# US 11,026,621 B1 · Collaborative concussion sensing system for better concussion prediction

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- Number: US 11,026,621 B1
- Document ID: US11026621B1
- Status: Granted
- Kind: B1
- Application number: 17/025,907
- Filed: 2020-09-18
- Granted: 2021-06-08
- Earliest claimed: 2020-09-18
- Assignees: Aegis of Soteria LLC
- Applicants: Maddox J Yu; Aaliyah J Yu
- Inventors: Maddox J Yu; Aaliyah J Yu
- Web page: https://patentgrep.com/patent/US11026621B1

## CPC

- A61B 5/002: {Monitoring the patient using a local or closed circuit, e.g. in a room or building (A61B5/0017 takes precedence)}
- A61B 5/4064: {Evaluating the brain (for intracranial pressure A61B5/031; for cerebral blood gases A61B5/14553; using EEG A61B5/369)}
- A61B 5/0004: {characterised by the type of physiological signal transmitted}
- A61B 5/0022: {Monitoring a patient using a global network, e.g. telephone networks, internet}
- A61B 5/6803: {Head-worn items, e.g. helmets, masks, headphones or goggles}
- A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems}
- A61B 5/7275: {Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor}
- A61B 5/7282: {Event detection, e.g. detecting unique waveforms indicative of a medical condition (cough events A61B5/0823; seizures A61B5/4094; sleep apnoea A61B5/4818)}
- A61B 2503/10: Athletes
- A61B 2505/09: Rehabilitation or training
- A61B 2562/0219: Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
- A61B 2562/08: Sensors provided with means for identification, e.g. barcodes or memory chips
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)

## Abstract

A system that uses information from multiple players involved in an impact to improve the measurement of impact g-force by collaborative analysis and hence improve the prediction of the risk of concussion for an athlete, which includes a wearable device with an impact sensor and an application processor, and a smartphone mobile application. The wearable device is mounted to the player's helmet or other locations where the impact force to the head is measured. The wearable device wirelessly communicates with a smartphone, where the measured g-force, including magnitude and direction, from the wearable device, is obtained and an iterative optimization algorithm is run to make the correction and/or optimization of the measurement based on the law of physics. The said iterative optimization algorithm takes into the consideration of the data from all players involved in the impact, and minimize the error based on the law of physics. Potentially a cloud-based data storage system and an algorithm improvement system can be included. The impact force data and all related information can be uploaded from the smartphone to a cloud-based database for storage. An algorithm improvement system will periodically analyze the data in order to build a better collaborative analysis algorithm for optimization. Once a better optimization algorithm is identified, such an algorithm will be sent to or downloaded by the smartphone for better analysis.

## Claims

### Claim 1

A system that uses information from multiple players involved in an impact to improve the measurement accuracy of impact g-force and hence improve the prediction accuracy of the risk of concussion for an athlete, comprising:
wearable devices operatively worn on the head of multiple athletes, each of which contains an impact force measurement sensor to measure the impact g-force, an application processor to process the impact g-force, and a wireless communication processor to send information to a smartphone;
a smartphone mobile application that connects wirelessly to said wearable devices, wherein the measured impact g-force, including magnitude and direction, from the wearable devices, are obtained wirelessly, and an iterative optimization algorithm is run to make a correction and/or optimization of the measurement accuracy based on conservation of momentum which takes into consideration the impact g-force from all players involved in the impact and minimizes measurement error.

### Claim 2 (depends on 1)

The system of claim 1 wherein:
the smartphone mobile application is configured to collect location and speed data from all players involved in the impact and to feed the location and speed data into the iterative optimization algorithm in order to improve the measurement accuracy; and
to pre-register weight information of each player who is involved in the impact and to feed the weight information into the iterative optimization algorithm in order to improve the measurement accuracy.