Paper
9 April 2013 Wireless health monitoring helmet for football players to diagnose concussion and track fatigue
Author Affiliations +
Abstract
Football players are regularly exposed to violent impacts. Concussions are mild traumatic brain injuries that are one of the most common injuries experienced by football players. These concussions are often overlooked by football players themselves and the clinical criteria used to diagnose them. The cumulative effect of these mild traumatic brain injuries can cause long-term residual brain dysfunctions. In addition, an athlete’s fatigue level should be monitored to prevent any secondary injuries due to over exertion. Nitric Oxide acts as a metabolic adjustment factor that controls the flow of oxygen in blood and the contraction/relaxation of muscles. Fatigue can be evaluated by measuring the concentration change of nitric oxide in blood. However, measuring the concentration of nitric oxide in blood is not feasible during exercise. Nevertheless, the degree of fatigue can be measured with SpO2 during exercise because the change of nitric oxide also influences the SpO2. In this paper, we propose a wireless health monitoring helmet to diagnose concussions and evaluate fatigue in real time and on the field. The helmet is equipped with sensors and a transmitter module. As sensors, textile based electrodes are used to sense EEG and oximeter sensors are used to derive SpO2. The sensed physiological signals are amplified and processed in the transmitter module. The processed signals are transmitted to a server using Zigbee wireless communication. The EEG signals are classified to diagnose concussion or any abnormality of brain function. In conclusion, the system can monitor and diagnose concussions and evaluate fatigue in football players in real time by measuring their EEGs and SpO2.
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Sechang Oh, Prashanth Shyam Kumar, Hyeokjun Kwon, Pratyush Rai, Mouli Ramasamy, and Vijay K. Varadan "Wireless health monitoring helmet for football players to diagnose concussion and track fatigue", Proc. SPIE 8691, Nanosensors, Biosensors, and Info-Tech Sensors and Systems 2013, 869106 (9 April 2013); https://doi.org/10.1117/12.2009719
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CITATIONS
Cited by 6 scholarly publications and 1 patent.
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KEYWORDS
Electroencephalography

Sensors

Electrodes

Amplifiers

Diagnostics

Linear filtering

Oxygen

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