Effectiveness of the Engagement Skills Trainer 2000

The purpose of this article and study is to analyze the effectiveness of the Engagement Skills Trainer 2000 (EST2000), which is the program of record for Army marksmanship training. The EST2000 has only been used for training with the actual marksmanship qualification being done on live ranges. However, the newest version of the rifle qualification course will include a component of shooting on the EST2000. Thus, this study is designed to evaluate the effectiveness of the EST2000 in capturing real-world performance. USMA cadets were recruited to complete the Basic Rifle Marksmanship (BRM) course on the EST2000, and these results were compared to the shooter’s performance on a live BRM course. A paired t-test was conducted to determine whether the EST2000 scores and the BRM scores were statistically different, and an R2 value was calculated to determine the relationship between the soldier’s performance on the EST2000 and real-world performance.

New possible multidimensional models for classification of the basic level of pistol shooting skill

The aim of this paper was to provide a possible methodological solution for monitoring of the marksmanship training progress and evaluation of the level of shooting skill acquisition with service pistol CZ99. The second aim was the idea of development of a screening model for gender-dependent classification of the police personal, other security personnel and sport-oriented personnel in relation to their basic marksmanship skill. The research sample included a total of 83 participants (Men = 53, Women = 30) initially divided into four qualitative categories according to the personal shooting experience and shooting skill level. The applied principal component analysis has revealed a highly stable structure of the component matrix of the extracted factor. The following variables had the highest descriptive value in relation to the shooting skill in the respective samples regardless of distance: Men - an averaged value of the hit circles on the target and rounds fired, the index of efficiency considering precision and a coefficient of variation of hit circle achieved during the shooting at the target; Women - an averaged value of the hit circles on the target and rounds fired, the index of efficiency considering precision, a coefficient of variation of hit circle achieved during the shooting at the target and the index of efficiency considering accuracy. On the basis of the obtained results highly statistically significant (p ≤ 0.000) specific multidimensional models were developed which enabled statistically significant classification of the participants relative to the pistol shooting skill classification. The accuracy of the defined equation model for estimation of shooting skill score classification was 59.7 and 61.5% for men and 68.6 and 68.0% for women in relation to the examined shooting distances of 6 and 10 m, respectively.

Teaching biathletes the rules of shooting using electronic devices

An advanced direction in marksmanship training of biathletes is teaching the rules of shooting: «marking» of a shot; defining the mean point of impact; correcting the sight; offset shooting. Teaching the rules of shooting using electronic devices will help to achieve the aim without a coach and will help to save cartridges. The article presents the description of the teaching programs algorythms for electronic devices.

Index Finger Muscle Fatigue and Pistol Firing Failure

Objective: The aim of this study was to analyze finger strength and effects of muscle fatigue on the ability to shoot. Background: The finger and hand muscles of soldiers are subject to high loads. For example, the trigger pull of military pistols can amount up to 58 N (≈6 kg) and could cause muscle fatigue in the trigger finger. For soldiers, however, maintaining the ability to shoot is essential for self-defense and survival. Method: The marksmanship training of 30 German soldiers (15 female) ages 18 to 40 years was evaluated. Three consecutive exercises with a total of 60 rounds were fired from target ranges of 5 and 10 m, equally using a single-action and double-action trigger mode. Maximum voluntary isometric contraction of the index finger (MVCIF) was measured before and after each of the three firing exercises. Results: Shooting reduced MVCIF in female (88.2 ± 15.8 N to 67.3 ± 17.7 N, p < .001) and male soldiers (145.8 ± 21.7 N to 112.7 ± 26.6 N, p < .001). Of the 30 subjects, 23 were unable to shoot due to fatigue, including 15 of 15 female soldiers. The higher MVCIF was at rest, the less commonly ( r = .73, p < .001) and the later ( r = 0.82, p < .001) task failure occurred. Two intermissions of approximately 6 min did not suffice for a significant recovery. Conclusion: Excessive trigger pull weight causes muscle fatigue of the index finger and can ultimately lead to task failure during pistol marksmanship training. Short breaks are insufficient for the recovery of finger muscles. Application: This study presents a new perspective on ideal trigger pull weight, which should be carefully considered by manufacturers to allow repetitive firing and simultaneously ensure safe handling.

Machine learning for approximated sensors for Marksmanship training

"All people in the military must be proficient on the basics – to shoot, move, and communicate. Basic Rifle Marksmanship (BRM) is required for both noncommissioned and enlisted Warfighters in all branches of military service, with training on BRM skills being conducted in a series of “dry fire”, simulation, and live drills. In all phases of training, Warfighters receive instruction on the four fundamentals of shooting: breathing, body position, sight picture, and trigger squeeze. Within simulation, this training is conducted in a 1:4 to 1:8 range; one instructor per 4-8 students. While realtime individualized feedback is a goal of instruction, it is not a reality, as instructors must attend to the needs of many students. In an effort to aid instructors in providing valuable individualized feedback, a tutoring system was developed which automatically diagnosed novice performance when compared to experts. This system was used to diagnose novice performance with extensive physical sensors applied to the weapons. This work investigates whether machine learning can aid in the diagnosis of the novice performance, without the physical sensors, and analyzes the degree to which the sensors are necessary."