objective: Observational design.Design: On the field.Setting: High school varsity football team (n = 35; age = 16.85 ± 0.75 years, height = 183.49 ± 5.31 cm, mass = 89.42 ± 12.88 kg).Patients or Other Participants: Biomechanical variables (linear acceleration, rotational acceleration, jerk, force, impulse, and impact duration) related to head impacts were categorized by session type, player position, and helmet impact location.Main Outcome Measure(s): Differences in grouping variables were found for each impact descriptor. Impacts occurred more frequently and with greater intensity during games. Linear acceleration was greatest in defensive linemen and offensive skill players and when the impact occurred at the top of the helmet. The largest rotational acceleration occurred in defensive linemen and with impacts to the front of the helmet. Impacts with the highest-magnitude jerk, force, and impulse and shortest duration occurred in the offensive skill, defensive line, offensive line, and defensive skill players, respectively. Top-of-the-helmet impacts yielded the greatest magnitude for the same variables.Results: We are the first to provide a biomechanical characterization of head impacts in an interscholastic football team across a season of play. The intensity of game play manifested with more frequent and intense impacts. The highest-magnitude variables were distributed across all player groups, but impacts to the top of the helmet yielded the highest values. These high school football athletes appeared to sustain greater accelerations after impact than their older counterparts did. How this finding relates to concussion occurrence has yet to be elucidated.Conclusions:

There is a lack of information concerning the relation between objective measures of gait and balance and fall history in persons with MS (PwMS). This investigation assessed the relation between demographic, clinical, mobility and balance metrics and falls history in persons with multiple sclerosis (MS). 52 ambulatory persons with MS (PwMS) participated in the investigation. All persons provided demographic information including fall history over the last 12 months. Disease status was assessed with Expanded Disability Status Scale (EDSS). Walking speed, coordination, endurance and postural control were quantified with a multidimensional mobility battery. Over 51% of the participants fell in the previous year with 79% of these people being suffering recurrent falls. Overall, fallers were older, had a greater prevalence of assistive devices use, worse disability, decreased walking endurance, and greater postural sway velocity with eyes closed compared to non-fallers. Additionally, fallers had greater impairment in cerebellar, sensory, pyramidal, and bladder/bowel subscales of the EDSS. The current observations suggest that PwMS who are older, more disabled, utilize an assistive device, have decreased walking coordination and endurance and have diminished balance have fallen in the previous year. This suggests that individuals who meet these criteria need to be carefully monitored for future falls. Future research is needed to determine a prospective model of falls specific to PwMS. Additionally, the utility of interventions aimed at reducing falls and fall risk in PwMS needs to be established.

E monitored all football related head impacts in 78 high school athletes (mean age = 16.7 yr) from 2005 to 2008 to better understand the biomechanical characteristics of concussive impacts. Results: Using the Head Impact Telemetry System, a total of 54,247 impacts were recorded, and 13 concussive episodes were captured for analysis. A classification and regression tree analysis of impacts indicated that rotational acceleration (>5582.3 rad·s−2), linear acceleration (>96.1g), and impact location (front, top, and back) yielded the highest predictive value of concussion. Conclusions: These threshold values are nearly identical with those reported at the collegiate and professional level. If the Head Impact Telemetry System were implemented for medical use, sideline personnel can expect to diagnose one of every five athletes with a concussion when the impact exceeds these tolerance levels. Why all athletes did not sustain a concussion when the impacts generated variables in excess of our threshold criteria is not entirely clear, although individual differences between participants may play a role. A similar threshold to concussion in adolescent athletes compared with their collegiate and professional counterparts suggests an equal concussion risk at all levels of play....

Falls are a major health problem for older adults with significant physical and psychological consequences. A first step of successful fall prevention is to identify those at risk of falling. Recent advancement in sensing technology offers the possibility of objective, low-cost and easy-to-implement fall risk assessment. The objective of this systematic review is to assess the current state of sensing technology on providing objective fall risk assessment in older adults. A systematic review was conducted in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement (PRISMA). Twenty-two studies out of 855 articles were systematically identified and included in this review. Pertinent methodological features (sensing technique, assessment activities, outcome variables, and fall discrimination/prediction models) were extracted from each article. Four major sensing technologies (inertial sensors, video/depth camera, pressure sensing platform and laser sensing) were reported to provide accurate fall risk diagnostic in older adults. Steady state walking, static/dynamic balance, and functional mobility were used as the assessment activity. A diverse range of diagnostic accuracy across studies (47.9% - 100%) were reported, due to variation in measured kinematic/kinetic parameters and modelling techniques. A wide range of sensor technologies have been utilized in fall risk assessment in older adults. Overall, these devices have the potential to provide an accurate, inexpensive, and easy-to-implement fall risk assessment. However, the variation in measured parameters, assessment tools, sensor sites, movement tasks, and modelling techniques, precludes a firm conclusion on their ability to predict future falls. Future work is needed to determine a clinical meaningful and easy to interpret fall risk diagnosis utilizing sensing technology. Additionally, the gap between functional evaluation and user experience to technology should be addressed.