David Pitman

THink: Inferring Cognitive Status from Subtle Behaviors

The Digital Clock Drawing Test is a fielded application that provides a major advance over existing neuropsychological testing technology. It captures and analyzes high precision information about both outcome and process, opening up the possibility of detecting subtle cognitive impairment even when test results appear superficially normal. We describe the design and development of the test, document the role of AI in its capabilities, and report on its use over the past seven years. We outline its potential implications for earlier detection and treatment of neurological disorders. We also set the work in the larger context of the THink project, which is exploring multiple approaches to determining cognitive status through the detection and analysis of subtle behaviors.

Display requirements for an interactive rail scheduling display

This work, a collaboration between Alstom Transport and the MIT Humans and Automation Laboratory (HAL), is focused on the development of an interactive in-cab scheduling interface for train operators. Currently, operators rely on a combination of paper schedules, paper speed charts, and rote memorization to meet the many demands of train operation. The separation of this information over multiple sources shifts driver attention away from the windscreen and may result in increased workload levels and safety compromises. A Hybrid Cognitive Task Analysis (hCTA), which derives the information requirements necessary to meet mission goals directly from operational tasks, was conducted to generate cognitive requirements for the desired scheduling display. The resulting seventeen requirements were used to guide the development of a new scheduling display, which is presented.

Development and Testing of a Quad Rotor Smartphone Control System for Novice Users

With recent regulatory efforts to reduce restrictions placed on the operation of Micro Air Vehicles (MAVs) in the United States, it is likely that in the next few years, these vehicles will become commonplace in the commercial marketplace as they are in military environments. In order to reduce the barrier to entry for operations of MAVs, customers of these systems will require ease of operation as well as minimal training time in order to reduce costs. To this end, a smartphone application was developed to control a quadrotor remotely in the exploration of an unknown environment, and tested for users with only three minutes of training. Initial motion capture room tests produced encouraging results for localization and target identification tasks, however, such environments are inherently artificial and the extensibility of such results is limited. A follow-on outdoor field study was conducted in order to compare the indoor and outdoor results and to assess operator performance in a realistic environment. Performance on the outdoor localization tasks was comparable to the indoor study, however, participants generally performed slightly worse on the target identification task in the outdoor experiment, attributed to camera image quality and GPS localization issues. Other issues such as wind and flight safety considerations are discussed.