Detection and Prevention of Concussive Injuries With Smart Technology.

Concussion Clinical Trial

Official title:

Detection and Prevention of Concussive Injuries With Smart Technology.

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT04946747
• Other study ID #: 19-013
• Status: Not yet recruiting
• Phase: N/A
• Start date: June 2021
• Est. completion date: April 10, 2022

Study information

• Verified date: June 2021
• Source: University of Missouri, Kansas City
• Contact: Kim Dyer, MSN
• Phone: 816.404.1380
• Email: kim.dyer[@]tmcmed.org
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Concussions are consequences of inopportune interactions between an impact force and the head that causes the head (and brain) to move too rapidly. This project involves two parts. 1. The outcome of head-impact depends upon the force and the biomechanical properties of the head-and-neck. Modern microelectrical mechanical systems (MEMS) head-impact sensors only measure the physical parameters of external forces. The researchers have developed a next-generation smart MEMS sensor fortified with artificial intelligence (AI) that can help define a personalized concussive threshold. The researchers sensor machine-learns the biomechanical properties of the participant's head-and-neck and accurately determines the likelihood for concussive injuries. The researchers first goal is to field-test the sensor in soccer players. 2. Researchers hypothesize that an increase in neck stiffness should reduce concussive risks. The researchers have developed a training protocol that involves a conditioned response (CR) to increase neck stiffness during a head-impact event and thereby decrease concussion risk. The Researchers have also developed technology to monitor neck stiffness. The smart sensor is fully integrated into the training protocol and monitors the neck stiffness to validate the effectiveness of the training. The second goal is to optimize and finalize our training protocol and conduct a field-test in soccer players.

Description:

The hypothesis is that MEMS sensors fortified with artificial intelligence and machine learning can incorporate individualized human factors into consideration and help to define concussive threshold for diagnosis that is personalized as in precision medicine. In laboratory tests, the prototype smart sensor the researchers built can machine-learn the biomechanical properties of the head-and-neck of the user without being programmed with that information. It then measures the magnitude of the impact against a personalized threshold of the user, in real time. These capabilities allow the smart sensor to accurately determine the potential for concussive injuries for a given individual. The first aim is (a) to optimize and finalize the sensor into a wearable, field-test-ready prototype and (b) to conduct a field-test in soccer players in order to examine the accuracy of the sensors in setting personalized concussive thresholds. The hypothesis is that the dynamic increase in neck stiffness should reduce concussive risks significantly. The smart sensor is fully integrated into the training in order to monitor the increase in neck stiffness and validate the effectiveness of the acquired CR in reducing concussion risks. The second aim therefore is (a) to optimize and finalize our training protocol and (b) to conduct a field-test in soccer players. The long-term objectives are to develop methods and technology for rapid and reliable concussion risk assessment in the field as well as for the prevention and mitigation of concussive injuries. PROCEDURES Part 1 of study: Study information will be given to parents and soccer players (study participants) by Dr. Moncure and Dr. Huang at the Local soccer academy during normal hours. This will be a one-time session for approximately 1 hour, depending on questions. The study information provided by investigators will also be recorded on video in order to assure that all parents and soccer players receive the same information even if they are not present at the meeting. All players will be given the opportunity to participate based on inclusion and exclusion criteria. Informed Consent and Assent will be reviewed with participants and parents by Dr. Moncure at the Local soccer academy after parents and soccer players have been fully informed of the study and their participation requirements. All participants and their parents must attend the informational session or watch the study informational video prior to participation. All study related questions will be answered by the Dr. Moncure or Dr. Huang. Completing the ICF and Assent will occur after the study informational session and will take approximately 30 minutes. A Training session will be held to show all Local soccer academy trainers how the sensors work and how the sensors are affixed to the players. Later, the trainers will see to it that the soccer players will properly wear the sensors every time during practice. This training session will take approximately 30 minutes. Once a participant has been enrolled, the participant can begin wearing the sensor during training or playing soccer at Local soccer academy. Sensors will be worn over a period of at least 4 weeks when the players are at the Local soccer academy. The participant has completed Part 1 at the end of 4 weeks. The purpose of Part 1 is to collect head movement data from the soccer players before concussion avoidance training. Part 2 of study: Randomization of participants will occur. Participants will be randomized into 2 groups -- Trained group and Control group. Trainers will be shown how to conduct the Virtual Reality (VR) training session. Trainers will be shown proper placement of the head-impact sensor system to measure participant response to training. After Part 1 of the study has been completed, the participants will be randomized and divided into the Trained group and the Control group. Considerations will be given to obtain the best possible age-match and gender match in the Trained group and the control group. Both groups will be shown how to use the Virtual Reality goggles. During the one to two week VR training period, both groups will be using the VR goggles. The Trained group will have the conditioned stimulus (CS, images of opposing players approaching) and the unconditioned stimulus (US, a voice cue to stiffen the neck by the coach) always being delivered with a consistent timing relationship (e.g. a 250 msec delay between the CS and the US), causing the conditioned response (neck stiffening) to emerge. The Control group will also receive the same CS and the same US, but the CS and the US will bear no consistent timing relationship, therefore never causing any CR to emerge. Both groups will also wear our smart head-impact sensor system to measure their response to training. One purpose of this arrangement is to provide an avenue for a double-blind analysis. A second purpose will be the provision for an age-and gender-matched control group for the study. CR training will be carried out over a period of approximately 10 days with daily 30-minute sessions (or roughly over a period of one to two weeks). The training involves wearing the VR goggles and our smart head-impact sensor system (head sensor and body sensor), at the local soccer academy in the training area. The participant will receive virtual visual stimuli of usual soccer play as CS. The participant will also receive a mildly unpleasant auditory stimuli (such as those from a coach) as US. The training will be done in the local soccer academy training room, with only those randomized participants and their trainers present. The Control group will also participate in VR training but will not know that they are in the Control group. All data will be kept within software that comes with the sensors and VR goggles. Once the CR training has been completed, all participants will again wear our smart sensors whenever they are playing soccer at the local soccer academy for another 4 weeks. Informed Consent and Assent forms will be completed in person, original copies will be collected and stay with the Investigators, a copy of both will be given to the participants. All other data will be collected electronically. Sensors send data directly to researcher (Chi-Ming Huang).

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 100
• Est. completion date: April 10, 2022
• Est. primary completion date: December 17, 2021
• Accepts healthy volunteers: No
• Gender: All
• Age group: 7 Years to 17 Years

Eligibility

Inclusion Criteria:

• Local soccer academy soccer player, Age 7-17,
• Agrees to participate in study, (signed Assent),
• Parent agrees to child's participation in study (signed consent)

Exclusion Criteria:

• Any individual who does not agree to participate,
• Any individual whose parent does not agree to having their child participate,
• Individual who is unable or unwilling to wear a sensor

Related Conditions & MeSH terms

• Concussion
• Craniocerebral Trauma
• Head Injury Trauma
• Wounds and Injuries

Intervention

Device:
• Modern microelectrical mechanical systems (MEMS) head-impact sensors
Both groups will wear our smart head-impact sensor system (MEMS head-impact sensors) to measure their response to training.

Other:
• Virtual Reality (VR) Goggle Use with consistent timing of Conditioned Stimulus and Unconditioned Stimulus
The Trained group will have the conditioned stimulus (CS, images of opposing players approaching) and the unconditioned stimulus (US, a voice cue to stiffen the neck by the coach) always being delivered with a consistent timing relationship (e.g. a 250 msec delay between the CS and the US), causing the conditioned response (neck stiffening) to emerge.
• Virtual Reality (VR) Goggle Use with inconsistent timing of Conditioned Stimulus and Unconditioned Stimulus
The Control group will also receive the same CS and the same US as trained group, but the CS and the US will bear no consistent timing relationship, therefore never causing any CR to emerge.

Locations

Country	Name	City	State
n/a

Sponsors (2)

Lead Sponsor	Collaborator
Chi-Ming Huang	UMKC School of Medicine

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Examine the accuracy of our sensors in setting personalized concussive thresholds.	We aim to capture data on head impact events or head movements from male and female human subjects. The name of the measurement tool is accelerometers or inertia measurement unit (IMU). One such example is the vector mouthguard sensor marketed by Athlete Intelligence (Seattle, WA). We are also engaged in the development of this technology. These data we will assess includes head angular velocities and accelerations. When such data is processed and assessed, we can query the data with our machine-learning algorithms in order to derive data on putative concussive threshold. The results of such queries will inform us whether concussive threshold may have a gender-specific component.	3 months
Primary	Monitor neck stiffness of participants in 2 groups (Trained versus Control) while using virtual reality goggles.	We aim to monitor neck stiffness of participants in 2 groups. The name of the measurement tool is accelerometers or inertia measurement unit (IMU). One such example is the vector mouthguard sensor marketed by Athlete Intelligence (Seattle, WA). We are also engaged in the development of this technology. More specifically, if a pair of such sensors are affixed to a human subject, we can assess, compare, and compute from the outputs (on head angular velocities and accelerations) of the pair and determine the relative discrepancies between the output of the pair. The stiffness measure, including neck stiffness, is inversely proportional to the amount of the said discrepancies described above. The results of such comparison and computation will therefore inform us whether neck stiffness can be modified by training with virtual reality goggles.	3 months
Primary	Optimize and finalize our training protocol	We aim to train human subjects in stiffing the neck prior to impact. The impact will be delivered in virtual reality such that the human subject is not getting a real impact. Participants in training will nevertheless acquire the neck-stiffening reflex upon "sensing" the impact in virtual reality. We, as investigators, will monitor the data on neck stiffness as described previously in our reply to comment 2. One goal of such monitoring is for us to optimize our detailed training protocol. As before in comments 1 and 2, the name of the measurement tool is accelerometers or inertia measurement unit (IMU). The expected outcome is that in the two groups of human subjects (trained vs. control as described in comment 2), the trained group will show significantly increases in neck stiffness upon impact compared with the control group.	5 months