Professor Stirling’s research aims to quantify human performance and human-machine fluency in operational settings by advancing the use of wearable sensors for space, medical, industry, and military applications. Quantifying these measures is key for augmenting human performance, mitigating injury risk, and providing relevant feedback to subject matter experts across many domains. Development of human-in-the-loop applications requires understanding the human capability to complete required tasks while utilizing additional technology, such as exosystems (rigid exoskeletons and soft exosuits) or tele-robots.

Seamus Lombardo testing spacesuit gloves and a lunar landing simulator to understand how glove static fit affects task performance.

In many domains, human motor performance is assessed visually by subject matter experts, but what is needed is the capability to assess performance when direct visual assessment is not possible. We enhance the ability to make decisions when the person is not observable (e.g., an astronaut in a spacesuit), the subject matter expert is not present (e.g., telehealth), the action is fast (e.g., military readiness), or the system is responsive (e.g., exosystems) by enabling wearable sensors to quantify these qualitative assessments. While wearable sensors passively sense information about humans or their environment, exosystems are technologies that actively affect human motor actions, and may restore, enhance, or provide new human perceptual, cognitive, or physical abilities. The active assist is informed by sensors and needs to anticipate and co-adapt with the operator.

In each of these applications, there can be multiple stakeholders, the person being measured may be different from the person (or people) making the decision. For wearable technology or telerobotic applications, the robotic system is an additional interpreter of the information. The quantified metrics must be defined and considered in the context of the task and presented in a manner that is usable by the relevant stakeholder. Research in the Stirling Lab is interdisciplinary and includes human factors, biomechanics, signal processing, and control system design.  

Additional Research Pages