Current Research Interests
Research in the Locomotion and Energetics Group focuses on a mechanistic understanding of human movement, and the application of this understanding to clinical populations.
Passive Gait Assistance
Many characteristics of human walking can be predicted from the body’s passive mechanical properties, as demonstrated by unpowered and powered dynamic walking devices. However, these devices walk substantially slower than humans. Recent simulations (see Dean and Kuo 2009 Supplementary Material) have shown that passive elastic joint actuation is able to produce more typical human gait patterns. We are currently investigating whether a passive elastic exoskeleton based on these simulations is able to make human walking easier, as quantified by reduced muscle activity and energy consumption. In the long term, such a device could be used as a low-cost method of providing gait assistance during rehabilitation for populations with limited locomotor function.
Post-Stroke Control Accuracy and Gait Function
Following a neurological injury such as a stroke, functional mobility is often limited. One potential contributor to this reduced function is altered sensorimotor integration, which can decrease an individual’s capacity to accurately control voluntary movement. We are currently investigating whether decreases in neural control accuracy predictably influence gait stability and economy. In the longer term, we plan to apply our findings to the development of rehabilitation devices or therapies to improve function.
Active Control of Gait Stability
Remaining upright while walking is a challenge of engineering and control, but is accomplished relatively easily by many humans. A potentially efficient strategy of maintaining stability is appropriate foot placement. We have recently found that human foot placement is predictably influenced by swing phase muscle activity, which appears to be based on the mechanical state of the stance leg (Dean 2012). We are currently investigating the possible sources of sensory feedback which humans may use to determine their choice of foot placement location.
Despite the redundancy found in the musculoskeletal and nervous systems, humans often prefer stereotyped movement patterns when performing a task. Changing the mechanical demands of a task, such as by altering the environment, can influence the preferred movement pattern. We have recently found that for a simple bouncing task, the preferred movement pattern is influenced by system mechanics (Raburn et al 2011) and gradually adapts toward the mechanical and metabolic optimum over time (Merritt et al 2012). We are currently investigating the proposal that proprioceptive feedback is integral to this adaptation process (Dean 2013) during human walking.
Relationship between Gait Stability and Economy
During walking, two apparent goals are to maintain stability and keep energetic cost low. Bipedal walking robots have been developed that are quite stable (ASIMO; Honda) and that do not expend much energy (Cornell Ranger), but not that meet both criteria. Recent model simulations have suggested a trade-off between gait stability and energetic demand. Subsequent experiments demonstrated that humans do not always prefer the gait with minimal energetic cost, but sometimes choose gaits that are more costly, but potentially more stable (Hunter et al 2010; Monsch et al 2012). We are currently investigating whether this potential trade-off can be formally quantified.