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.
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