Rachel V. Vitali
People HIR Lab Research Home

Human Instrumentation and Robotics (HIR) Lab

The mission of our lab is to quantify, understand, and distinguish human movement via wearable technologies to better interpret performance, health, and behavior with applications in human-robot interaction. This research is necessarily interdisciplinary and draws from the fields of engineering dynamics, signal processing, robotics, biomechanics, controls, and human factors, to name a few. One of the many challenges associate with this type of work is a comprehensive definition or metric for performance cannot be defined; in fact, most applications require a task-specific definition of performance that has both physical and operational meaning to the stakeholders involved. Below are examples of projects our lab will be pursuing in the near future including a continuation of my postdoctoral research, which has a corresponding website and paper linked below where you can learn more.

We are currently looking for highly motivated and creative graduate and undergraduate students to join our group. Interested students are encouraged to apply for graduate admission and to contact Prof. Vitali via email. Interested undergraduate students should email Prof. Vitali with their resume, academic major, academic standing, and any past research experience.

Scientific Physical and Operational Characterization (SPOC)

Collaborators: Matthew Miller, Leia Stirling
The near future of human space exploration includes sending astronauts back to our moon and then on to Mars within the next few decades. The scientific investigations and pursuits integral to those missions will involve planetary fieldwork to collect geological samples or survey new environments, to name a couple examples. However, there are many challenges to developing field operations for crewmembers during extravehicular activities. For instance, the processes that scientists utilize to achieve their fieldwork objectives in present-day terrestrial settings are not well documented and measures do not currently exist to quantify operational performance for relevant tasks. Further, spacesuits will likely never be able to fully mimic a person’s natural physical movements.

Given what little is known about the physical movements exhibited during scientific fieldwork conducted on Earth, the suit-imposed mobility constraints present potentially significant limitations for future missions. The goal of this research is to characterize physical movements during scientific fieldwork in terms of both biomechanical and motor control capabilities, which will be accomplished with noninvasive wearable sensor technology. By leveraging the portability and noninvasive nature of wearable sensors, expert scientists can more naturally conduct their unstructured fieldwork activities. Ultimately, this study design choice yields data that more accurately portrays important aspects of scientific fieldwork that are of interest to various stakeholders within NASA.


Evaluation Framework for Wearable Robotic Devices

Wearable robotic devices like powered exoskeletons and prostheses have enormous potential to assist those with reduced mobility/capabilites or rehabilitation as well as to offload/support loads on the user to reduce energy expenditure and risk of injury. In addition to the challenges associated with the physical design of such devices, most (if not all) evaluations are conducted in a laboratory, often on a treadmill, for which an individual’s kinematics have been shown to differ as compared to their daily activity kinematics. As a result, another ongoing open challenge is providing a framework for determining which products or control strategies is best for an individual, which will be the focus of this project.

Tantamount to the success of this framework is the ability to provide a personalized, objective assessment of performance during daily life. Extensions of our lab's methods employing wearable sensor arrays will likely reveal how participants learn to interact with assistive devices by studying their adaptation over time. A far-reaching end goal is an adaptive control strategy that “learns” alongside the participant to optimize their performance (e.g., minimize gait energy expenditure or maximize gait symmetry).

Determining Anatomical Frames of Reference for Inertial Motion Capture

Despite the exponential growth in using IMUs for biomechanical studies, future growth in inertial motion capture is stymied by a fundamental challenge - how to estimate the orientation of underlying bony anatomy using skin-mounted IMUs. This challenge is of paramount importance given the need to deduce the orientation of the bony anatomy to estimate joint angles. Unfortunately, a convention does not yet exist for how to define these anatomical frames for inertial motion capture and the four current approaches in the literature produce significantly different estimates for these frames to a degree that renders it difficult, if not impossible, to compare results across studies.

Consequently, a significant need remains for creating, validating, and adopting a standard for defining anatomical axes via inertial motion capture to fully realize this technology’s potential for biomechanical studies. This project will focus on how to accomplish this in a way that is repeatable and reproducible across testing sessions, subject populations, and technologies. The approach will focus on simulating IMU data from optical motion capture data and developing kinematic biomechanical constraints conducive to IMU data to automatically detect these reference frames.