A biomechanics and energetics dataset of neurotypical adults walking with and without kinematic constraints.

Numerous studies have explored the biomechanics and energetics of human walking, offering valuable insights into how we walk. However, prior studies focused on changing external factors (e.g.

Experimental evaluation of accuracy and efficiency of two control strategies for a novel foot commanded robotic laparoscope holders with surgeons.

The implementation of a laparoscope-holding robot in minimally invasive surgery enhances the efficiency and safety of the operation. However, the extra robot control task can increase the cognitive load on surgeons. A suitable interface may simplify the control task and reduce the surgeon load.

Adaptive auditory assistance for stride length cadence modification in older adults and people with Parkinson's.

Gait rehabilitation using auditory cues can help older adults and people with Parkinson's improve walking performance. While auditory cues are convenient and can reliably modify gait cadence, it is not clear if auditory cues can reliably modify stride length (SL), another key gait performance metric. Existing algorithms also do not address habituation or fluctuation in motor capability, and have not been evaluated with target populations or under dual-task conditions.

Effect of Tibial Component Misalignment on the Lower Limb Joint Kinematics During Squat.

The component orientation of the total knee replacement is critical to surgical outcomes. There have been many studies focused on knee movement for different component rotations. However, the effect of component misalignment on a dynamic movement, especially which requires high knee flexion, is not widely studied.

Auditory cueing strategy for stride length and cadence modification: a feasibility study with healthy adults.

People with Parkinson's Disease experience gait impairments that significantly impact their quality of life. Visual, auditory, and tactile cues can alleviate gait impairments, but they can become less effective due to the progressive nature of the disease and changes in people's motor capability. In this study, we develop a human-in-the-loop (HIL) framework that monitors two key gait parameters, stride length and cadence, and continuously learns a person-specific model of how the parameters change in response to the feedback.