Search for: All records

Millions of concussions happen each year in the US alone. A proportionally large number of these concussions are due to high impact sports injury. Currently, there exists no solution to quickly monitor brain functions and test the oculomotor functions of individuals who have suffered a traumatic brain injury in order to diagnose them as having suffered a concussion. What is presently done to diagnose concussions is a CT scan or MRI, which are lengthy procedures to schedule, set up, and conduct; and furthermore, takes additional time to analyze the results in order to arrive at a diagnosis. This prolongation of the diagnosing process is inherently problematic since the longer time it takes between time of injury and time of diagnosis, there is greater risk of decisions and actions which can worsen damage to the brain. The sooner a concussion can be diagnosed, the sooner and better the treatment can be performed for recovery. In order to ameliorate this issue, we seek to develop a device to perform the function of diagnosis and monitoring of brain activity in a more rapid and timely manner. Literature review into the anatomy of vestibular and ocular brain functions was performed; as well as research into various testing and monitoring methodologies of these vestibular and ocular functions. One such method that has proven to be a reliable method for diagnosis is Vestibular Ocular Motor Screening (VOMS), which is a visual and balance test performed by a doctor with a patient. Further research was also done into existing technologies whose functionalities would allow the device in order to perform brain monitoring, visual testing, and ultimately diagnosis; namely EEG, VR, and infrared eye tracking. Currently, very few devices on the market take advantage of these technologies together for medical uses. A device incorporating these technologies together allows would allow for more consistent administering of visual tests and real-time monitoring of brain activity. With a functional prototype, user testing is to be performed in order to assess the function and viability of the device. 

Mobile brain-body imaging (MoBI) technology allows the study of the brain in action and the context of complex natural settings. MoBI devices are wearable devices that typically record the scalp electroencephalogram (EEG) and head motion of the user. MoBI systems have applications in neuroscience, rehabilitation, design, and other applications. Here, we propose design principles for MoBI systems for use in brain-machine interfaces for rehabilitation by individuals with movement disabilities. This design study discusses the validity of the process of utilizing 3D anthropometric data as a basis to design a MoBI headset for an optimized fit and ergonomics. The study also discusses the need for ensuring that EEG sensors keep constant contact with the scalp and face for the best scan quality. Moreover, the need for singlehanded correct positioning of the headset is discussed to address disabilities in the older populations and clinical populations with motor impairments. 

Socioeconomic status (SES) has been shown to be related to brain development and cognitive performance. We present a functional NIRS connectivity analysis in children with different SES during a working memory task. 

Pain-related neural mechanisms are not well understood yet. FNIRS could elucidate the hemodynamic responses under pain stimulation. We present a qualitative perspective on brain response to pain in patients suffering from osteoarthritis. 

Conventional bulky and rigid electronics prevents compliant interfacing with soft human skin for health monitoring and human-machine interaction, due to the incompatible mechanical characteristics. To overcome the limitations, soft skin-mountable electronics with superior mechanical softness, flexibility, and stretchability provides an effective platform for intimate interaction with humans. In addition, soft electronics offers comfortability when worn on the soft, curvilinear, and dynamic human skin. In this review, recent advances in soft electronics as health monitors and human-machine interfaces (HMIs) are briefly discussed. Strategies to achieve softness in soft electronics including structural designs, material innovations, and approaches to optimize the interface between human skin and soft electronics are briefly reviewed. Characteristics and performances of soft electronic devices for health monitoring, including temperature sensors, pressure sensors for pulse monitoring, pulse oximeters, electrophysiological sensors, and sweat sensors, exemplify their wide range of utility. Furthermore, we review the soft devices for prosthetic limb, household object, mobile machine, and virtual object control to highlight the current and potential implementations of soft electronics for a broad range of HMI applications. This review concludes with a discussion on the current limitations and future opportunities of soft skin-mountable electronics.