Project Details

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Development of a Mobile Software Application to Assess Cognitive Impairment from Alcohol Intoxication

Company: PSU Decision Neuroscience Laboratory

Major(s):
Primary: CMPSC
Secondary: BME

Non-Disclosure Agreement: NO

Intellectual Property: YES

Alcohol intoxication is a serious public health concern that has significant societal impact. There is a need for the development of an “easy and reliable” technology to track and diagnose cognitive impairments associated with alcohol intoxication. This technology would allow non-invasive collection of data from human users to determine their level of cognitive impairment in order to aid in their decision making (e.g., deciding whether or not to drive home while under the influence of alcohol). The sponsor has developed experimental tasks to assess individual measures of risk preferences and cognitive control, which have been used to explain and identify suboptimal decision making behavior. Importantly, these experimental tasks have been used to identify potential neurophysiological correlates associated with individual differences in risk preference and cognitive control. The sponsor is looking for a creative student team to translate experimental tasks to a software application that will simultaneously collect information from a human user’s phone such as GPS and accelerometer data. Additionally, the sponsor would like the application to be able to integrate and collect data from other biosensors that may be attached to the user’s cellular phone (e.g., breath alcohol concentration, heart rate variability). This software application would support the lab’s data collection efforts aimed at engagement in risky behavior in the real world. The second objective will be to develop a machine learning model that will be able to use data collected from the application to determine the level of cognitive impairment and potentially differential individual states such as “intoxicated” or “sober”. The team will need to: 1) Enhance the design of a user-friendly software application to be used on a cellular device that integrates the sponsor’s cognitive tasks while keeping in mind data collection, storage, and access constraints and is able to access/store any additional data from other proprietary biosensors (i.e., heart rate, breath alcohol concentration); 3) Develop a method for acquiring, time-stamping, storing, and accessing data for researchers; 4) Develop a machine learning model that uses data collected to determine the human user’s a) level of cognitive impairment and b) physiologically-informed state of “intoxicated” or “sober”; Stretch goals: 5) Develop an IRB protocol to collect data from human subjects to validate the software application and demonstrate proof of concept; and 6) Collect data in laboratory and real-world environments.