Research | Sensing in Biomechanical Processes Lab (SimPL)

Immediate Neurophysiological Effects of Head Impacts

Our lab is developing sensitive and quantitative methods to evaluate the immediate electrophysiological changes after sports head impacts. Our preliminary results have shown that even the mildest sports head impacts could cause transient, subtle electroencephalogram (EEG) changes across the brain, lasting on the order of seconds. Higher severity impacts or higher frequency impacts may lead to higher levels of physiological changes requiring longer recovery time. This is a first investigation to quantify immediate physiological effects of impacts that are traditionally thought to be mild and non-injurious, which could shed light on the mechanisms of brain changes resulting from mild repetitive sports head impact exposure.

Mobile Brain and Body Imaging (MoBI) Systems

Mobile brain/body imaging (MoBI) is an emerging research approach that leverages technological advancements in wearable technologies for brain and body sensing in dynamic environments. Despite some pilot work in this area, there is a substantial gap between currently available technologies and actual out-of-the-laboratory data collection, due to technological limitations, usability issues, data quality concerns, complexity of real-world stimuli, limited sensing modality, and high individual variability. We are interested in developing and applying MoBI technology to study brain processes and brain health in everyday, natural scenarios.

The Instrumented Mouthguard

In Dr. Wu’s PhD work, she developed an instrumented mouthguard containing a triaxial accelerometer and a triaxial gyroscope to measure linear and rotational motion of the head during head impacts. The mouthguard gives us an accurate measurement of skull kinematics, which we can use to simulate brain deformation using finite element modeling. So far, this device has been deployed in football, women’s lacrosse, mixed martial arts, and boxing to gather sports head impact data. Such data enable us to study concussions, or mild traumatic bran injuries (mTBI) in humans.

Wu, L.C., Zarnescu, L., Nangia, V., Cam, B., Camarillo, D. A Head Impact Detection System Using SVM Classification and Proximity Sensing in an Instrumented Mouthguard. IEEE Transactions on Biomedical Engineering. 61 (11), 2659–68 (2014). Feature Article. link

Hernandez, F., Wu, L.C., Yip, M.C., Kleiven, S., Hoffman A.R., Lopez, J., Grant, G., Camarillo, D.B. Six Degree of Freedom Measurements of Human Mild Traumatic Brain Injury. Annals of Biomedical Engineering. 43(8), 1918-34 (2015). link

In Vivo Evaluation of Wearable Head Impact Sensors

Current sensors are generally divided into three categories: those mounted on headgear (e.g. helmet sensors), on soft tissue (e.g. skin sensors), and on hard tissue connected to the skull (e.g. mouthguards). We found through high speed stereo video analysis that sensors do not couple well to the skull through headgear or soft tissue. Large sensor errors can result from loose coupling. Thus mounting location is critical to sensor accuracy, and the mouthguard sensor is a promising approach.

Wu, L.C., Nangia, V., Bui, K., Hammoor, B.T., Kurt, M., Hernandez, F., Kuo C., In vivo Evaluation of Wearable Head Impact Sensors. Annals of Biomedical Engineering. 44(4), 1234-45 (2015). link

Head Impact Detection Using Machine Learning

Light wearable inertial sensors can pick up acceleration from any source: mouthguard chewing, throwing, insertion into helmet facemask, etc. We developed a head impact detector using a support vector machine classifier, trained on frequency domain features of linear acceleration and rotational velocity. Since the dynamics of motion differs between head impacts and spurious non-impact events, we could accurately detect head impacts using this method, achieving 99% accuracy.

Investigating Concussion Mechanisms

Through our field deployment of the instrumented mouthguard, we have gathered both injury and non-injury head impact data. Analysis of this data showed that common predictors used to quantify head injury risk, such as peak linear acceleration of the head, were not the best predictors for injury. Instead, brain deformation measures such as brain tissue strain are better predictors of injury. In addition, we found that helmeted head impacts in football may be exciting a resonant frequency of the brain, which implies that the effectiveness of the helmet is questionable.